DETAILED ACTION
Status of Claims
The following is a Final Office Action in response to applicant’s amendments received on 05/23/2025.
Claims 1, 7, 11, 14, 17, 23, 27, 28, 33, 34, 37, 38, and 41-43 are amended. Claims 10 and 26 are cancelled. Claims 41-43 are newly added. Claims 1-9, 11-25, and 27-43 are considered in this Office Action. Claims 1-9, 11-25, and 27-43 are currently pending.
Response to Arguments
Applicant’s amendments necessitated new grounds of rejections set forth in this Office Action.
Response to §112(b) Arguments- Applicant’s arguments with respect to claim 41, applicant’s amendments to the claims overcome the indefinite rejection. The claim objections are withdrawn. An updated 35 U.S.C. 112(b) will address applicant’s amendments.
Response to § 101 Arguments- Applicant's arguments with respect to the 35 U.S.C. §101 rejection to claims have been considered, but are not persuasive.
Applicant argues that Applicant's claims do not recite a mental process because the claim limitations, viewed as an ordered combination, are not practically performable in the human mind. The claims require machine acquisition and coordination of sensor/video datasets from a mobile asset and remote sources and Al-based processing of the requested, time-synchronized datasets. Applicant's claims are tied to a particular machine environment that is integral to the claimed invention: a mobile asset, an onboard recorder/camera-based data acquisition and recording system, remote data sources, a web portal, and an AI video analytics system. The claims use that architecture to generate concrete safety/compliance outputs, including processed data, scores, and certification/decertification recommendations, that define a meaningful technological application, not a claim to "evaluation" in the abstract. See MPEP §§ 2106.04(d), 2106.05(a), 2106.05(b), and 2106.05(e). (Remarks pages 7, 22-23).
The examiner respectfully disagrees. The examiner notes the claims recite an abstract idea of assessing the performance skills of an operator of a mobile asset by reciting concepts performed in the human mind (including an observation, evaluation, judgment, opinion), which falls into the “mental process” group within the enumerated groupings of abstract ideas, wherein the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. (See MPEP 2106.04(a)(2)). The claims further fall into “Certain methods of organizing human activity”, particularly managing personal behavior (including social activities, teaching, and following rules or instructions).
The examiner further notes that the additional elements such as mobile asset, an onboard recorder/camera-based data acquisition and recording system, remote data sources, a web portal, and an AI video analytics system are not considered part of the abstract idea under Prong I and further evaluated under Prong II. These elements have been fully considered, however they are directed to the use of generic computing elements (Applicant’s Specification [0184] describes high level general purpose computer) to perform the abstract idea, which is not sufficient to amount to a practical application and is tantamount to simply saying “apply it” using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment (computer based operating environment) by using the computer as a tool to perform the abstract idea, which is not sufficient to amount to particular application. While receiving, using a data recorder of a data acquisition and recording system onboard the mobile asset, a set of first data based on at least one data signal from at least one of: at least one data source onboard the mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system; and at least one data source remote from the mobile asset is considered part of the abstract idea, if considered under Prong II as additional elements, it would amount to pre-solution activity, because it is generic step which amounts to data gathering step, wherein “at least one data source onboard a mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system” are recited at high level of generality and amounts to data gathering means. The examiner notes that the “a video analytics system comprising an artificial intelligence component” recited in claims has been considered. The claims do not impose any limits on how the video analytics system comprising an artificial intelligence component that is caused to perform processing least the set of first data and the set of second data into processed data. The claims also do not impose any limits on how the analysis is accomplished, and thus it can be performed in any way known to those of ordinary skill in the art. The video analytics system comprising an artificial intelligence component is recited at high level of generality which is not sufficient to amount to a practical application and is tantamount to simply saying “apply it” using a general-purpose computer, which merely serves to tie the abstract idea to a particular technological.
Applicant argues that Claims 33 and 37 further underscore that the invention is not mentally performable. Those claims require review of selected events and points along a path of travel of the mobile asset, identification of improper or unsafe operation by the specified operator, and comparison of processed data to a rule set and score system to generate a certification/decertification recommendation. The specification explains that, after determining the right ride to evaluate, a railroad officer who is logged into a secure portal can press a button and automatically obtain inward and outward video data for relevant operating scenarios. Spec. [00155]. The disclosure also states that "results of real time events are converted into a satisfactory or unsatisfactory score for engineer performance using a combination of artificial intelligence (AI) and other algorithmic techniques." Spec. [00160]. The improved engineer evaluation assistant is described as "an enhanced improvement" providing a "more efficient and faster way" to perform engineer- evaluation activities "in a unified user experience throughout the desired train route." Spec. [00153]. That is the language of a concrete technological workflow, not of a mental process. (Remarks page 23).
The examiner respectfully disagrees. The examiner notes the claims recite an abstract idea of assessing the performance skills of an operator of a mobile asset by reciting concepts performed in the human mind (including an observation, evaluation, judgment, opinion), which falls into the “mental process” group within the enumerated groupings of abstract ideas, wherein the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. (See MPEP 2106.04(a)(2)). The claims further fall into “Certain methods of organizing human activity”, particularly managing personal behavior (including social activities, teaching, and following rules or instructions). The examiner notes that the review of selected events and points along a path of travel of the mobile asset, identification of improper or unsafe operation by the specified operator, and comparison of processed data to a rule set and score system to generate a certification/decertification recommendation is a mental step which can be performed in the human mind or by the aid of a pen and paper, as they fall within an observation, evaluation, judgment, and opinion.
The applicant argues that the claims as a whole integrate any such concept into a practical application under Step 2A, Prong Two. Applicant's claimed functionality is tied to a particular machine environment that is integral to the claims: a mobile asset; an onboard data acquisition and recording system; onboard cameras and recorders; remote data sources; a web portal; and a video analytics system with an artificial intelligence component. The claims use that architecture to produce concrete safety and compliance outputs, including processed video/operational data, operator scores, and certification or decertification recommendations. This is not a claim that merely says "apply evaluation on a computer." It is a claim to a specific mobile-asset monitoring and recertification framework.
The examiner further notes that the additional elements such as mobile asset, an onboard recorder/camera-based data acquisition and recording system, remote data sources, a web portal, and an AI video analytics system are not considered part of the abstract idea under Prong I and further evaluated under Prong II. These elements have been fully considered, however they are directed to the use of generic computing elements (Applicant’s Specification [0184] describes high level general purpose computer) to perform the abstract idea, which is not sufficient to amount to a practical application and is tantamount to simply saying “apply it” using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment (computer based operating environment) by using the computer as a tool to perform the abstract idea, which is not sufficient to amount to particular application. While receiving, using a data recorder of a data acquisition and recording system onboard the mobile asset, a set of first data based on at least one data signal from at least one of: at least one data source onboard the mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system; and at least one data source remote from the mobile asset is considered part of the abstract idea, if considered under Prong II as additional elements, it would amount to pre-solution activity, because it is generic step which amounts to data gathering step, wherein “at least one data source onboard a mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system” are recited at high level of generality and amounts to data gathering means. The examiner notes that the “a video analytics system comprising an artificial intelligence component” recited in claims has been considered. The claims do not impose any limits on how the video analytics system comprising an artificial intelligence component that is caused to perform processing least the set of first data and the set of second data into processed data. The claims also do not impose any limits on how the analysis is accomplished, and thus it can be performed in any way known to those of ordinary skill in the art. The video analytics system comprising an artificial intelligence component is recited at high level of generality which is not sufficient to amount to a practical application and is tantamount to simply saying “apply it” using a general-purpose computer, which merely serves to tie the abstract idea to a particular technological.
The applicant asserts that The Office Action also errs in treating the additional elements as effectively irrelevant at Step 2A because they define allegedly generic computer implementation. MPEP § 2106.04(d) expressly states that "in Step 2A Prong Two, examiners should ensure that they give weight to all additional elements, whether or not they are conventional, when evaluating whether a judicial exception has been integrated into a practical application." Here, the Office Action dismisses the claimed onboard recorder, cameras, remote portal, and Al video analytics as generic computer implementation without addressing how those elements cooperate in the claimed mobile-asset monitoring workflow.
The examiner respectfully disagrees. The additional elements are directed to system, web portal, a data acquisition and recording system onboard the mobile asset, at least one signal from at least one of at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system and at least one data source remote from the mobile asset (means to collect data)and an artificial intelligence component of a video analytics system (recited at high level of generality), the web portal adapted to display at least one of the web portal and a display device, the displayed processed data comprising at least one video, and the displayed processed data adapted to display (amounts to displaying results)to implement abstract idea. However, these elements fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Furthermore, these elements have been fully considered, however they are directed to the use of generic computing elements (Applicant’s Specification [0184] describes high level general purpose computer) to perform the abstract idea, which is not sufficient to amount to a practical application and is tantamount to simply saying “apply it” using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment (computer based operating environment) by using the computer as a tool to perform the abstract idea, which is not sufficient to amount to particular application. While receiving, using a data recorder of a data acquisition and recording system onboard the mobile asset, a set of first data based on at least one data signal from at least one of: at least one data source onboard the mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system; and at least one data source remote from the mobile asset is considered part of the abstract idea, if considered under Prong II as additional elements, it would amount to pre-solution activity, because it is generic step which amounts to data gathering step, wherein “at least one data source onboard a mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system” are recited at high level of generality and amounts to data gathering means. The examiner notes that the “a video analytics system comprising an artificial intelligence component” recited in claims has been considered. The claims do not impose any limits on how the video analytics system comprising an artificial intelligence component that is caused to perform processing least the set of first data and the set of second data into processed data. The claims also do not impose any limits on how the analysis is accomplished, and thus it can be performed in any way known to those of ordinary skill in the art. The video analytics system comprising an artificial intelligence component is recited at high level of generality which is not sufficient to amount to a practical application and is tantamount to simply saying “apply it” using a general-purpose computer, which merely serves to tie the abstract idea to a particular technological.
Applicant asserts that under Step 2B, the record still does not establish that the ordered combination of claim elements is merely well-understood, routine, and conventional. Whether something is well-understood, routine, and conventional is a factual issue. Berkheimer v. HP Inc., 881 F.3d 1360, 1368 (Fed. Cir. 2018). The Office Action cites generic client-device disclosure and generic computer functionality, but that does not address the claimed ordered combination of onboard mobile-asset recording, acquisition of multi-source operational and video data, artificial-intelligence video analytics processing, rule-set/score-system comparison, and portal-based presentation of processed data and certification-related outputs. Nor does it address the specification's disclosure of concrete technical architecture and workflow improvements. See, e.g., Spec. [0055], [0068], [0076], [0089], [00153], [00155], [00160]. (Remarks Pages 25-27).
The examiner respectfully disagrees. As best understood by the Examiner, applicant’s argument appears to be based on a misunderstanding of the Berkheimer decision, which the Examiner emphasizes is germane only to Step 2B eligibility inquiry and only for “additional elements” (i.e., not the elements that actually recite the abstract idea). In particular, the Berkheimer memo provides guidelines for evaluating whether certain claim limitations (the “additional elements”) are well-understood, routine, and conventional, and describes the evidentiary requirements to support factual findings related thereto. Berkheimer v. HP Inc., 881 F.3d 1360 (Fed. Cir. 2018).
Accordingly, the Examiner emphasizes that a §101 rejection, including one based on a judicial exception, does not hinge on whether or not the entire claimed subject matter is directed to “well-understood, routine, and conventional activities,” as suggested by Applicant. Notably, a §101 rejection may be proper even if there are no claim elements deemed well-understood, routine, and conventional. We may assume that the techniques claimed are “[g]roundbreaking, innovative, or even brilliant,” but that is not enough for eligibility. Ass’n for Molecular Pathology v. Myriad Genetics, Inc., 569 U.S. 576, 591 (2013); accord buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1352 (Fed. Cir. 2014). Nor is it enough for subject-matter eligibility that claimed techniques be novel and nonobvious in light of prior art, passing muster under 35 U.S.C. §§ 102 and 103. See Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 89–90 (2012); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151 (Fed. Cir. 2016) (“[A] claim for a new abstract idea is still an abstract idea. The search for a § 101 inventive concept is thus distinct from demonstrating §102 novelty.”); Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1315 (Fed. Cir. 2016) (same for obviousness) (Symantec).
The examiner notes the claims do not impose any limits on how receiving, using a data recorder of a data acquisition and recording system onboard the mobile asset, a set of data based on at least one data signal from at least one of: at least one data source onboard the mobile asset, the at least one data source onboard the mobile asset comprising at least one camera and at least one data recorder of the data acquisition and recording system; and at least one data source remote the mobile asset.. The claims also do not impose any limits on how the analysis is accomplished, and thus it can be performed in any way known to those of ordinary skill in the art. Additionally, with respect to the Berkheimer court case, below can be found evidence provided by the Examiner that provides, based on 2B analysis, how the claims are viewed as well-understood, routine, and conventional activity for consistency with the Federal Circuit’s decision in Berkheimer and MPEP 2106.5(d). This is supported by the fact that the disclosure does not provide the details necessary to provide significantly more than the abstract idea performed on a general-purpose computer and therefore not significantly more. Prior art references teach the limitations of receiving data, and may or may not include other components 172 such as an image/video/sound capture device such as a camera, voice recording microphone, stylus, etc. is a known technique. Thus, the use of camera to gather data, as recognized in art, which predate Applicant’s invention. As disclosed in Salameh et al. (US Pub. No 2015/0149321 A1) “0070] As stated above, FIG. 1B is an exemplary illustration of well-known, conventional computing machine as client computing machines or devices that may be used to implement and access one or more embodiments of the network-based social-marketplace platform 102 of the present invention. As illustrated, the client computing device 108 (hereinafter simply referred to as client device 108) may be any well-known conventional computing machine, non-limiting examples of which may include netbooks, notebooks, laptops, smart tablets, mobile devices such as feature or smart mobile phones, or any other devices that are Network and or Internet enabled. The client device 108 includes the typical, conventional components such as an I/O module 160 (e.g., a keyboard or touch screen display, etc.), a storage module 162 for storing information (may use Cloud Computing Systems and services), a memory 164 used by a processor 166 to execute programs, a communication module 168 for implementing desired communication protocol, a communications interface (e.g., transceiver module) 170 for transmitting and receiving data, and may or may not include other components 172 such as an image/video/sound capture device such as a camera, voice recording microphone, stylus, etc.” . Therefore, as shown by cited prior art references, the 2B features of the invention are “routine and conventional.” It is when the claims are wholly directed to the abstract idea without anything significantly more in the claims that the claims are deemed to preempt or monopolize the exception (i.e. the abstract idea).
