Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Status of Claims
This action is a first action on the merits in response to the application filed on 07/09/2025.
Claims 1 – 20 are currently pending and have been examined in this application.
Information Disclosure Statement
The information disclosure statement filed 07/09/2025 fails to comply with 37 CFR 1.98(a)(2), which requires a legible copy of each cited foreign patent document; each non-patent literature publication or that portion which caused it to be listed; and all other information or that portion which caused it to be listed. The NPL references and foreign patent documents have not been considered. The US Patents and PGPubs have been considered.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1, 2, 11, 12 and 18 of Application no. 19/263,868 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1, 12 and 18 of U.S. Patent No. 12,380,511 (Hereinafter “’511”). Although the claims at issue are not identical, they are not patentably distinct from each other because:
The narrower patented claims anticipate the broader instant application claims.
Claim of the referenced patent ‘511 read:
1. A computer-implemented method, performed by one or more processors, for identifying a vehicle associated with a trip, the computer-implemented method comprising:
receiving, from a mobile computing device temporarily disposed within an initially unidentified vehicle, a first geographic location associated with a vehicle entry event corresponding to a first point in time and a second geographic location associated with a vehicle exit event corresponding to a second point in time;
receiving sensor data generated by one or more sensors of a mobile computing device at times between the first point in time and the second point in time;
generating a trip log associated with the mobile computing device, the trip log including portions of the sensor data generated by the one or more sensors of the mobile computing device temporarily disposed inside the initially unidentified vehicle at times between the first point in time and the second point in time;
when a number of previous trip logs associated with the mobile computing device exceeds a threshold number, triggering an execution of a multivariate analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of the previous trip logs associated with the mobile computing device; and
identifying the initially unidentified vehicle associated with the trip log, based on the multivariate analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previous trip logs associated with the mobile computing device.
Claims 12 and 18 substantially recite the subject matter of Claim 1
Claims of the instant application read:
A computer-implemented method, performed by one or more processors of a mobile computing device, for identifying a vehicle associated with a trip, the computer- implemented method comprising:
generating sensor data by one or more sensors of the mobile computing device while the mobile computing device is temporarily disposed within an initially unidentified vehicle;
generating a trip log associated with the mobile computing device, the trip log including at least a portion of the sensor data generated by the one or more sensors of the mobile computing device while the mobile computing device is temporarily disposed inside the initially unidentified vehicle;
triggering an execution of an analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previous trip logs associated with the mobile computing device; and
identifying the initially unidentified vehicle associated with the trip log, based on the analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previous trip logs associated with the mobile computing device.
2. The computer-implemented method of claim 1, further comprising: determining a first geographic location associated with a vehicle entry event corresponding to a first point in time and a second geographic location associated with a vehicle exit event corresponding to a second point in time, wherein generating the sensor data by the one or more sensors of the mobile computing device includes generating sensor data at times between the first point in time and the second point in time.
Claims 11, 12 and 18 are recite substantially the subject matter Claim 1 and 2.
However, it would have been obvious to one of ordinary skill in the art at the time of the invention to modify claim 1 of the instant application to receiving from a mobile computing device within an unidentified vehicle, a first and second geographic location associated with vehicle entry/exit and receiving sensor data generated by one or more sensors of a mobile computing device in order to assist in determining a vehicle associated with a user mobile device (see Spec ¶002).
Claims 1, 11 and 18 of Application no. 19/263,868 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1, 12 and 18 of U.S. Patent No. 11,922,511 (Hereinafter “’2511”).
Although the claims at issue are not identical, they are not patentably distinct from each other because:
The narrower patented claims anticipate the broader instant application claims.
Claim of the referenced patent ‘2551 read:
1. A computer-implemented method for verifying the use of a primary vehicle associated with a user's insurance policy, comprising:
generating sensor data by one or more sensors of a mobile computing device temporarily disposed inside an initially unidentified vehicle at times between a first point in time corresponding to a vehicle entry event and a second point in time corresponding to a vehicle exit event;
receiving, by one or more computer processors, the sensor data generated by the one or more sensors of the mobile computing device temporarily disposed within the initially unidentified vehicle;
generating, with the one or more computer processors, a trip log associated with the mobile computing device, the trip log including portions of the sensor data generated by the sensors of the mobile computing device temporarily disposed inside the initially unidentified vehicle at times between the first point in time and the second point in time;
storing, with the one or more computer processors, the trip log associated with the mobile computing device in a trip database;
when a number of previously stored trip logs associated with the mobile computing device exceeds a threshold number, triggering, with the one or more computer processors, an execution of a multivariate analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previously stored trip logs associated with the mobile computing device in the trip database; and
identifying the initially unidentified vehicle associated with the trip log, with the one or more computer processors, based on the multivariate analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previously stored trip logs associated with the mobile computing device in the trip database.