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrate the abstract idea into a practical application. Their collective functions merely provide conventional computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that the ordered combination amounts to significantly more than the abstract idea itself.
Applicant argues that like the claims in Desjardins, Applicant’s claims define an improvement to the technical field of safe railroad operation, and in particular confirming through automated procedures the skills, abilities and competency of those engineers who operate large moving railroad equipment. These confirmation procedures are required by U.S. Federal Regulation 49 CFR $240.127 to be conducted by railroad management to ensure only qualified persons operate a locomotive or train as stated in par. [00148] of Applicant's specification. Applicant submits that safe railroad operation matters qualify without question as technology and a technical field. (remarks pages 28-35).
The examiner respectfully disagrees. The examiner notes that the claims in Desjardins reflects a specific improvement that addressed the technical problem of "catastrophic forgetting" in continual learning systems, while allowing artificial intelligence systems to variously optimize system performance, use less storage capacity and reduce system complexity by showing an improved way of training a machine learning model that protected the model's knowledge about previous tasks while allowing it to effectively learn new tasks. Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision) (precedential). Unlike Desjardins, applicant's claims are directed to an abstract idea of assessing the performance skills of an operator of a mobile asset by reciting concepts performed in the human mind (including an observation, evaluation, judgment, opinion), which falls into the “mental process” group within the enumerated groupings of abstract ideas, wherein the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. (See MPEP 2106.04(a)(2)). The claims further fall into “Certain methods of organizing human activity”, particularly managing personal behavior (including social activities, teaching, and following rules or instructions). The additional elements are directed to system, web portal, a data acquisition and recording system onboard the mobile asset, at least one signal from at least one of at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system and at least one data source remote from the mobile asset (means to collect data)and an artificial intelligence component of a video analytics system (recited at high level of generality), the web portal adapted to display at least one of the web portal and a display device, the displayed processed data comprising at least one video, and the displayed processed data adapted to display (amounts to displaying results)to implement abstract idea. However, these elements fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Furthermore, these elements have been fully considered, however they are directed to the use of generic computing elements (Applicant’s Specification [0184] describes high level general purpose computer) to perform the abstract idea, which is not sufficient to amount to a practical application and is tantamount to simply saying “apply it” using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment (computer based operating environment) by using the computer as a tool to perform the abstract idea, which is not sufficient to amount to particular application. While receiving, using a data recorder of a data acquisition and recording system onboard the mobile asset, a set of first data based on at least one data signal from at least one of: at least one data source onboard the mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system; and at least one data source remote from the mobile asset is considered part of the abstract idea, if considered under Prong II as additional elements, it would amount to pre-solution activity, because it is generic step which amounts to data gathering step, wherein “at least one data source onboard a mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system” are recited at high level of generality and amounts to data gathering means. The examiner notes that the “a video analytics system comprising an artificial intelligence component” recited in claims has been considered. The claims do not impose any limits on how the video analytics system comprising an artificial intelligence component that is caused to perform processing least the set of first data and the set of second data into processed data. The claims also do not impose any limits on how the analysis is accomplished, and thus it can be performed in any way known to those of ordinary skill in the art. The video analytics system comprising an artificial intelligence component is recited at high level of generality which is not sufficient to amount to a practical application and is tantamount to simply saying “apply it” using a general-purpose computer, which merely serves to tie the abstract idea to a particular technological.
Accordingly, Applicant's arguments with respect to the 35 U.S.C. §101 rejection to claims are not persuasive, and updated 35 U.S.C. § 101 rejection will address applicant's amendments.
Response to § 103 Arguments- Applicant’s amendments and arguments have been considered however applicant’s arguments are primarily raised in light of applicant’s amendments and updated 35 U.S.C. 103 rejection will address applicant’s amendments.
Examiner Notes
With respect to method claim 42, the claim recites the following limitations: “the operator being at a set of controls, the set of controls being typical of controls used on the mobile asset operated on at least one of a specified railroad and a segment of the specified railroad”, which is not a positively recited method step. The phrases describe a result or condition without identifying an act performed. Because these steps are merely descriptive, the limitations are not given patentable weight. See MPEP 2173.05(q).
With respect to method claim 43, the claim recites the following limitation ““he operator being at a set of controls, the set of controls being typical of controls used on the mobile asset operated on at least one of a specified railroad and a segment of the specified railroad,” which is not a positively recited method step. The phrase describes a result or condition without identifying an act performed. Because this step is merely descriptive, this limitation is not given patentable weight. See MPEP 2173.05(q).
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claim 41 is rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention.
Claim 41 recites the limitation "the DP" and “the web portal”. There is insufficient antecedent basis for this limitation in the claim.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-9, 11-25, and 27-43 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
Claims 1-9, 11-25, and 27-43 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance with the “Patent Subject Matter Eligibility Guidance” (as explained in MPEP 2106).
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is first noted that the method (claims 1-9 and 11-16), the system (claim 17-25 and 27-32), the method (claims 33-36), the system (claims 37-40), the method (claim 41), the method (claim 42), and the method (claim 43) are directed to an eligible category of subject matter (i.e., process, machine, and article of manufacture respectively). Thus, Step 1 is satisfied.
With respect to Step 2, and in particular Step 2A, it is next noted that the claims recite an abstract idea of assessing the performance skills of an operator of a mobile asset by reciting concepts performed in the human mind (including an observation, evaluation, judgment, opinion), which falls into the “mental process” group within the enumerated groupings of abstract ideas, wherein the courts consider a mental process (thinking) that "can be performed in the human mind, or by a human using a pen and paper" to be an abstract idea. (See MPEP 2106.04(a)(2)). The claims further fall into “Certain methods of organizing human activity”, particularly managing personal behavior (including social activities, teaching, and following rules or instructions). The limitations reciting the abstract idea are highlighted in italics and the limitation directed to additional elements highlighted in bold, as set forth in exemplary claim 17, are: A system for automating the assessment of safety performance skills of a specified operator of a mobile asset, comprising: a web portal adapted to receive a request from a user, the request comprising identification of the specified operator of the mobile asset and a specified time range; a data acquisition and recording system onboard the mobile asset comprising at least one data recorder, the data acquisition and recording system adapted to receive a set of first data related to the operational performance characteristics of the mobile asset, and a set of second data related to the specified operator and the specified time range, the set of second data comprising a subset of the set of first data, the set of first data based on at least one data signal from at least one of: at least one data source onboard the mobile asset, the at least one on board data source including at least one of at least one camera and the at least one data recorder of the data acquisition and recording system; and at least one data source remote from the mobile asset; a video analytics system comprising an artificial intelligence component, the video analytics system and the artificial intelligence component adapted to process the set of first data and the set of second data into processed data, compare the processed data to a rule set directed to safe operation of mobile assets, and analyze the performance of the specified operator, the rule set part of a score system derived from the safe operation of mobile assets, implementation of the score system resulting in a score, the score equating to one of certifying the specified operator and decertifying the specified operator, the rule set part of a score system derived from the safe operation of mobile assets, implementation of the score system resulting in a score, the score equating to one of certifying the specified operator and decertifying the specified operator; and the web portal adapted to display at least one of the processed data and the score on at least one of the web portal and a display device, the displayed processed data comprising at least one video, and the displayed processed data adapted to be at least one of viewed by the user and compared to rules directed to the safe operation of mobile assets. Claims 1, 33, and 37 substantially recite the same limitation as claim 17 and therefore subject to the same rationale.
The limitations reciting the abstract idea are highlighted in italics and the limitation directed to additional elements highlighted in bold, as set forth in exemplary claim 41, are: A method for automating the assessment of safety performance skills of a specified operator of a mobile asset comprising the steps of: processing, using an artificial intelligence component of a video analytics system, at least a set of first data and a set of second data into processed data, the set of first data related to the operational performance characteristics of the mobile asset, the set of first data gathered from the mobile asset and the set of second data gathered from a source remote from the mobile asset; analyzing, using the video analytics system, the processed data in a score system of the video analytics system, the score system comprising a set of rules directed to safe operation of the mobile asset, each rule or a combination of the rules of the set of rules selected from the group consisting of the mobile asset operator performance of a class III brake test, the mobile asset operator efficiently starts movement of the mobile asset, the mobile asset operator strips a throttle of the mobile asset, the mobile asset operator failed to wait 10 seconds before transition to dynamic brakes, the mobile asset operator independently set up and used a brake properly of the mobile asset, the mobile asset operator performed proper running release, the mobile asset operator performed a proper combination braking procedure, the mobile asset operator made proper use of the at least one of a horn, bell, headlights, and telemetry of the mobile asset, the mobile asset operator did not fail to initialize a trip optimizer of the mobile asset during a trip, a positive train control (PTC) of the mobile asset was properly initialized and monitored by the mobile asset operator, and the DP was properly set up and brake tested by the mobile asset operator; the analyzing step establishing a score of the processed data, a score attached to each selected rule; displaying, using a display device of the web portal, at least one of the processed data and the score, the score corresponding to one of a certification and decertification of the mobile asset operator. Claims 42-43 substantially recite the same limitation as claim 42 and therefore subject to the same rationale.
With respect to Step 2A Prong Two, the judicial exception is not integrated into a practical application. The additional elements are directed to system, web portal, a data acquisition and recording system onboard the mobile asset, at least one signal from at least one of at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system and at least one data source remote from the mobile asset (means to collect data)and an artificial intelligence component of a video analytics system (recited at high level of generality), the web portal adapted to display at least one of the web portal and a display device, the displayed processed data comprising at least one video, and the displayed processed data adapted to display (amounts to displaying results)to implement abstract idea. However, these elements fail to integrate the abstract idea into a practical application because they fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment. Furthermore, these elements have been fully considered, however they are directed to the use of generic computing elements (Applicant’s Specification [0184] describes high level general purpose computer) to perform the abstract idea, which is not sufficient to amount to a practical application and is tantamount to simply saying “apply it” using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment (computer based operating environment) by using the computer as a tool to perform the abstract idea, which is not sufficient to amount to particular application. While receiving, using a data recorder of a data acquisition and recording system onboard the mobile asset, a set of first data based on at least one data signal from at least one of: at least one data source onboard the mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system; and at least one data source remote from the mobile asset is considered part of the abstract idea, if considered under Prong II as additional elements, it would amount to pre-solution activity, because it is generic step which amounts to data gathering step, wherein “at least one data source onboard a mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system” are recited at high level of generality and amounts to data gathering means. The examiner notes that the “a video analytics system comprising an artificial intelligence component” recited in claims has been considered. The claims do not impose any limits on how the video analytics system comprising an artificial intelligence component that is caused to perform processing least the set of first data and the set of second data into processed data. The claims also do not impose any limits on how the analysis is accomplished, and thus it can be performed in any way known to those of ordinary skill in the art. The video analytics system comprising an artificial intelligence component is recited at high level of generality which is not sufficient to amount to a practical application and is tantamount to simply saying “apply it” using a general-purpose computer, which merely serves to tie the abstract idea to a particular technological.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional limitations are directed to: system, web portal, a data acquisition and recording system onboard the mobile asset, at least one signal from at least one of at least one data source onboard the mobile asset comprising at least one of at least one camera and at least one data recorder of the data acquisition and recording system and at least one data source remote from the mobile asset (means to collect data)and an artificial intelligence component of a video analytics system (recited at high level of generality), the web portal adapted to display at least one of the web portal and a display device, the displayed processed data comprising at least one video, and the displayed processed data adapted to display (amounts to displaying results)to implement abstract idea. These elements have been considered, but merely serve to tie the invention to a particular operating environment (i.e., computer-based implementation), though at a very high level of generality and without imposing meaningful limitation on the scope of the claim. In addition, Applicant’s Specification ([0184]) describes generic off-the-shelf computer-based elements for implementing the claimed invention, and which does not amount to significantly more than the abstract idea, which is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo.
The examiner notes the claims do not impose any limits on how receiving, using a data recorder of a data acquisition and recording system onboard the mobile asset, a set of data based on at least one data signal from at least one of: at least one data source onboard the mobile asset, the at least one data source onboard the mobile asset comprising at least one camera and at least one data recorder of the data acquisition and recording system; and at least one data source remote the mobile asset.. The claims also do not impose any limits on how the analysis is accomplished, and thus it can be performed in any way known to those of ordinary skill in the art. Additionally, with respect to the Berkheimer court case, below can be found evidence provided by the Examiner that provides, based on 2B analysis, how the claims are viewed as well-understood, routine, and conventional activity for consistency with the Federal Circuit’s decision in Berkheimer and MPEP 2106.5(d). This is supported by the fact that the disclosure does not provide the details necessary to provide significantly more than the abstract idea performed on a general-purpose computer and therefore not significantly more. Prior art references teach the limitations of receiving data, and may or may not include other components 172 such as an image/video/sound capture device such as a camera, voice recording microphone, stylus, etc. is a known technique. Thus, the use of camera to gather data, as recognized in art, which predate Applicant’s invention. As disclosed in Salameh et al. (US Pub. No 2015/0149321 A1) “0070] As stated above, FIG. 1B is an exemplary illustration of well-known, conventional computing machine as client computing machines or devices that may be used to implement and access one or more embodiments of the network-based social-marketplace platform 102 of the present invention. As illustrated, the client computing device 108 (hereinafter simply referred to as client device 108) may be any well-known conventional computing machine, non-limiting examples of which may include netbooks, notebooks, laptops, smart tablets, mobile devices such as feature or smart mobile phones, or any other devices that are Network and or Internet enabled. The client device 108 includes the typical, conventional components such as an I/O module 160 (e.g., a keyboard or touch screen display, etc.), a storage module 162 for storing information (may use Cloud Computing Systems and services), a memory 164 used by a processor 166 to execute programs, a communication module 168 for implementing desired communication protocol, a communications interface (e.g., transceiver module) 170 for transmitting and receiving data, and may or may not include other components 172 such as an image/video/sound capture device such as a camera, voice recording microphone, stylus, etc.” . Therefore, as shown by cited prior art references, the 2B features of the invention are “routine and conventional.” It is when the claims are wholly directed to the abstract idea without anything significantly more in the claims that the claims are deemed to preempt or monopolize the exception (i.e. the abstract idea).
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrates the abstract idea into a practical application. Their collective functions merely provide conventional computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that the ordered combination amounts to significantly more than the abstract idea itself.
The dependent claims have been fully considered as well (for example, claims 2/18 the at least one camera comprising at least one of at least one 360 degrees camera located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset, at least one fixed camera located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset, and at least one microphone located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset, wherein the at least one 360 degrees camerasaying “apply it” using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment (computer based operating environment) by using the computer as a tool to perform the abstract idea, which is not sufficient to amount to particular application. These elements have been considered, but merely serve to tie the invention to a particular operating environment (i.e., computer-based implementation), though at a very high level of generality and without imposing meaningful limitation on the scope of the claim. In addition, Applicant’s Specification ([0184]) describes generic off-the-shelf computer-based elements for implementing the claimed invention, and which does not amount to significantly more than the abstract idea, which is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo), however, similar to the finding for claims above, these claims are similarly directed to the abstract idea of concepts of mental process, without integrating it into a practical application and with, at most, a general-purpose computer that serves to tie the idea to a particular technological environment, which does not add significantly more to the claims.
The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to significantly more than the abstract idea.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 3, 4, 12, 16, 17, 19, 50, 28, and 32 are rejected under 35 U.S.C. 103 as being unpatentable over William E. Durie (US 20170263120 A1, hereinafter “Durie”) in view of Kenji Fujii (US 2020/0364800 A1, hereinafter “Fujii”) in view of Ronald Ziegler (US 2010/0039247 A1, hereinafter “Ziegler”)
Claim 1/17
Durie teaches:
A method for automating the assessment of safety performance skills of a specified operator of a mobile asset([0194] The vehicle data manager 10 collects information about driver behavior and/or performance), comprising the steps of:
receiving, using a data recorder of a data acquisition and recording system onboard the mobile asset, a set of first data based on at least one data signal from at least one of: at least one data source onboard the mobile asset, the at least one data source onboard the mobile asset includingfrom the mobile asset ([0011] the vehicle data management device configured to establish a vehicle record, wherein the vehicle record includes video footage captured by the video capture device. [0189] VDM's 10 functions as described herein, and which is communicably coupled to various devices and/or sensors within the vehicle 101, as well as to the network 12. [0190] According to embodiments of the present disclosure, the VDM 10 is configured to establish a vehicle record. The vehicle record may be a set of data stored locally in the mobile environment 101 and/or transmitted via the network 12 to other environments for later storage, use, and integration with other vehicle records. [0210] The video capture device 26 may be any imaging device capable of capturing visual information within its field of view, for example, a camera or a camcorder, and transmitting some or all of such visual information to the VDM 10. Video capture devices 26 may be internal and/or external to the vehicle 101, and can capture both events happening inside or outside the vehicle, as well as weather conditions, pedestrians, other vehicles, traffic signals, and the like);
providing, using the data source onboard the mobile asset, video data and mobile asset operational performance data([0174] FIG. 14 illustrates a report showing vehicle speed, engine speed, ignition, left turn, right turn, brake activation, spotter switch activation, reverse activation, emergency light activation, siren activation, and driver's seatbelt activation data over a particular length of time corresponding to a run, or an emergency response. [0209] and [0228] A rotation and/or speed sensor and/or a speed sensing device 24 may also be communicably coupled to the VDM 10. [0024]and [0229] and the video capture device, the vehicle data management device configured to establish a vehicle record, wherein the vehicle record includes video footage captured by the video capture device, wherein the vehicle data management device is further configured to determine whether a particular safety situation exists with the emergency vehicle based on the visual information):
receiving, using a web portal remote from the mobile asset, a request from a user comprising identification of the specified operator and a specified time range([0273] The enterprise storage server 126 and/or enterprise application server 128, which may be a single server or separate servers, may be configured to permit access to the vehicle record data, to permit report generation based on a number of different user selectable factors, including time, vehicle ID, driver ID, and other factors [0193] For example, the enterprise workstation 122 accesses a web interface and/or thin client web browser application which requests the information over the network 12 from application server 128. [0276] The report query screen may allow the user to select individual drivers, a group of drivers, or all drivers, and show vehicle data records or statistics for the selected driver(s). The report query may allow the user to create reports based on a specific driver or group of drivers that operated a specific vehicle or group of vehicles. The report query may allow a user to select a date and/or time range);
receiving, using the data acquisition and recording system onboard the mobile asset, a set of second data related to the specified operator and the specified time range([0276] The report query screen may allow the user to select individual drivers, a group of drivers, or all drivers, and show vehicle data records or statistics for the selected driver(s). The report query may allow the user to create reports based on a specific driver or group of drivers that operated a specific vehicle or group of vehicles. The report query may allow a user to select a date and/or time range. [0277] The report query may provide for the selection of a summary of the requested data, or trends for the selected data, based on user-defined trend periods. [0278] When the user loads a user-created query, the query may automatically populate with the most recent and accurate results,), the set of second data comprising a subset of the set of first data([0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range, according to embodiments of the present disclosure. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events,), based on at least one data signal from at least one of: the at least one data source onboard the mobile asset; and the at least one data source remote from the mobile asset([0011] the vehicle data management device configured to establish a vehicle record, wherein the vehicle record includes video footage captured by the video capture device. [0189] VDM's 10 functions as described herein, and which is communicably coupled to various devices and/or sensors within the vehicle 101, as well as to the network 12. [0190] the VDM 10 is configured to establish a vehicle record. The vehicle record may be a set of data stored locally in the mobile environment 101 and/or transmitted via the network 12 to other environments for later storage, use, and integration with other vehicle records. Video capture devices 26 may be internal and/or external to the vehicle 101, and can capture both events happening inside or outside the vehicle, as well as weather conditions, pedestrians, other vehicles, traffic signals, and the like).
and displaying, using a display device of the web portal, at least one of the processed data and the score, the processed data comprising at least one video, the displayed processed data adapted to be viewed by the user(FIG. 11 illustrates an example of a driver safety report as it may be displayed by server 128 via a remote internet interface, [0300] The enterprise application server 128 may also be configured to provide a “second-by-second report,” which may display a user-defined date and/or time period, and resolution of all monitored inputs and indicators in a graphical format, with time being the horizontal axis and the value and description of the input displayed on the vertical axis. The second-by-second report may also permit the user to directly access a video presentation of a selected portion of the second-by-second graph, for example with a mouse click and/or a hot key ).
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Fujii teaches:
processing, using an artificial intelligence component of a video analytics system, at least the set of first data and the set of second data into processed data, the set of first data including the video data and the mobile asset operational performance data([0051] The machine learning module 124 is comprised of at least one insurance machine learning algorithm to analyze the data from the sensors 114, diagnostics module 116, engine control unit 118 and self-driving module 121 to generate driver scores and trip information. [0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data);
analyzing, using at least one of the video analytics systems and the user, the performance of the specified operator by comparing the processed data to a score system([0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data), the score system derived from a rule set directed to safe operation of mobile assets([0092] FIG. 7 is a flow diagram illustrating an exemplary method 700 for calculating a driver score of a driver of a vehicle. As defined above, the driver may be a person or the vehicle itself if the self-driving feature is engaged. [0093] For example, if the driver suddenly brakes, the vehicle module may check the corresponding sensor data over a 10 second time frame to determine the time of the greatest deceleration. When the vehicle module determines that a risky event has occurred, a severity level between 0 and 3, (or between 0 and 4) for example, is assigned and the trip summary is updated. The system may automatically assume a trip severity of 4 for every minute of the trip where the trip score is a number from 0-100, after taking into consideration the trip's configured typical severity (or predetermined severity or threshold) and the actual severity per minute. Table 1 further illustrates scores associated with safe operation of vehicle. Further, see [0095]-[0097]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie to incorporate the teachings of Fujii to include processing, using an artificial intelligence component of a video analytics system, at least the set of first data and the set of second data into processed data, the set of first data including the video data and the mobile asset operational performance data and analyzing, using at least one of the video analytics systems and the user, the performance of the specified operator by comparing the processed data to a score system, the score system derived from a rule set directed to safe operation of mobile assets as part of the grading system of Durie. Doing so would improve the efficiency and accuracy of business operations. [0005].
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range, according to embodiments of the present disclosure. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Zielger teaches:
the comparison resulting in a score for the operator, the score recommending one of certifying and decertifying the operator ([0169]"performance tuning" may be utilized as a way to rank authorized and licensed/certified operators according to experience and skill, and to adjust the operating characteristics of the mobile asset 12 accordingly. For example, operator performance ratings such as P1, P2 and P3 can be used to differentiate authorized operators, where P3 may correspond to a beginner, P2 may correspond to an intermediate skilled operator and P1 may correspond to an advanced skilled operator. [0170] As an authorized operator's performance rating is improved, the mobile asset may unlock or otherwise enable advanced features, modify features and mobile asset capabilities and/or otherwise adjust one or more operating characteristics to match the capability of the operator).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie to incorporate the teachings of Zielger to include the comparison resulting in a score for the operator, the score recommending one of certifying and decertifying the operator as part of the system of Durie. Doing so would improve the efficiency and accuracy of business operations. [0002].
Claim 3/19
While Durie teaches in [0011] the vehicle data management device configured to establish a vehicle record, wherein the vehicle record includes video footage captured by the video capture device. [0189] VDM's 10 functions as described herein, and which is communicably coupled to various devices and/or sensors within the vehicle 101, as well as to the network 12. [0190] According to embodiments of the present disclosure, the VDM 10 is configured to establish a vehicle record. The vehicle record may be a set of data stored locally in the mobile environment 101 and/or transmitted via the network 12 to other environments for later storage, use, and integration with other vehicle records. Video capture devices 26 may be internal and/or external to the vehicle 101, and can capture both events happening inside or outside the vehicle, as well as weather conditions, pedestrians, other vehicles, traffic signals, and the like. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Fujii further teaches:
The method of claim 1, further including at least one of: at least one video recorder located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset; at least one sound recorder located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset; at least one accelerometer on board the mobile asset; at least one of at least one gyro meter and at least one gyroscope onboard the mobile asset; and at least one magnetometer onboard the mobile asset([0008] triggering recording of video data using a camera on-board the vehicle; [0061] The GPU inputs can be received from vehicle cameras, such as dashboard cameras and driving assistance cameras. [0048] The vehicle module 104 gathers driver data using the various sensors 114 provided in the vehicle (e.g., speed sensors, accelerometers, GPS locators, tire pressure sensors, self-driving sensors, and Audio/Visual sensors, such as backup cameras, and anti-theft theft devices) that are typically connected to the ECU via a Controller Area Network (CAN) bus for example).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie to incorporate the teachings of Fujii to include at least one of: at least one video recorder located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset; at least one sound recorder located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset; at least one accelerometer on board the mobile asset; at least one of at least one gyro meter and at least one gyroscope onboard the mobile asset; and at least one magnetometer onboard the mobile asset as part of the sensors of Durie. Doing so would improve the efficiency and accuracy of business operations. [0005].
Claim 4/20
Durie teaches:
The method of claim 1, the set of first data further comprising at least one of event data recorder data, accelerometer data, gyrometer data, gyroscope data, fuel volume data, microphone data, inward facing 360 degrees camera data, outward facing 360 degrees camera data, inward facing fixed camera data, and outward facing fixed camera data([0011] In Example 8, a system for vehicle data management according to embodiments of the present disclosure includes an accelerometer, wherein the accelerometer is mounted in a vehicle and is configured to measure an accelerometer specific force of the vehicle, a speed sensor, wherein the speed sensor is configured to measure a speed of the vehicle, a video capture device, a vehicle data management device communicably coupled to the accelerometer, the speed sensor, and the video capture device, the vehicle data management device configured to establish a vehicle record, [0231] A VDM 10 creates a vehicle record, for example a vehicle driving safety record, based on various types of information which may include, without limitation, driver identification information, seatbelt information, vehicle backing information, force information, and speed information. [0190] the VDM 10 is configured to establish a vehicle record. The vehicle record may be a set of data stored locally in the mobile environment 101 and/or transmitted via the network 12 to other environments for later storage, use, and integration with other vehicle records. Video capture devices 26 may be internal and/or external to the vehicle 101, and can capture both events happening inside or outside the vehicle, as well as weather conditions, pedestrians, other vehicles, traffic signals, and the like).
Claim 12/28
Durie teaches:
The method of claim 1, the set of first data further comprising at least one of fuel data, weather data, train consist data, crew data, time data, and movement authority data for a specified course of movement of the mobile asset(Figures 11-18; (0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range [0273] The enterprise storage server 126 and/or enterprise application server 128, which may be a single server or separate servers, may be configured to permit access to the vehicle record data, to permit report generation based on a number of different user selectable factors, including time, vehicle ID, driver ID, and other factors [0193] For example, the enterprise workstation 122 accesses a web interface and/or thin client web browser application which requests the information over the network 12 from application server 128. [0276] The report query screen may allow the user to select individual drivers, a group of drivers, or all drivers, and show vehicle data records or statistics for the selected driver(s). The report query may allow the user to create reports based on a specific driver or group of drivers that operated a specific vehicle or group of vehicles. The report query may allow a user to select a date and/or time range).