Claims 12 and 18 substantially recite the subject matter of Claim 1.
Claims of the instant application read:
A computer-implemented method, performed by one or more processors of a mobile computing device, for identifying a vehicle associated with a trip, the computer- implemented method comprising:
generating sensor data by one or more sensors of the mobile computing device while the mobile computing device is temporarily disposed within an initially unidentified vehicle;
generating a trip log associated with the mobile computing device, the trip log including at least a portion of the sensor data generated by the one or more sensors of the mobile computing device while the mobile computing device is temporarily disposed inside the initially unidentified vehicle;
triggering an execution of an analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previous trip logs associated with the mobile computing device; and
identifying the initially unidentified vehicle associated with the trip log, based on the analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previous trip logs associated with the mobile computing device.
Claims 11 and 18 substantially recite the subject matter of Claim 1.
However, it would have been obvious to one of ordinary skill in the art at the time of the invention to modify claim 1 of the instant application to include generating sensor data between a first/second point of time corresponding to vehicle entry/exit, receiving sensor data, storing the trip log associated with the mobile computing device in a trip database and triggering and execution of multivariate analysis of sensor data based on when a number of previously stored trip logs associated with the mobile computing device in order to assist in determining a vehicle associated with a user mobile device (see Spec ¶002).
Claims 1, 11, and 18 of Application no. 19/263,868 are rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1, 10 and 14 of U.S. Patent No. 11,182,859 (Hereinafter “’859”).
Although the claims at issue are not identical, they are not patentably distinct from each other because:
The narrower patented claims anticipate the broader instant application claims.
Claim of the referenced patent ‘859 read:
A computer-implemented method for verifying the use of a primary vehicle associated with a user's insurance policy, comprising:
generating sensor data by one or more sensors of a mobile computing device temporarily disposed inside a vehicle;
receiving, via a network interface, an indication of a vehicle entry event and a vehicle exit event from the mobile computing device temporarily disposed inside the vehicle, wherein the vehicle entry event corresponds to a user of the mobile computing device entering the vehicle at a first point in time, and wherein the vehicle exit event corresponds to the user exiting the vehicle at a second point in time;
generating, with one or more computer processors, a trip log including portions of the sensor data generated by the sensors of the mobile computing device temporarily disposed inside the vehicle at times between the first point in time and the second point in time;
storing, with the one or more computer processors, the trip log associated with the mobile computing device in a trip database;
when a number of previously stored trip logs associated with the mobile computing device exceeds a threshold number, triggering, with the one or more computer processors, an execution of a multivariate analysis of the sensor data of the trip log and the sensor data of previously stored trip logs associated with the mobile computing device in the trip database; and
identifying, with the one or more computer processors, based on the multivariate analysis of the sensor data of the trip log and the sensor data of previously stored trip logs in the trip database associated with the mobile computing device, the vehicle associated with the trip log as:
(a) a primary vehicle associated with the user's insurance policy or (b) an other vehicle driven by the user, wherein the other vehicle driven by the user is a rental vehicle or a borrowed vehicle, by using a learning algorithm to cluster the trip log and the previously stored trip logs associated with the mobile computing device into a primary vehicle trip log group or one or more other vehicle trip log groups based on one or more of:
(i) acceleration or braking patterns associated with the vehicle determined based on sensor data stored in each trip log;
(ii) audio signals associated with the vehicle determined based on sensor data stored in each trip log;
(iii) driving routes associated with the vehicle determined based on sensor data stored in each trip log; or
(iv) destinations associated with the vehicle determined based on sensor data stored in each trip log.
Claims 10 and 14 substantially recites the subject matter of Claim 1.