Claim 16/32
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range, according to embodiments of the present disclosure. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Ziegler teaches:
The method of claim 1, further comprising: determining an automated score-based recommendation for one of certification and decertification of the specified operator ([0169] "performance tuning" may be utilized as a way to rank authorized and licensed/certified operators according to experience and skill, and to adjust the operating characteristics of the mobile asset 12 accordingly. For example, operator performance ratings such as P1, P2 and P3 can be used to differentiate authorized operators, where P3 may correspond to a beginner, P2 may correspond to an intermediate skilled operator and P1 may correspond to an advanced skilled operator. [0170] As an authorized operator's performance rating is improved, the mobile asset may unlock or otherwise enable advanced features, modify features and mobile asset capabilities and/or otherwise adjust one or more operating characteristics to match the capability of the operator. [0171] Operator rating may be based upon a number of factors, including for example the currently held operator licenses, certifications, number of years of experience, etc. Further, operator rating may be based upon actual monitored measures of operator capabilities. As noted above, the mobile asset information linking device 38 may be capable of monitoring and logging aspects of mobile asset operation, and to wirelessly transmit that information to the network, for example, to the mobile asset application server 14. As such, the metrics used to evaluate and determine operator skill may be based upon actual event and other data collected by a corresponding mobile asset information linking device 38. For example, if an operator trips the impact sensors 60 a predetermined number of times, or when traveling at certain speeds, the corresponding performance rating may be adjusted. This example was meant by way of illustration and not by way of limitation of the many approaches to integrate actual operator performance/usage/capability information into a determination of performance ranking).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie and Fujii to incorporate the teachings of Zielger to include determining an automated score-based recommendation for one of certification and decertification of the specified operator as part of the system of Fujii. Doing so would improve the efficiency and accuracy of business operations. [0002].
Claims 2, 6, 18, and 22 are rejected under 35 U.S.C. 103 as being unpatentable over Durie in view of Fujii in view of Ziegler, as applied in claim 1 and 17, and further in view of Glen Dargy (US 2015/0094885 A1, hereinafter “Dargy”).
Claim 2/18
Durie teaches:
and at least one microphone located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset ([0085] In Example 82, the system of any of Examples 80 or 81, further comprising an audio capture device located on the vehicle, the vehicle data management device further configured to automatically stream audio footage from the audio capture device. [0211] An audio capture device 28 may also be communicably coupled to the VDM 10, according to embodiments of the present disclosure. The audio capture device 26 may be any audio device capable of capturing sound information, for example a digital sound recorder or a voice recorder, and transmitting some or all of such audio data to the VDM 10, according to embodiments of the present disclosure. The video capture device 26 and audio capture device 28 may be one device, for example in the form of a camcorder; alternatively, one audiovisual device with both audio and video capabilities may serve as an audio capture device 28 only, a video capture device 26 only, or both, according to embodiments of the present disclosure. The audio capture device 28 may also be configured to detect audio levels and/or ambient noise, for example the level of ambient noise in decibels, according to embodiments of the present disclosure).
While Durie teaches in [0011] In Example 8, a system for vehicle data management according to embodiments of the present disclosure includes an accelerometer, wherein the accelerometer is mounted in a vehicle and is configured to measure an accelerometer specific force of the vehicle, a speed sensor, wherein the speed sensor is configured to measure a speed of the vehicle, a video capture device, a vehicle data management device communicably coupled to the accelerometer, the speed sensor, and the video capture device, the vehicle data management device configured to establish a vehicle record, [0231] A VDM 10 creates a vehicle record, for example a vehicle driving safety record, based on various types of information which may include, without limitation, driver identification information, seatbelt information, vehicle backing information, force information, and speed information. [0190] the VDM 10 is configured to establish a vehicle record. The vehicle record may be a set of data stored locally in the mobile environment 101 and/or transmitted via the network 12 to other environments for later storage, use, and integration with other vehicle records. Video capture devices 26 may be internal and/or external to the vehicle 101, and can capture both events happening inside or outside the vehicle, as well as weather conditions, pedestrians, other vehicles, traffic signals, and the like. Durie does not explicitly teach the following, however analogous reference Dargy teaches:
The method of claim 1, comprising at least one of at least one 360 degrees camera located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset([0026] The external camera 14 preferably comprises a 360° camera configured to generate an image that spans 360° horizontally around the external camera 14 and/or the vehicle 10), at least one fixed camera located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset ([0028] An input-capture system comprising an internal camera 48 is mounted in the interior of the vehicle 10 and positioned to capture an image of the display device 34 and the keypad 38. As depicted in FIGS. 2-3, the internal camera 48 is mounted along a rear wall 50 of the interior of the vehicle 10 but it might be mounted in any desired location that provides a suitable view of the display device 34 and keypad 38.)), wherein the at least one 360 degrees camera is one of an inward facing and an outward facing and the at least one fixed camera is one of an inward facing and an outward facing ([0024] The external camera 14 is preferably configured to capture video... Other forms and configurations of cameras and combinations thereof that capture 360-degree views of another viewing angle maybe employed in embodiments of the invention without departing from the scope of described herein. [0028] The internal camera 48 may comprise any available video or still camera technology without departing from the scope of the embodiments of the invention described herein. The examiner notes that the 360-degree view camera and the fixed camera can be of any configuration, including an inward and outward facing camera as illustrated in figures 1-3).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, and Zielger to incorporate the teachings of Dargy to include at least one of at least one 360 degrees camera located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset, at least one fixed camera located in at least one of in the mobile asset, on the mobile asset, and in the vicinity of the mobile asset, wherein the at least one 360 degrees camera is one of an inward facing and an outward facing and the at least one fixed camera is one of an inward facing and an outward facing as part of the system of Durie. Doing so would improve the efficiency and accuracy of business operations by providing an accurate tracking. [0012].
Claim 6/22
While Durie teaches in [0011] In Example 8, a system for vehicle data management according to embodiments of the present disclosure includes an accelerometer, wherein the accelerometer is mounted in a vehicle and is configured to measure an accelerometer specific force of the vehicle, a speed sensor, wherein the speed sensor is configured to measure a speed of the vehicle, a video capture device, a vehicle data management device communicably coupled to the accelerometer, the speed sensor, and the video capture device, the vehicle data management device configured to establish a vehicle record, [0231] A VDM 10 creates a vehicle record, for example a vehicle driving safety record, based on various types of information which may include, without limitation, driver identification information, seatbelt information, vehicle backing information, force information, and speed information. [0190] the VDM 10 is configured to establish a vehicle record. The vehicle record may be a set of data stored locally in the mobile environment 101 and/or transmitted via the network 12 to other environments for later storage, use, and integration with other vehicle records. Video capture devices 26 may be internal and/or external to the vehicle 101, and can capture both events happening inside or outside the vehicle, as well as weather conditions, pedestrians, other vehicles, traffic signals, and the like. Durie does not explicitly teach the following, however analogous reference, Dargy teaches:
The method of claim 1, the set of first data further comprising at least one of positive train control event logs and network dispatch system data ([0026] With reference now to FIGS. 2 and 3, a positive train control (PTC) data-verification unit 30 is disposed in the interior of the vehicle 10. With continued reference to FIGS. 1-7, operation of the track-data verification vehicle 10 to verify positional data in a PTC track data file for an asset, such as a signal 66).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, and Zielger to incorporate the teachings of Dargy to include the set of first data further comprising at least one of positive train control event logs and network dispatch system data as part of the system of Durie. Doing so would improve the efficiency and accuracy of business operations by providing an accurate tracking. [0012].
Claims 5 and 21 are rejected under 35 U.S.C. 103 as being unpatentable over Durie in view of Fujii in view of Ziegler, as applied in claim 1 and 17, and further in view of Lawence B. Jordon (US 2017/0327138 A1, hereinafter “Jordon”).
Claim 5/21
While Durie teaches in [0011] In Example 8, a system for vehicle data management according to embodiments of the present disclosure includes an accelerometer, wherein the accelerometer is mounted in a vehicle and is configured to measure an accelerometer specific force of the vehicle, a speed sensor, wherein the speed sensor is configured to measure a speed of the vehicle, a video capture device, a vehicle data management device communicably coupled to the accelerometer, the speed sensor, and the video capture device, the vehicle data management device configured to establish a vehicle record, [0231] A VDM 10 creates a vehicle record, for example a vehicle driving safety record, based on various types of information which may include, without limitation, driver identification information, seatbelt information, vehicle backing information, force information, and speed information. [0190] the VDM 10 is configured to establish a vehicle record. The vehicle record may be a set of data stored locally in the mobile environment 101 and/or transmitted via the network 12 to other environments for later storage, use, and integration with other vehicle records. Video capture devices 26 may be internal and/or external to the vehicle 101, and can capture both events happening inside or outside the vehicle, as well as weather conditions, pedestrians, other vehicles, traffic signals, and the like. Durie does not explicitly teach the following, however analogous reference, Jordon teaches:
The method of claim 1, further comprising: storing, using an onboard data manager, at least one of the set of first data, the set of second data, and the processed data in at least one local memory component of the at least one data recorder of the data acquisition and recording system ([0004] and storing, using an onboard data manager of the data recorder, at least one of the data, the processed data, and the record at a configurable first predetermined rate in at least one local memory component of the data recorder);
sending, using the onboard data manager, at least one of the set of first data, the set of second data, and the processed data to a remote data manager remote from the mobile asset via a wireless data link at a configurable predetermined rate ([0020] The data recorder 102 is installed on the vehicle or mobile asset 164 and communicates with any number of various information sources through any combination of wired and/or wireless data links 142, such as a wireless gateway/router (not shown). Data recorder 102 gathers video data, audio data, and other data or information from a wide variety of sources, which can vary based on the asset's configuration, through onboard data links 142. The data recorder 102 comprises a local memory component, such as a crash hardened memory module 104, an onboard data manager 106, and a data encoder 108 in the asset 164. [0022] describes multiple data segments such as for example, video data from cameras 140, asset data 134 such as speed, GPS data, and inertial sensor data, weather component 136 data, and route/crew, manifest, and GIS component data 138; while claim 14 sending, using the onboard data manager, the record to a remote data manager via a wireless data link at a configurable second predetermined rate, wherein the second predetermined rate is configurable between zero seconds and five minutes );
and storing, using the remote data manager, at least one of the set of first data, the set of second data, and the processed data in a remote data repository remote from the mobile asset ([0024] information processed by the track detection and infrastructure monitoring component 114, and diagnosis and monitoring information is sent to the data encoder 108 of the data recorder 102 via onboard data links 142 to encode the data. The data recorder 102 stores the encoded data in the crash hardened memory module 104, and optionally in the optional non-crash hardened removable storage device, and sends the encoded information to a remote data manager 146 in the data center 166 via a wireless data link 144. The remote data manager 146 stores the encoded data in a remote data repository 148 in the data center 166. [0020] The data recorder 102 is installed on the vehicle or mobile asset 164 and communicates with any number of various information sources through any combination of wired and/or wireless data links 142, such as a wireless gateway/router (not shown). Data recorder 102 gathers video data, audio data, and other data or information from a wide variety of sources, which can vary based on the asset's configuration, through onboard data links 142. The data recorder 102 comprises a local memory component, such as a crash hardened memory module 104, an onboard data manager 106, and a data encoder 108 in the asset 164).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, and Zielger to incorporate the teachings of Jordon to include storing, using an onboard data manager, at least one of the set of first data, the set of second data, and the processed data in at least one local memory component of the at least one data recorder of the data acquisition and recording system, sending, using the onboard data manager, at least one of the set of first data, the set of second data, and the processed data to a remote data manager remote from the mobile asset via a wireless data link at a configurable predetermined rate, and storing, using the remote data manager, at least one of the set of first data, the set of second data, and the processed data in a remote data repository remote from the mobile asset as part of the system of Durie. Doing so would analyze the operational efficiency and safety of assets in real-time or near real-time. [0012].
Claims 7, 11, 23, and 27 are rejected under 35 U.S.C. 103 as being unpatentable over Durie in view of Fujii in view of Ziegler, as applied in claim 1 and 17, and further in view of Nicholas E. Roddy (US 2011/0208567 A9, hereinafter “Roddy”) in view of Ajith Kumar (US 2016/0009304 A1, hereinafter “Kumar”).
Claim 7/23
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Roddy teaches:
The method of claim 1, further comprising: continuously monitoring, using a back office remote from the mobile asset, at least one of the set of first data, the set of second data, and processed data for at least one of critical events and … based at least one of the set of first data related to the mobile asset, the set of second data related to the specified operator, to the specified time range, the specified operator's performance, and operational performance ([0028] the fleet of locomotives 12 or the fleet of trucks 26, the operating parameters of each of the mobile assets may be monitored 32 by the on-board sensors. Such operating parameters are monitored in real time, and data related to these operating parameters is available for communication to a data center 18 wherever appropriate. [0033] When a critical fault is identified 38, or an anomaly is found to exist 58 in one or more of the operating parameters, a service recommendation may be developed 60. Information regarding the anomaly 58, critical fault 38, and/or service recommendation 60 may also be uploaded 56 to an Internet web page. [0058] Signals transmitted by communication element 112 are received by monitoring station 114 that, for example, may be the maintenance facility 22 or data center 18 of FIG. 1. Monitoring station 114 includes appropriate hardware and software for receiving and processing vehicle system parameter data signals generated by locomotive 12 or truck 26 from a remote location).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, and Ziegler to incorporate the teachings of Roddy to include continuously monitoring, using a back office remote from the mobile asset, at least one of the set of first data, the set of second data, and processed data for at least one of critical events and … based at least one of the set of first data related to the mobile asset, the set of second data related to the specified operator, to the specified time range, the specified operator's performance, and operational performance as part of the system of Durie. Doing so would improve the efficiency of operations of the assets to remain competitive in the market place. [0003].
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, reference Kumar teaches:
and regulatory requirements ((col 9, lines 55- col 10, line 3 - The railroad infrastructure level 102 includes the... governmental regulatory requirements).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, Ziegler, and Roddy to incorporate the teachings of Kumar to include regulatory requirements as part of the system of Durie. Doing so would efficiently and accurately assess data captured for more accurate results for regulatory safety.
Claim 11/27
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Fujii teaches [0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data, Durie and Fujii do not explicitly teach the following, however analogous reference Ziegler teaches:
The method of claim 1, analyzing, […], at least one of the set of first data, the set of second data, the processed data, and the data based on specified […] requirements for one of certification and de-certification of the specified operator([0102] As another illustrative example, the checklist may ask specific questions directed to ascertain whether or not the operator can demonstrate that they are suitably trained to operate that mobile asset 12. As an example, if the mobile asset comprises a forklift truck, a checklist item may ask "What is the maximum load capacity?" Such a checklist question would require that the operator know the answer, or at least be trained to locate and read a capacity plate or other designated marking provided on the mobile asset 12. Any other questions may be asked that require the operator to demonstrate knowledge of specific characteristics of the mobile asset 12 to be operated. Thus, as the operator works with different mobile asset types, the checklist items can be used to verify that the operator knows and understands the characteristics of each mobile asset 12, or knows where to look to find the appropriate information. In this regard, an incorrect answer may or may not affect the ability of the operator to utilize the mobile asset 12. [0171] Operator rating may be based upon a number of factors, including for example the currently held operator licenses, certifications, number of years of experience, etc. Further, operator rating may be based upon actual monitored measures of operator capabilities. [0169] Referring to FIG. 12, in an exemplary implementation, "performance tuning" may be utilized as a way to rank authorized and licensed/certified operators according to experience and skill, and to adjust the operating characteristics of the mobile asset 12 accordingly. For example, operator performance ratings such as P1, P2 and P3 can be used to differentiate authorized operators, where P3 may correspond to a beginner, P2 may correspond to an intermediate skilled operator and P1 may correspond to an advanced skilled operator. [0170] As an authorized operator's performance rating is improved, the mobile asset may unlock or otherwise enable advanced features, modify features and mobile asset capabilities and/or otherwise adjust one or more operating characteristics to match the capability of the operator. Correspondingly, the mobile asset 12 may disable advanced features, limit capabilities, alter performance capabilities, etc., for relatively lower ranked/skilled operators. For example, an experienced P1 operator may be able to drive a mobile asset 12 at higher rates of speed, perform certain functions simultaneously, etc., relative to a corresponding novice P3 operator).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie and Fujii to incorporate the teachings of Zielger to include analyzing, […], at least one of the set of first data, the set of second data, the processed data, and the data based on specified […] requirements for one of certification and de-certification of the specified operator as part of the system of Durie. Doing so would improve the efficiency and accuracy of business operations. [0002].
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation,, Roddy teaches:
the analyzed data comprising at least one of operational data, performance data, and behavioral characteristics related to a predetermined geographic segment, the data related to the mobile asset, the set of first data related to the specified operator, and the set of second data related to the specified time range ([0026] The mobile assets, e.g., 12 or 26, may also be equipped with a GPS receiver 16 or other satellite-based or local navigation instrument for determining the geographic location of the mobile asset. Data regarding the location of the mobile asset and its operating parameters may be transferred periodically or in real time. [0028] the operating parameters of each of the mobile assets may be monitored 32 by the on-board sensors. In one exemplary, such operating parameters are monitored in real time, and data related to these operating parameters is available for communication to a data center 18 wherever appropriate. Data regarding both the location and the operating parameters for each mobile asset, e.g., 12 or 26, may be periodically downloaded 36 from an on-board data file to a centralized data base 39. The data may further include environmental conditions to which each mobile asset has been exposed to during their operation. Example of such data may include temperature, barometric pressure, terrain topography, humidity level, dust level, etc. [0033] Such video information may be accompanied by live audio information, including speech from the operator, thereby allowing the user 14, the operator located on the mobile asset, and personnel at a service center 22 to conference regarding a developing anomaly. [0055] At 456, the number of times each distinct fault occurred during the predetermined period of time is determined).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Fujii to incorporate the teachings of Roddy to include the analyzed data comprising at least one of operational data, performance data, and behavioral characteristics related to a predetermined geographic segment, the data related to the mobile asset, the set of first data related to the specified operator, and the set of second data related to the specified time range as part of the system of Fujii. Doing so would improve the efficiency of operations of the assets to remain competitive in the market place. [0003].
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Fujii teaches [0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data, Durie and Fujii do not explicitly teach the following, however analogous reference Kumar teaches:
analyzing at least one of the set of first data, the set of second data, and the processed data based on specified government regulatory requirements (fig. 3 and col. 10 lines 62-65 describe the infrastructure processor 200 analyzes this input data and optimizes (e.g., improves) the railroad infrastructure level 102 operation, wherein col 9, lines 55- col 10, line 3 - the railroad infrastructure level 102 includes the... governmental regulatory requirements).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, Zielger, and Roddy to incorporate the teachings of Kumar to include analyzing at least one of the set of first data, the set of second data, and the processed data based on specified government regulatory requirements as part of the system of Durie. Doing so would efficiently and accurately assess data captured for more accurate results for regulatory safety.
Claims 8, 13, 15, 24, 29, 31 are rejected under 35 U.S.C. 103 as being unpatentable over Durie in view of Fujii in view of Ziegler, as applied in the claims 1 and 17, and further in view of Nicholas E. Roddy (US 2011/0208567 A9, hereinafter “Roddy”).
Claim 8/24
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Roddy teaches:
The method of claim 1, wherein the data acquisition and recording system receives the set of first data and the set of second data via at least one of a wireless data link and a wired data link ([0058] An apparatus configured to accomplish communication actions is generally identified by numeral 110 of FIG. 5, and it comprises one or more communication elements 112 and a monitoring station 114. The communication element(s) 112 are carried by the remote vehicle, for example locomotive 12 or truck. The communication element(s) may comprise a cellular modem, a satellite transmitter or similar well-known means or methods for conveying wireless signals over long distances. Signals transmitted by communication element 112 are received by monitoring station 114 that, for example, may be the maintenance facility 22 or data center 18 of FIG. 1. Monitoring station 114 includes appropriate hardware and software for receiving and processing vehicle system parameter data signals generated by locomotive 12 or truck 26 from a remote location).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, and Zielger to incorporate the teachings of Roddy to include data acquisition and recording system receives the set of first data and the set of second data via at least one of a wireless data link and a wired data link as part of the system of Durie. Doing so would improve the efficiency of operations of the assets to remain competitive in the market place. [0003].
Claim 13/29
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Roddy teaches:
The method of claim 1, wherein displaying the processed data includes displaying at least one of critical geographic zones of operation, critical operational areas, work zones, regulatory- based alerts based on algorithms, and regulatory-based alerts based on output received from the artificial intelligence component ([0025] There is a tremendous amount of information available related to a fleet of mobile assets. Such information may include design information, real time operating data, historical performance data including failure probabilities, parts inventories, and geographic information related to the assets, cargo being transported with the assets, parts, personnel and repair facilities, etc).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, and Zielger to incorporate the teachings of Roddy to include displaying the processed data includes displaying at least one of critical geographic zones of operation, critical operational areas, work zones, regulatory- based alerts based on algorithms, and regulatory-based alerts based on output received from the artificial intelligence component as part of the system of Durie. Doing so would improve the efficiency of operations of the assets to remain competitive in the market place. [0003].
Claim 15/31
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Roddy teaches:
The method of claim 1, further comprising: generating a summarized report of the specified operator's performance; and displaying, using the web portal, the summarized report([0029] Various data processing routines may be used to generate performance reports 50 regarding each of the individual assets or the fleet as an entirety. Statistical data 52 may be calculated to aid in the analysis of the operating parameters of the fleet. [0030] In order to effectively utilize the vast amount of data that may be available regarding a fleet of mobile assets, the output of the analysis 48 of such data must be effectively displayed and conveyed to an interested user 14).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, and Zielger to incorporate the teachings of Roddy to include generating a summarized report of the specified operator's performance; and displaying, using the web portal, the summarized report as part of the system of Durie. Doing so would improve the efficiency of operations of the assets to remain competitive in the market place. [0003].
Claims 9 and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Durie in view of Fujii in view of Ziegler, as applied in claim 1 and 17, and further in view of Balaji Venkatraman (US 2015/0009331 A1, hereinafter “Venkatraman”).
Claim 9/25
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Venkatraman teaches:
The method of claim 1, further comprising: coordinating time-synchronized event recorder data and geographic position data with video of a cab of the mobile asset and video of features adjacent to a course of travel of the mobile asset([0023] The digital video cameras capture, measure and analyzes video images of railways track and adjacent structure from a running train and automatically compute degree of disaster vulnerability from collective analysis of output from all video cameras. [0193] The module communicates with other components which are part of the Train Onboard Computer System (200) and embedded video analytics layer in the Digital Video Camera System (100) using communication network synchronized in real time. [0253] The centralized system discovers and classifies deeper level of threat or vulnerability assessment using additional real-time geographic and environmental data comprising real time geographic features and real time environmental factors prevailing in a particular rail route whereby combining environmental factors as well as geographical factors to advanced analytics output that may contribute to a potential disaster and subsequently taking necessary precautionary measures to avoid such disaster).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, and Zielger to incorporate the teachings of Venkatraman to include coordinating time-synchronized event recorder data and geographic position data with video of a cab of the mobile asset and video of features adjacent to a course of travel of the mobile asset as part of the system of Durie. Doing so would provide an intelligent and effective system for predicting and preempting a disaster by making real time assessment of a potential disaster. [0011].
Claims 14 and 30 are rejected under 35 U.S.C. 103 as being unpatentable over Durie in view of Fujii in view of Ziegler, as applied in claim 1 and 17, and further in view of Michael Hawthorne (US 2001/0029411 A1, hereinafter “Hawthorne”).
Claim 14/30
Durie teaches:
displaying, using the web portal, information to user (FIG. 11 illustrates an example of a driver safety report as it may be displayed by server 128 via a remote internet interface, [0300] The enterprise application server 128 may also be configured to provide a “second-by-second report,” which may display a user-defined date and/or time period, and resolution of all monitored inputs and indicators in a graphical format, with time being the horizontal axis and the value and description of the input displayed on the vertical axis. The second-by-second report may also permit the user to directly access a video presentation of a selected portion of the second-by-second graph, for example with a mouse click and/or a hot key).
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Fujii teaches [0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data, Durie and Fujii do not explicitly teach the following, however analogous reference Hawthorne teaches:
The method of claim 1, further comprising: receiving, using the web portal, user comments related to at least one of a specific event identified in the set of second data and a period of time identified in the set of second ([0112] The engineer's response is recorded as it relates to the train's conditions, for example as a function of time and/or location of the train. The suggested response or settings are also recorded if determined or used in the onboard training or determined during a post analysis. [0122]-[0123] By supplementing the LEADER recorded data with this type of additional information, the instructor or trainer can make specific entries, which will be available during a playback session. All entries can be correlated to time and location of the train and enhance the trainer’s ability to evaluate the trainees’ skills. Further, a permanent record can be created and stored for each trainee. Analysis of the data captured by LEADER will create a more objective qualification criteria for the trainee and provide feedback as to what categories a trainee needs improvement).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, and Zielger to incorporate the teachings of Hawthorne to include receiving, using the web portal, user comments related to at least one of a specific event identified in the set of second data and a period of time identified in the set of second as part of the system of Durie. Doing so would provide and create a more objective qualification criteria for the trainee and provide feedback as to what categories a trainee needs improvement. [0122].
Claims 33, 34-37, 39, and 40 are rejected under 35 U.S.C. 103 as being unpatentable over Durie in view of Fujii in view of Ziegler.
Claim 33/37
Durie teaches:
A method for automating the assessment of safety performance skills of a specified operator of a mobile asset and certifying or de-certifying the specified operator, comprising the steps of: receiving, using a web portal, a request from a user comprising identifying information of the specified operator and the specified time range([0276] The report query screen may allow the user to select individual drivers, a group of drivers, or all drivers, and show vehicle data records or statistics for the selected driver(s). The report query may allow the user to create reports based on a specific driver or group of drivers that operated a specific vehicle or group of vehicles. The report query may allow a user to select a date and/or time range. [0277] The report query may provide for the selection of a summary of the requested data, or trends for the selected data, based on user-defined trend periods. [0278] When the user loads a user-created query, the query may automatically populate with the most recent and accurate results,),
receiving, using a data recorder of a data acquisition and recording system onboard the mobile asset, a set of first operational performance characteristics data related to the mobile asset, and a set of second data related to the specified operator and the specified time range([0011] the vehicle data management device configured to establish a vehicle record, wherein the vehicle record includes video footage captured by the video capture device. [0189] VDM's 10 functions as described herein, and which is communicably coupled to various devices and/or sensors within the vehicle 101, as well as to the network 12. [0190the VDM 10 is configured to establish a vehicle record. The vehicle record may be a set of data stored locally in the mobile environment 101 and/or transmitted via the network 12 to other environments for later storage, use, and integration with other vehicle records. [[0276] The report query screen may allow the user to select individual drivers, a group of drivers, or all drivers, and show vehicle data records or statistics for the selected driver(s). The report query may allow the user to create reports based on a specific driver or group of drivers that operated a specific vehicle or group of vehicles. The report query may allow a user to select a date and/or time range. [0277] The report query may provide for the selection of a summary of the requested data, or trends for the selected data, based on user-defined trend periods. [0278] When the user loads a user-created query, the query may automatically populate with the most recent and accurate results,) [0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range, according to embodiments of the present disclosure. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events),
the set of first data based on at least one data signal from at least one of: at least one data source onboard the mobile asset, the at least one data source onboard the mobile asset comprising at least one of at least one camera and the data recorder of the data acquisition and recording system; and at least one data source remote from the mobile asset([0011] the vehicle data management device configured to establish a vehicle record, wherein the vehicle record includes video footage captured by the video capture device. [0189] VDM's 10 functions as described herein, and which is communicably coupled to various devices and/or sensors within the vehicle 101, as well as to the network 12. [0190] the VDM 10 is configured to establish a vehicle record. The vehicle record may be a set of data stored locally in the mobile environment 101 and/or transmitted via the network 12 to other environments for later storage, use, and integration with other vehicle records. Video capture devices 26 may be internal and/or external to the vehicle 101, and can capture both events happening inside or outside the vehicle, as well as weather conditions, pedestrians, other vehicles, traffic signals, and the like).