Claims of the instant application read:
A computer-implemented method, performed by one or more processors of a mobile computing device, for identifying a vehicle associated with a trip, the computer- implemented method comprising:
generating sensor data by one or more sensors of the mobile computing device while the mobile computing device is temporarily disposed within an initially unidentified vehicle;
generating a trip log associated with the mobile computing device, the trip log including at least a portion of the sensor data generated by the one or more sensors of the mobile computing device while the mobile computing device is temporarily disposed inside the initially unidentified vehicle;
triggering an execution of an analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previous trip logs associated with the mobile computing device; and
identifying the initially unidentified vehicle associated with the trip log, based on the analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previous trip logs associated with the mobile computing device.
Claims 11 and 18 substantially recite the subject matter of Claim 1.
However, it would have been obvious to one of ordinary skill in the art at the time of the invention to modify claim 1 of the instant application to include storing the trip log associated with the mobile computing device in a trip database, triggering and execution of multivariate analysis of sensor data based on when a number of previously stored trip logs and identifying the vehicle in order to assist in determining the primary driver of a vehicle (see Spec ¶002).
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 recites:
generating sensor data by [one or more sensors of the mobile computing device ]while [the mobile computing device] is temporarily disposed within an initially unidentified vehicle;
generating a trip log associated with [the mobile computing device], the trip log including at least a portion of the sensor data generated by the one or more sensors of [the mobile computing device while [the mobile computing device is temporarily disposed inside the initially unidentified vehicle;
triggering an execution of an analysis of the sensor data of the trip log associated with [the mobile computing device] and the sensor data of previous trip logs associated with [the mobile computing device]; and
identifying the initially unidentified vehicle associated with the trip log, based on the analysis of the sensor data of the trip log associated with [the mobile computing device] and the sensor data of previous trip logs associated with [the mobile computing device].
The limitation under its broadest reasonable interpretation covers Certain Methods of Organizing Human Activities related to fundamental economic principles dealing with insurance and commercial interactions, but for the recitation of generic computer components (e.g. a processor and memory). For example, generating sensor data while temporarily disposed in an unidentified vehicle, generating a trip log including sensor data, triggering an execution of an analysis of the sensor data of the trip log and previous trip logs and identifying the initially unidentified vehicle associated with the trip log involves insurance related activities and commercial interactions. Accordingly, the claim recites an abstract idea of Certain Methods of Organizing Human Activity.
Additionally, the claims are directed to Mental Processes related to observation and evaluation of data (e.g. generating sensor data, generating a trip log, analysis of sensor data to produce a result of identifying an unidentified vehicle.
Independent Claims 11 and 18 substantially recite the subject matter of Claim 1 and also include the abstract ideas identified above. The dependent claims encompass the same abstract ideas. For instance, Claim 2 is directed to determining a first and second geographic location associated with a vehicle entry/exit event (analysis); Claim 3 is directed to receiving an indication of the vehicle entry event and vehicle exit event based on supervised classification algorithm( analysis using complex math); Claim 4 continuously generation sensor data (receiving data); Claim 5 is directed to generating sensor data including GPS data; Claim 6 is directed to sensor data types; Claim 7 capturing in the trip log an originating point associated with entry/ exit; Claim 8 is directed a learning algorithm to cluster the trip log and previous trip logs (analysis using complex math); Claim 9 is directed sensor data includes engine sounds and Claim 10 is directed analysis of sensor data in a weighted manner. Claims 12-17 and 20 substantially recite the subject matter of Claims 2, 3,5, 6,9 and 10 and encompass the same abstract idea.
The judicial exceptions are not integrated into a practical application. Claim 1 recites the additional elements of one or more processors of a mobile computing device. Claim 11 recites the additional elements of one or more processors, or nor more memories coupled to the one or more processors and a mobile computing device. Claim 18 recites the additional elements of a non-transitory computer readable storage medium and one or more processors of a mobile computing device (see ¶0022 and Figure 1).
For instance, the steps of generating sensor data is data gathering activity. The steps of generating a trip loc associated with the mobile device; triggering an execution of an analysis of the sensor data of trip log and previous trip logic and identifying the initially unidentified vehicle associated with the trip log involves analyzing data.
Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer components (e.g. a processor and memory). The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer component (e.g. a processor and memory). Therefore, the additional elements do not integrate the abstract ideas into a practical application because it does not impose meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As stated above, the additional elements of a processor, a memory, a crm, etc. are considered generic computer components performing generic computer functions that amount to no more than instructions to implement the judicial exception. Mere, instructions to apply an exception using generic computer components cannot provide an inventive concept.