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Fujii teaches:
processing, using an artificial intelligence component of a video analytics system, the set of first data and the set of second data into processed data([0057] the processor 110 computes the gathered data using artificial intelligence and/or machine learning module 124 based on insurance machine learning algorithms and an extensive data collection and analysis previously gathered to calculate a driving score that includes risk and safety for a particular trip. That is, the machine learning module 124 uses the on-board machine learning methods to locally (on the vehicle module) compute scores (such as a driver score, trip score, and risk score) based on the ingested vehicle sensor and video data, evaluated against extensive, previously collected datasets. Once the scores and trip summary have been completed, the vehicle module 102 established a connection with the networked servers and transmits the data allowing a user to evaluate the driver's performance against established datasets);
reviewing, using the artificial intelligence component of the video analytics system, the set of first data regarding selected events and points along a path of travel of the mobile asset([0057] the processor 110 computes the gathered data using artificial intelligence and/or machine learning module 124 based on insurance machine learning algorithms and an extensive data collection and analysis previously gathered to calculate a driving score that includes risk and safety for a particular trip. That is, the machine learning module 124 uses the on-board machine learning methods to locally (on the vehicle module) compute scores (such as a driver score, trip score, and risk score) based on the ingested vehicle sensor and video data, evaluated against extensive, previously collected datasets. Once the scores and trip summary have been completed, the vehicle module 102 established a connection with the networked servers and transmits the data allowing a user to evaluate the driver's performance against established datasets. [0093] If a risky event is detected 712, the vehicle module is triggered to record video and/or vehicle data for on-board and off-board analysis by vehicle threshold events to indicate an abnormal situation 714. According to one example, the vehicle module may use a 5-10 second window to determine the peak of the risky event. For example, if the driver suddenly brakes, the vehicle module may check the corresponding sensor data over a 10 second time frame to determine the time of the greatest deceleration. When the vehicle module determines that a risky event has occurred, a severity level between 0 and 3, (or between 0 and 4) for example, is assigned and the trip summary is updated. The trip summary may be transmitted to a remote database or server at the start and end of the trip as well as every 10 seconds as well as stored in the vehicle module on-board the vehicle (along the path of the travel of the mobile asset). All the severity levels of the risky events detected over the course of the trip are used to calculate a trip severity that can be used to assess a trip score);
and identifying, using the artificial intelligence component of the video analytics system, at least one of improper operation and unsafe operation of the mobile asset by the specified operator based on a comparison of the processed data to a rule set derived from directed to safe operation of mobile assets, the rule set part of a score system corresponding to the safe operation of the mobile asset by the specified operator(([0057] the processor 110 computes the gathered data using artificial intelligence and/or machine learning module 124 based on insurance machine learning algorithms and an extensive data collection and analysis previously gathered to calculate a driving score that includes risk and safety for a particular trip. That is, the machine learning module 124 uses the on-board machine learning methods to locally (on the vehicle module) compute scores (such as a driver score, trip score, and risk score) based on the ingested vehicle sensor and video data, evaluated against extensive, previously collected datasets. Once the scores and trip summary have been completed, the vehicle module 102 established a connection with the networked servers and transmits the data allowing a user to evaluate the driver's performance against established datasets. [0093] If a risky event is detected 712, the vehicle module is triggered to record video and/or vehicle data for on-board and off-board analysis by vehicle threshold events to indicate an abnormal situation 714. According to one example, the vehicle module may use a 5-10 second window to determine the peak of the risky event. For example, if the driver suddenly brakes, the vehicle module may check the corresponding sensor data over a 10 second time frame to determine the time of the greatest deceleration. When the vehicle module determines that a risky event has occurred, a severity level between 0 and 3, (or between 0 and 4) for example, is assigned and the trip summary is updated. The trip summary may be transmitted to a remote database or server at the start and end of the trip as well as every 10 seconds as well as stored in the vehicle module on-board the vehicle (along the path of the travel of the mobile asset). All the severity levels of the risky events detected over the course of the trip are used to calculate a trip severity that can be used to assess a trip score). Table 1 represent set of rules and score associated with each),
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range, according to embodiments of the present disclosure. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Zielger teaches:
the comparison resulting in a score recommending one of a certification and decertification of the specified operator ([0169]"performance tuning" may be utilized as a way to rank authorized and licensed/certified operators according to experience and skill, and to adjust the operating characteristics of the mobile asset 12 accordingly. For example, operator performance ratings such as P1, P2 and P3 can be used to differentiate authorized operators, where P3 may correspond to a beginner, P2 may correspond to an intermediate skilled operator and P1 may correspond to an advanced skilled operator. [0170] As an authorized operator's performance rating is improved, the mobile asset may unlock or otherwise enable advanced features, modify features and mobile asset capabilities and/or otherwise adjust one or more operating characteristics to match the capability of the operator).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie and Fujii to incorporate the teachings of Zielger to include the comparison resulting in a score for the operator, the score recommending one of certifying and decertifying the operator as part of the system of Durie. Doing so would improve the efficiency and accuracy of business operations. [0002].
Claim 35/39
Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range, according to embodiments of the present disclosure. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Ziegler teaches:
The method of claim 33, further comprising: recommending, […] analytics system, one of certifying and de-certifying the specified operator based on said identification([0169] Referring to FIG. 12, in an exemplary implementation, "performance tuning" may be utilized as a way to rank authorized and licensed/certified operators according to experience and skill, and to adjust the operating characteristics of the mobile asset 12 accordingly. For example, operator performance ratings such as P1, P2 and P3 can be used to differentiate authorized operators, where P3 may correspond to a beginner, P2 may correspond to an intermediate skilled operator and P1 may correspond to an advanced skilled operator. [0170] As an authorized operator's performance rating is improved, the mobile asset may unlock or otherwise enable advanced features, modify features and mobile asset capabilities and/or otherwise adjust one or more operating characteristics to match the capability of the operator. Correspondingly, the mobile asset 12 may disable advanced features, limit capabilities, alter performance capabilities, etc., for relatively lower ranked/skilled operators. For example, an experienced P1 operator may be able to drive a mobile asset 12 at higher rates of speed, perform certain functions simultaneously, etc., relative to a corresponding novice P3 operator).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie and Fujii to incorporate the teachings of Zielger to include the comparison resulting in a score for the operator, the score recommending one of certifying and decertifying the operator as part of the system of Durie. Doing so would improve the efficiency and accuracy of business operations. [0002].
Claim 36/40
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range, according to embodiments of the present disclosure. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Ziegler teaches:
The method of claim 33, further comprising one of: certifying, using the artificial intelligence component of the video analytics system, the specified operator based on said identification; and de-certifying, using the artificial intelligence component of the video analytics system, the specified operator based on said identification(0169] Referring to FIG. 12, in an exemplary implementation, "performance tuning" may be utilized as a way to rank authorized and licensed/certified operators according to experience and skill, and to adjust the operating characteristics of the mobile asset 12 accordingly. For example, operator performance ratings such as P1, P2 and P3 can be used to differentiate authorized operators, where P3 may correspond to a beginner, P2 may correspond to an intermediate skilled operator and P1 may correspond to an advanced skilled operator. [0170] As an authorized operator's performance rating is improved, the mobile asset may unlock or otherwise enable advanced features, modify features and mobile asset capabilities and/or otherwise adjust one or more operating characteristics to match the capability of the operator. Correspondingly, the mobile asset 12 may disable advanced features, limit capabilities, alter performance capabilities, etc., for relatively lower ranked/skilled operators. For example, an experienced P1 operator may be able to drive a mobile asset 12 at higher rates of speed, perform certain functions simultaneously, etc., relative to a corresponding novice P3 operator [0171] Operator rating may be based upon a number of factors, including for example the currently held operator licenses, certifications, number of years of experience, etc. Further, operator rating may be based upon actual monitored measures of operator capabilities. As noted above, the mobile asset information linking device 38 may be capable of monitoring and logging aspects of mobile asset operation, and to wirelessly transmit that information to the network, for example, to the mobile asset application server 14. As such, the metrics used to evaluate and determine operator skill may be based upon actual event and other data collected by a corresponding mobile asset information linking device 38).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie and Fujii to incorporate the teachings of Zielger to include one of: certifying, using the artificial intelligence component of the video analytics system, the specified operator based on said identification; and de-certifying, using the artificial intelligence component of the video analytics system, the specified operator based on said identification. Doing so would improve the efficiency and accuracy of business operations. [0002].
Claims 34 and 38 are rejected under 35 U.S.C. 103 as being unpatentable over Durie in view of Fujii in view of Ziegler, as applied in claims 33 and 37, and further in view of Roddy in view of Kumar.
Claim 34/38
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range, according to embodiments of the present disclosure. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Ziegler teaches:
The method of claim 33, further comprising: analyzing, […], at least one of the data, the processed data, the set of first data, the set of second data based and regulations on specified […] requirements for one of certification and de-certification of the specified operator([0102] As another illustrative example, the checklist may ask specific questions directed to ascertain whether or not the operator can demonstrate that they are suitably trained to operate that mobile asset 12. As an example, if the mobile asset comprises a forklift truck, a checklist item may ask "What is the maximum load capacity?" Such a checklist question would require that the operator know the answer, or at least be trained to locate and read a capacity plate or other designated marking provided on the mobile asset 12. Any other questions may be asked that require the operator to demonstrate knowledge of specific characteristics of the mobile asset 12 to be operated. Thus, as the operator works with different mobile asset types, the checklist items can be used to verify that the operator knows and understands the characteristics of each mobile asset 12, or knows where to look to find the appropriate information. In this regard, an incorrect answer may or may not affect the ability of the operator to utilize the mobile asset 12. [0171] Operator rating may be based upon a number of factors, including for example the currently held operator licenses, certifications, number of years of experience, etc. Further, operator rating may be based upon actual monitored measures of operator capabilities. [0169] Referring to FIG. 12, in an exemplary implementation, "performance tuning" may be utilized as a way to rank authorized and licensed/certified operators according to experience and skill, and to adjust the operating characteristics of the mobile asset 12 accordingly. For example, operator performance ratings such as P1, P2 and P3 can be used to differentiate authorized operators, where P3 may correspond to a beginner, P2 may correspond to an intermediate skilled operator and P1 may correspond to an advanced skilled operator. [0170] As an authorized operator's performance rating is improved, the mobile asset may unlock or otherwise enable advanced features, modify features and mobile asset capabilities and/or otherwise adjust one or more operating characteristics to match the capability of the operator. Correspondingly, the mobile asset 12 may disable advanced features, limit capabilities, alter performance capabilities, etc., for relatively lower ranked/skilled operators. For example, an experienced P1 operator may be able to drive a mobile asset 12 at higher rates of speed, perform certain functions simultaneously, etc., relative to a corresponding novice P3 operator).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie and Fujii to incorporate the teachings of Zielger to include analyzing at least one of the data, the processed data, the set of first data, the set of second data-based regulations on specified requirements for one of certification and de-certification of the specified operator as part of the system of Durie. Doing so would improve the efficiency and accuracy of business operations. [0002].
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range, according to embodiments of the present disclosure. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Durie does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Roddy teaches:
the analyzed data comprising at least one of mobile asset operational data, the specified operator performance data, and the specified operator behavioral characteristics related to a predetermined geographic segment, the data related to the mobile asset ([0026] The mobile assets, e.g., 12 or 26, may also be equipped with a GPS receiver 16 or other satellite-based or local navigation instrument for determining the geographic location of the mobile asset. Data regarding the location of the mobile asset and its operating parameters may be transferred periodically or in real time. [0028] the operating parameters of each of the mobile assets may be monitored 32 by the on-board sensors. In one exemplary, such operating parameters are monitored in real time, and data related to these operating parameters is available for communication to a data center 18 wherever appropriate. Data regarding both the location and the operating parameters for each mobile asset, e.g., 12 or 26, may be periodically downloaded 36 from an on-board data file to a centralized data base 39. The data may further include environmental conditions to which each mobile asset has been exposed to during their operation. Example of such data may include temperature, barometric pressure, terrain topography, humidity level, dust level, etc. [0033] Such video information may be accompanied by live audio information, including speech from the operator, thereby allowing the user 14, the operator located on the mobile asset, and personnel at a service center 22 to conference regarding a developing anomaly. [0055] At 456, the number of times each distinct fault occurred during the predetermined period of time is determined).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fuiji, and Ziegler to incorporate the teachings of Roddy to include the analyzed data comprising at least one of mobile asset operational data, the specified operator performance data, and the specified operator behavioral characteristics related to a predetermined geographic segment, the data related to the mobile asset as part of the system of Durie. Doing so would improve the efficiency of operations of the assets to remain competitive in the market place. [0003].
While Durie teaches in 0276] The report query may allow a user to select a date and/or time range. The default time range in the report query interface may be by twenty-four-hour increments (e.g. the set of first data), but the time range may also be editable to select a more precise range, according to embodiments of the present disclosure. The report query may also permit a user to filter information displayed in the report based on a minimum distance traveled (for example in tenths of a mile or kilometer) and/or time duration (in seconds) for specific events. [0066] the vehicle data management device configured to query a remote server based on the identity of the current crew member, receive a crew member performance score from a remote server based on the query, and activate the user experience system if the crew member performance score exceeds a predefined level. [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. Roddy teaches [0028] the operating parameters of each of the mobile assets may be monitored 32 by the on-board sensors. [0033] When a critical fault is identified 38, or an anomaly is found to exist 58 in one or more of the operating parameters, a service recommendation may be developed 60. Information regarding the anomaly 58, critical fault 38, and/or service recommendation 60 may also be uploaded 56 to an Internet web page. [0058] Signals transmitted by communication element 112 are received by monitoring station 114 that, for example, may be the maintenance facility 22 or data center 18 of FIG. 1, Durie and Roddy do not explicitly teach the following, however analogous reference Kumar teaches:
analyzing at least one of the data and the processed data based on specified government regulatory requirements (fig. 3 and col. 10 lines 62-65 describe the infrastructure processor 200 analyzes this input data and optimizes (e.g., improves) the railroad infrastructure level 102 operation, wherein col 9, lines 55- col 10, line 3 - the railroad infrastructure level 102 includes the... governmental regulatory requirements).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Durie, Fujii, Ziegler, and Roddy to incorporate the teachings of Kumar to include analyzing at least one of the data and the processed data based on specified government regulatory requirements as part of the system of Durie. Doing so would efficiently and accurately assess data captured for more accurate results for regulatory safety.
Claims 41 and 42 rejected under 35 U.S.C. 103 as being unpatentable over Fujii in view of Durie in view of Hawthorne.
Claim 41
Fujii teaches:
A method for automating the assessment of safety performance skills of a specified operator of a mobile asset comprising the steps of: processing, using an artificial intelligence component of a video analytics system, at least a set of first data and a set of second data into processed data, [0048] The vehicle module 104 gathers driver data using the various sensors 114 provided in the vehicle (e.g., speed sensors, accelerometers, GPS locators, tire pressure sensors, self-driving sensors, and Audio/Visual sensors, such as backup cameras, and anti-theft theft devices) that are typically connected to the ECU via a Controller Area Network (CAN) bus for example. From the vehicle sensor data and/or video meta data gathered, the processor 110 computes the gathered data into scores using an artificial intelligence and/or machine learning module 124 based on insurance machine learning algorithms and an extensive data collection and analysis previously gathered to calculate a driving score that includes risk and safety for a particular trip. 0059] According to one example, the system may retain up to 60 seconds of video data at a time using the GPU. When the system detects a risky event, the GPU may save 10 seconds of video before and after the risky event on the on-board storage of the vehicle module. The data may be retained to enable the system to rebuild the video clips and telemetry data around an event as it occurs, and it is observed. The system may update the remote data storage or server with trip data at regular intervals. Regular intervals may include, but are not limited to, the start of a trip, the end of a trip and every 10 second of the trip. [0059] the system may update the remote data storage or server with trip data at regular intervals. [0008] The acts may further include notifying at least one user of the at least one score via the user interface; triggering recording of video data using a camera on-board the vehicle; and analyzing the recorded video data using vehicle threshold events to identify the at least one risky event).
While Fujii teaches in [0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data [0092] FIG. 7 is a flow diagram illustrating an exemplary method 700 for calculating a driver score of a driver of a vehicle. As defined above, the driver may be a person or the vehicle itself if the self-driving feature is engaged. [0093]-[0097] For example, if the driver suddenly brakes, the vehicle module may check the corresponding sensor data over a 10 second time frame to determine the time of the greatest deceleration. When the vehicle module determines that a risky event has occurred, a severity level between 0 and 3, (or between 0 and 4) for example, is assigned and the trip summary is updated. The system may automatically assume a trip severity of 4 for every minute of the trip where the trip score is a number from 0-100, after taking into consideration the trip's configured typical severity (or predetermined severity or threshold) and the actual severity per minute. Table 1 further illustrates scores associated with safe operation of vehicle. Fujii does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Durie teaches:
the set of first data gathered from the mobile asset and the set of second data gathered from a source remote from the mobile asset([0011] system for vehicle data management according to embodiments of the present disclosure includes an accelerometer, wherein the accelerometer is mounted in a vehicle and is configured to measure an accelerometer specific force of the vehicle, a speed sensor, wherein the speed sensor is configured to measure a speed of the vehicle, a video capture device, a vehicle data management device communicably coupled to the accelerometer, the speed sensor, and the video capture device, the vehicle data management device configured to establish a vehicle record, [0296] The enterprise application server 128 may also be configured to provide a “vehicle utilization report,” which may include distance, total time, park time, run time, move time, and/or idle time, [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. [0315] the VDM 10 may infer that it is raining, snowing, hailing, flooding, or that other adverse weather conditions are present, based on location information received from the navigation system 30 regarding the current vehicle 101 location, in combination with reports of weather conditions at different geographical locations obtained via, for example, network 12. the VDM 10 can access weather service feeds, such as APIs associated with national weather services, to determine local weather conditions at the current vehicle 101's location, as determined by navigation system 30)
analyzing, using the video analytics system, the processed data in a score system of the video analytics system, the score system comprising a set of rules directed to safe operation of the mobile asset([0004] determining an instantaneous acceleration of the vehicle by calculating a rate of change of the speed based on the speed signal, selecting a current observed acceleration as a lower value of the accelerometer specific force and the instantaneous acceleration, capturing video footage with a camera mounted on the vehicle, and flagging the video footage corresponding to a time when the current observed acceleration exceeds a preset safe force value. [0008] In Example 5, the method of any of Examples 1-4, further including flagging the video footage corresponding to a time when the speed exceeds a preset safe speed value. [0297] The enterprise application server 128 may also be configured to provide a “safety report,” which may display distance, low overforce, high overforce, low overspeed, high overspeed, seatbelt violations, and/or backing incidents according to driver and/or vehicle. A grade level may be assigned to each vehicle or driver. The level assigned to each vehicle or driver may include determining the level according to the following calculations. The miles driven may be divided by a number of counts to arrive at the score. Each second in an overforce or overspeed condition may equal one count, and each second in a high overforce or high overspeed condition may equal a user-defined number of counts. Each unsafe backing occurrence may equal a user defined number of counts. ), each rule or a combination of the rules of the set of rules selected from the group consisting of the mobile asset operator performance of a class III brake test, the mobile asset operator efficiently starts movement of the mobile asset, the mobile asset operator strips a throttle of the mobile asset, the mobile asset operator failed to wait 10 seconds before transition to dynamic brakes, the mobile asset operator independently set up and used a brake properly of the mobile asset, the mobile asset operator performed proper running release, the mobile asset operator performed a proper combination braking procedure, the mobile asset operator made proper use of the at least one of a horn, bell, headlights, and telemetry of the mobile asset, the mobile asset operator did not fail to initialize a trip optimizer of the mobile asset during a trip, a positive train control (PTC) of the mobile asset was properly initialized and monitored by the mobile asset operator, and the DP was properly set up and brake tested by the mobile asset operator([0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. [0297] The enterprise application server 128 may also be configured to provide a “safety report,” which may display distance, low overforce, high overforce, low overspeed, high overspeed, seatbelt violations, and/or backing incidents according to driver and/or vehicle. A grade level may be assigned to each vehicle or driver. The level assigned to each vehicle or driver may include determining the level according to the following calculations. The miles driven may be divided by a number of counts to arrive at the score. Each second in an overforce or overspeed condition may equal one count, and each second in a high overforce or high overspeed condition may equal a user-defined number of counts. Each unsafe backing occurrence may equal a user defined number of counts);
the analyzing step establishing a score of the processed data, a score attached to each selected rule ([0297] The enterprise application server 128 may also be configured to provide a “safety report,” which may display distance, low overforce, high overforce, low overspeed, high overspeed, seatbelt violations, and/or backing incidents according to driver and/or vehicle. A grade level may be assigned to each vehicle or driver. The level assigned to each vehicle or driver may include determining the level according to the following calculations. The miles driven may be divided by a number of counts to arrive at the score. Each second in an overforce or overspeed condition may equal one count, and each second in a high overforce or high overspeed condition may equal a user-defined number of counts. Each unsafe backing occurrence may equal a user defined number of counts);
displaying, using a display device of the web portal, at least one of the processed data and the score( [0297] FIG. 11 illustrates an example of a driver safety report as it may be displayed by server 128 via a remote internet interface).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Fujii to incorporate the teachings of Durie to include the set of first data gathered from the mobile asset and the set of second data gathered from a source remote from the mobile asset, analyzing, using the video analytics system, the processed data in a score system of the video analytics system, the score system comprising a set of rules directed to safe operation of the mobile asset, each rule or a combination of the rules of the set of rules selected from the group consisting of the mobile asset operator performance of a class III brake test, the mobile asset operator efficiently starts movement of the mobile asset, the mobile asset operator strips a throttle of the mobile asset, the mobile asset operator failed to wait 10 seconds before transition to dynamic brakes, the mobile asset operator independently set up and used a brake properly of the mobile asset, the mobile asset operator performed proper running release, the mobile asset operator performed a proper combination braking procedure, the mobile asset operator made proper use of the at least one of a horn, bell, headlights, and telemetry of the mobile asset, the mobile asset operator did not fail to initialize a trip optimizer of the mobile asset during a trip, a positive train control (PTC) of the mobile asset was properly initialized and monitored by the mobile asset operator, and the DP was properly set up and brake tested by the mobile asset operator, and displaying, using a display device of the web portal, at least one of the processed data and the score as part of the system of Fujii. Doing so would provide an accurate score for operator performance which will help maintain safety.
While Fujii teaches in [0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data [0092] FIG. 7 is a flow diagram illustrating an exemplary method 700 for calculating a driver score of a driver of a vehicle. As defined above, the driver may be a person or the vehicle itself if the self-driving feature is engaged. [0093]-[0097] For example, if the driver suddenly brakes, the vehicle module may check the corresponding sensor data over a 10 second time frame to determine the time of the greatest deceleration. When the vehicle module determines that a risky event has occurred, a severity level between 0 and 3, (or between 0 and 4) for example, is assigned and the trip summary is updated. The system may automatically assume a trip severity of 4 for every minute of the trip where the trip score is a number from 0-100, after taking into consideration the trip's configured typical severity (or predetermined severity or threshold) and the actual severity per minute. Table 1 further illustrates scores associated with safe operation of vehicle. Fujii does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Hawthorne teaches:
the score corresponding to one of a certification and decertification of the mobile asset operator ([0127] A determination is then made whether the user, through his I.D. or through his qualification level is approved for the particular equipment or locomotive. If the engineer is not, the system is disabled. [[0128] The encoded device which includes the user's I.D. and their qualification may also be used with the trainer of FIG. 14. This training session would determine, from the user I.D., their level prior to the training session. Depending upon the results and the qualification, this user's level would be updated. Thus, the encoded device would always carry the latest qualification level of the user).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Fujii and Durie to incorporate the teachings of Hawthorne to include displaying, using a display device of the web portal, at least one of the processed data and the score, the score corresponding to one of a certification and decertification of the mobile asset operator as part of the system of Fujii. Doing so would improve the efficiency of operations of the assets to remain competitive in the market place. [0003].
Claim 42
Fujii teaches:
A method to automate the determination of whether a specified operator of a mobile asset has the skills to safely operate the mobile asset comprising the steps of: processing, using an artificial intelligence component of a video analytics system, at least a set of first data and a set of second data into processed data, ([0048] The vehicle module 104 gathers driver data using the various sensors 114 provided in the vehicle (e.g., speed sensors, accelerometers, GPS locators, tire pressure sensors, self-driving sensors, and Audio/Visual sensors, such as backup cameras, and anti-theft theft devices) that are typically connected to the ECU via a Controller Area Network (CAN) bus for example. From the vehicle sensor data and/or video meta data gathered, the processor 110 computes the gathered data into scores using an artificial intelligence and/or machine learning module 124 based on insurance machine learning algorithms and an extensive data collection and analysis previously gathered to calculate a driving score that includes risk and safety for a particular trip. 0059] According to one example, the system may retain up to 60 seconds of video data at a time using the GPU. When the system detects a risky event, the GPU may save 10 seconds of video before and after the risky event on the on-board storage of the vehicle module. The data may be retained to enable the system to rebuild the video clips and telemetry data around an event as it occurs, and it is observed. The system may update the remote data storage or server with trip data at regular intervals. Regular intervals may include, but are not limited to, the start of a trip, the end of a trip and every 10 second of the trip. [0059] the system may update the remote data storage or server with trip data at regular intervals. [0008] The acts may further include notifying at least one user of the at least one score via the user interface; triggering recording of video data using a camera on-board the vehicle; and analyzing the recorded video data using vehicle threshold events to identify the at least one risky event);
or a combination of the rules of the set of rules selected from the group consisting of the operator following proper operating practices, the operator following proper equipment inspection practices, the operator following proper train handling practices, the operator complying with federal safety rules, and the operator operating the mobile asset for a sufficient length of time([0093]-[0095] identifies proper operating practices, wherein an anomaly is detected when the operator/driver does not comply with safety rules i.e., suddenly breaking or tailgating );
the operator being at a set of controls, the set of controls being typical of controls used on the mobile asset operated on at least one of a specified railroad and a segment of the specified railroad (see examiner notes set forth above).
While Fujii teaches in [0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data [0092] FIG. 7 is a flow diagram illustrating an exemplary method 700 for calculating a driver score of a driver of a vehicle. As defined above, the driver may be a person or the vehicle itself if the self-driving feature is engaged. [0093]-[0097] For example, if the driver suddenly brakes, the vehicle module may check the corresponding sensor data over a 10 second time frame to determine the time of the greatest deceleration. When the vehicle module determines that a risky event has occurred, a severity level between 0 and 3, (or between 0 and 4) for example, is assigned and the trip summary is updated. The system may automatically assume a trip severity of 4 for every minute of the trip where the trip score is a number from 0-100, after taking into consideration the trip's configured typical severity (or predetermined severity or threshold) and the actual severity per minute. Table 1 further illustrates scores associated with safe operation of vehicle. Fujii does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Durie teaches:
the set of first data related to the operational performance characteristics of the mobile asset, the set of first data gathered from the mobile asset and the set of second data gathered from a source remote from the mobile asset ([0011] system for vehicle data management according to embodiments of the present disclosure includes an accelerometer, wherein the accelerometer is mounted in a vehicle and is configured to measure an accelerometer specific force of the vehicle, a speed sensor, wherein the speed sensor is configured to measure a speed of the vehicle, a video capture device, a vehicle data management device communicably coupled to the accelerometer, the speed sensor, and the video capture device, the vehicle data management device configured to establish a vehicle record, [0296] The enterprise application server 128 may also be configured to provide a “vehicle utilization report,” which may include distance, total time, park time, run time, move time, and/or idle time, [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. [0315] the VDM 10 may infer that it is raining, snowing, hailing, flooding, or that other adverse weather conditions are present, based on location information received from the navigation system 30 regarding the current vehicle 101 location, in combination with reports of weather conditions at different geographical locations obtained via, for example, network 12. the VDM 10 can access weather service feeds, such as APIs associated with national weather services, to determine local weather conditions at the current vehicle 101's location, as determined by navigation system 30);
analyzing, using the video analytics system, the processed data in a score system of the video analytics system, the score system comprising a set of rules directed to safe operation of the mobile asset, each rule ([0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. [0297] The enterprise application server 128 may also be configured to provide a “safety report,” which may display distance, low overforce, high overforce, low overspeed, high overspeed, seatbelt violations, and/or backing incidents according to driver and/or vehicle. A grade level may be assigned to each vehicle or driver. The level assigned to each vehicle or driver may include determining the level according to the following calculations. The miles driven may be divided by a number of counts to arrive at the score. Each second in an overforce or overspeed condition may equal one count, and each second in a high overforce or high overspeed condition may equal a user-defined number of counts. Each unsafe backing occurrence may equal a user defined number of counts);
the analyzing step establishing a score of the processed data, a score attached to each selected rule ([0297] The enterprise application server 128 may also be configured to provide a “safety report,” which may display distance, low overforce, high overforce, low overspeed, high overspeed, seatbelt violations, and/or backing incidents according to driver and/or vehicle. A grade level may be assigned to each vehicle or driver. The level assigned to each vehicle or driver may include determining the level according to the following calculations. The miles driven may be divided by a number of counts to arrive at the score. Each second in an overforce or overspeed condition may equal one count, and each second in a high overforce or high overspeed condition may equal a user-defined number of counts. Each unsafe backing occurrence may equal a user defined number of counts);
displaying, using a display device of the web portal, at least one of the processed data and the score( [0297] FIG. 11 illustrates an example of a driver safety report as it may be displayed by server 128 via a remote internet interface).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Fujii to incorporate the teachings of Durie to include the set of first data related to the operational performance characteristics of the mobile asset, the set of first data gathered from the mobile asset and the set of second data gathered from a source remote from the mobile asset, analyzing, using the video analytics system, the processed data in a score system of the video analytics system, the score system comprising a set of rules directed to safe operation of the mobile asset, each rule, the analyzing step establishing a score of the processed data, a score attached to each selected rule, and displaying, using a display device of the web portal, at least one of the processed data and the score as part of the system of Fujii. Doing so would provide an accurate score for operator performance which will help maintain safety.
While Fujii teaches in [0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data [0092] FIG. 7 is a flow diagram illustrating an exemplary method 700 for calculating a driver score of a driver of a vehicle. As defined above, the driver may be a person or the vehicle itself if the self-driving feature is engaged. [0093]-[0097] For example, if the driver suddenly brakes, the vehicle module may check the corresponding sensor data over a 10 second time frame to determine the time of the greatest deceleration. When the vehicle module determines that a risky event has occurred, a severity level between 0 and 3, (or between 0 and 4) for example, is assigned and the trip summary is updated. The system may automatically assume a trip severity of 4 for every minute of the trip where the trip score is a number from 0-100, after taking into consideration the trip's configured typical severity (or predetermined severity or threshold) and the actual severity per minute. Table 1 further illustrates scores associated with safe operation of vehicle. Fujii does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Hawthorne teaches:
the score corresponding to one of a certification and decertification of the mobile asset operator ([0127] A determination is then made whether the user, through his I.D. or through his qualification level is approved for the particular equipment or locomotive. If the engineer is not, the system is disabled. [[0128] The encoded device which includes the user's I.D. and their qualification may also be used with the trainer of FIG. 14. This training session would determine, from the user I.D., their level prior to the training session. Depending upon the results and the qualification, this user's level would be updated. Thus, the encoded device would always carry the latest qualification level of the user).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Fujii and Durie to incorporate the teachings of Hawthorne to include displaying, using a display device of the web portal, at least one of the processed data and the score, the score corresponding to one of a certification and decertification of the mobile asset operator as part of the system of Fujii. Doing so would improve the efficiency of operations of the assets to remain competitive in the market place. [0003].
Claim 43 is rejected under 35 U.S.C. 103 as being unpatentable over Fujii in view of Durie in view of Ziegler.
Claim 43
Fujii teaches:
A method to automate the determination of whether a specified operator of a mobile asset has the skills to safely operate the mobile asset comprising the steps of: processing, using an artificial intelligence component of a video analytics system, at least a set of first data and a set of second data into processed data, the set of first data gathered from the mobile asset and the set of second data gathered from a source remote from the mobile asset([0048] The vehicle module 104 gathers driver data using the various sensors 114 provided in the vehicle (e.g., speed sensors, accelerometers, GPS locators, tire pressure sensors, self-driving sensors, and Audio/Visual sensors, such as backup cameras, and anti-theft theft devices) that are typically connected to the ECU via a Controller Area Network (CAN) bus for example. From the vehicle sensor data and/or video meta data gathered, the processor 110 computes the gathered data into scores using an artificial intelligence and/or machine learning module 124 based on insurance machine learning algorithms and an extensive data collection and analysis previously gathered to calculate a driving score that includes risk and safety for a particular trip. 0059] According to one example, the system may retain up to 60 seconds of video data at a time using the GPU. When the system detects a risky event, the GPU may save 10 seconds of video before and after the risky event on the on-board storage of the vehicle module. The data may be retained to enable the system to rebuild the video clips and telemetry data around an event as it occurs, and it is observed. The system may update the remote data storage or server with trip data at regular intervals. Regular intervals may include, but are not limited to, the start of a trip, the end of a trip and every 10 second of the trip. [0059] the system may update the remote data storage or server with trip data at regular intervals. [0008] The acts may further include notifying at least one user of the at least one score via the user interface; triggering recording of video data using a camera on-board the vehicle; and analyzing the recorded video data using vehicle threshold events to identify the at least one risky event);
analyzing, using the artificial intelligence of the video analytics system, the artificial intelligence trained to review the processed data, the processed data comprising at least one of an event occurring at a point along the mobile asset's path, to determine improper and unsafe mobile asset handling and violations of operating rules, the determination resulting in an evaluation score of the operator([0057] the processor 110 computes the gathered data using artificial intelligence and/or machine learning module 124 based on insurance machine learning algorithms and an extensive data collection and analysis previously gathered to calculate a driving score that includes risk and safety for a particular trip. That is, the machine learning module 124 uses the on-board machine learning methods to locally (on the vehicle module) compute scores (such as a driver score, trip score, and risk score) based on the ingested vehicle sensor and video data, evaluated against extensive, previously collected datasets. Once the scores and trip summary have been completed, the vehicle module 102 established a connection with the networked servers and transmits [0093] If a risky event is detected 712, the vehicle module is triggered to record video and/or vehicle data for on-board and off-board analysis by vehicle threshold events to indicate an abnormal situation 714. According to one example, the vehicle module may use a 5-10 second window to determine the peak of the risky event. For example, if the driver suddenly brakes, the vehicle module may check the corresponding sensor data over a 10 second time frame to determine the time of the greatest deceleration. When the vehicle module determines that a risky event has occurred, a severity level between 0 and 3, (or between 0 and 4) for example, is assigned and the trip summary is updated),
the operator being at a set of controls, the set of controls being typical of controls used on the mobile asset operated on at least one of a specified railroad and a segment of the specified railroad (see examiner notes set forth above).
While Fujii teaches in [0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data [0092] FIG. 7 is a flow diagram illustrating an exemplary method 700 for calculating a driver score of a driver of a vehicle. As defined above, the driver may be a person or the vehicle itself if the self-driving feature is engaged. [0093]-[0097] For example, if the driver suddenly brakes, the vehicle module may check the corresponding sensor data over a 10 second time frame to determine the time of the greatest deceleration. When the vehicle module determines that a risky event has occurred, a severity level between 0 and 3, (or between 0 and 4) for example, is assigned and the trip summary is updated. The system may automatically assume a trip severity of 4 for every minute of the trip where the trip score is a number from 0-100, after taking into consideration the trip's configured typical severity (or predetermined severity or threshold) and the actual severity per minute. Table 1 further illustrates scores associated with safe operation of vehicle. Fujii does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Durie teaches:
the set of first data related to the operational performance characteristics of the mobile asset, the set of first data gathered from the mobile asset and the set of second data gathered from a source remote from the mobile asset ([0011] system for vehicle data management according to embodiments of the present disclosure includes an accelerometer, wherein the accelerometer is mounted in a vehicle and is configured to measure an accelerometer specific force of the vehicle, a speed sensor, wherein the speed sensor is configured to measure a speed of the vehicle, a video capture device, a vehicle data management device communicably coupled to the accelerometer, the speed sensor, and the video capture device, the vehicle data management device configured to establish a vehicle record, [0296] The enterprise application server 128 may also be configured to provide a “vehicle utilization report,” which may include distance, total time, park time, run time, move time, and/or idle time, [0299] The enterprise application server 128 may also be configured to provide a “grading report,” which may permit the user to specify specific occurrences and events, and the data values attributed to such occurrences and events. For example, the user may wish to create a “green report” that grades driver performance as it relates to speed, forces, throttle position, oxygen sensor values, and idle time, which are all factors which tend to have a higher degree of relevance to the environment. [0315] the VDM 10 may infer that it is raining, snowing, hailing, flooding, or that other adverse weather conditions are present, based on location information received from the navigation system 30 regarding the current vehicle 101 location, in combination with reports of weather conditions at different geographical locations obtained via, for example, network 12. the VDM 10 can access weather service feeds, such as APIs associated with national weather services, to determine local weather conditions at the current vehicle 101's location, as determined by navigation system 30);
displaying, using a display device of the web portal, at least one of the processed data and the evaluation score( [0297] FIG. 11 illustrates an example of a driver safety report as it may be displayed by server 128 via a remote internet interface).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Fujii to incorporate the teachings of Durie to include the set of first data related to the operational performance characteristics of the mobile asset, the set of first data gathered from the mobile asset and the set of second data gathered from a source remote from the mobile asset, analyzing, using the video analytics system, the processed data in a score system of the video analytics system, the score system comprising a set of rules directed to safe operation of the mobile asset, each rule, the analyzing step establishing a score of the processed data, a score attached to each selected rule, and displaying, using a display device of the web portal, at least one of the processed data and the score as part of the system of Fujii. Doing so would provide an accurate score for operator performance which will help maintain safety.
While Fujii teaches in [0095] Based on all the data gathered from the trip, the system computes a trip-based driver scoring for a cumulative overall driver score 716. Next, the system computes the collected vehicle sensor and/or video meta data using artificial intelligence and/or machine learning based on data collection and analysis to develop driving scores including scores for risk and safety 718. If no more risky events are detected and it is determined that the trip has ended 720, the system stops collecting data [0092] FIG. 7 is a flow diagram illustrating an exemplary method 700 for calculating a driver score of a driver of a vehicle. As defined above, the driver may be a person or the vehicle itself if the self-driving feature is engaged. [0093]- [0097] For example, if the driver suddenly brakes, the vehicle module may check the corresponding sensor data over a 10 second time frame to determine the time of the greatest deceleration. When the vehicle module determines that a risky event has occurred, a severity level between 0 and 3, (or between 0 and 4) for example, is assigned and the trip summary is updated. The system may automatically assume a trip severity of 4 for every minute of the trip where the trip score is a number from 0-100, after taking into consideration the trip's configured typical severity (or predetermined severity or threshold) and the actual severity per minute. Table 1 further illustrates scores associated with safe operation of vehicle. Fujii does not explicitly teach the following, however, analogues reference in the field of performance evaluation, Zielger teaches:
the evaluation score recommending one of a certification and a decertification of the mobile asset operator, the evaluation score derived from mobile asset operating rules ([0169]"performance tuning" may be utilized as a way to rank authorized and licensed/certified operators according to experience and skill, and to adjust the operating characteristics of the mobile asset 12 accordingly. For example, operator performance ratings such as P1, P2 and P3 can be used to differentiate authorized operators, where P3 may correspond to a beginner, P2 may correspond to an intermediate skilled operator and P1 may correspond to an advanced skilled operator. [0170] As an authorized operator's performance rating is improved, the mobile asset may unlock or otherwise enable advanced features, modify features and mobile asset capabilities and/or otherwise adjust one or more operating characteristics to match the capability of the operator).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the teaching of Fujii and Durie to incorporate the teachings of Zielger to include the evaluation score recommending one of a certification and a decertification of the mobile asset operator, the evaluation score derived from mobile asset operating rules as part of the system of Fujii. Doing so would improve the efficiency and accuracy of business operations. [0002].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Scott M. Branka (US 20150225002 A1): system includes: an unmanned self-propelled vehicle, a sensor, a position system and a control system. The unmanned self-propelled vehicle is adapted to travel on a railway track ahead of the train and has a sensor configured to detect an adverse railway condition. The positioning system is configured to determine the position of the self-propelled vehicle. The control system in communication with the sensor and the train; wherein the control system communicates the adverse railway condition to the train.
Michael Bar-Am(US 8942426 B2): system is provided for monitoring rail track for detecting and generating alerts for certain hazards to the operation of trains that may cause various safety concerns and even derailment. The monitoring is during normal railway service runs without interrupting the normal railway services. In one implementation, an imaging module is used on a passenger or freight train to capture video images of the rail track under the train in motion. In one implementation, the captured video images are automatically processed in a computer using a software module which is based on digital image processing techniques and algorithms to determine whether an irregularity is present on the rail track. In one implementation, video images containing detected irregularities on the rail track are transmitted to a control center for further analysis and possible alert.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to REHAM K ABOUZAHRA whose telephone number is (571)272-0419. The examiner can normally be reached M-F 7:00 AM to 5:00 PM.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Brian Epstein can be reached at (571)-270-5389. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/REHAM K ABOUZAHRA/Examiner, Art Unit 3625
/BRIAN M EPSTEIN/Supervisory Patent Examiner, Art Unit 3625
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