The dependent claims when analyzed both individually and in combination are also held to be ineligible for the same reason above and the additional recited limitations fail to establish that the claims are not directed to an abstract. The additional limitations of the dependent claims when considered individually and as an ordered combination do not amount to significantly more than the abstract idea.
Looking at these limitations as an ordered combination and individually adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use generic computer components, to "apply" the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself. Therefore, Claims 1-20 are not patent eligible.
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 factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 (AIA ) 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.
Claims 1-8, 11-15 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Grokop et al. (US 2013/0245986) further in view of Basir et al. (US 2013/0041521).
Claim 1:
Grokop discloses:
A computer-implemented method, performed by one or more processors of a mobile computing device, for identifying a vehicle associated with a trip, the computer- implemented method comprising: (see at least Figure
1 and associated text; see also 1[0002-1[0006, a mobile device is used to detect
that a user is traveling in association with a vehicle based on motion data)
generating sensor data by one or more sensors of the mobile computing device while the mobile computing device is temporarily disposed within an initially unidentified vehicle; (see at least ¶0002-¶0006, a mobile device is used to detect that a user is traveling in association with a vehicle based on motion; see also ¶0025, motion state machine based on sensor data determines whether the user of mobile device is walking, standing , sitting in an automobile; see also Figure 9 and associated text)
[generating a trip log associated with the mobile computing device, the trip log including ]at least a portion of the sensor data generated by the one or more sensors of the mobile computing device while the mobile computing device is temporarily disposed inside the initially unidentified vehicle (see at least ¶0002-¶0006, a mobile device is used to detect that a user is traveling in association with a vehicle based on motion; see also ¶0025, motion state machine based on sensor data determines whether the user of mobile device is walking, standing , sitting in an automobile; see also Figure 9 and associated text)
While Grokop discloses the above limitations, Grokop does not explicitly disclose the following limitations; however, Basir discloses:
A computer-implemented method, performed by one or more processors of a mobile computing device, for identifying a vehicle associated with a trip, the computer- implemented method comprising: see at least ¶0018-¶0026, determine which drivers are driving in each vehicle during each journey; see also ¶0005, mobile phone)
generating a trip log associated with the mobile computing device, the trip log including at least a portion of the sensor data generated by the one or more sensors of the mobile computing device while the mobile computing device is temporarily disposed inside the initially unidentified vehicle; (see at least Figure 1 and associated text; see also ¶0016-¶0018, the server includes profiles related to the vehicle or user and contain information gathered from the vehicle/user operation including journeys associated to vehicle/user)
triggering an execution of an analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previous trip logs associated with the mobile computing device; and (Basir see at least Figure 1 and associated text; see also ¶0016-¶0018, the server includes profiles related to the vehicle or user and contain information gathered from the vehicle/user operation including journeys associated to vehicle/user; see also ¶0018-¶0026,, determining which drivers are driving in each vehicle during each journey, thus indicating a particular vehicle being used; see also ¶0057, provide identification of common drivers across multiple journeys spanning one or more vehicles)
identifying the initially unidentified vehicle associated with the trip log, based on the analysis of the sensor data of the trip log associated with the mobile computing device and the sensor data of previous trip logs associated with the mobile computing device. (see at least Figure 1 and associated text; see also ¶0016-¶0018, the server includes profiles related to the vehicle or user and contain information gathered from the vehicle/user operation including journesy associated to vehicle/user; see also ¶0018-¶0026,, determining which drivers are driving in each vehicle during each journey, thus indicating a particular vehicle being used; see also ¶0057, provide identification of common drivers across multiple journeys spanning one or more vehicles)
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the detection of various motion states of a mobile device as taught in Grokop with the vehicle monitoring system and data classification of Basir
in order to collect vehicle usage data which can be used to determine user and/or vehicle behavior (see ¶0002-¶0003) as well as vehicle utilization.
Claim 2:
Grokop and Basir disclose claim 1. Grokop further discloses:
further comprising: determining a first geographic location associated with a vehicle entry event corresponding to a first point in time and a second geographic location associated with a vehicle exit event corresponding to a second point in time, (see at least ¶0019; see also ¶0024-¶0025, determining that a mobile is stopped and positioning information using GPS; see also ¶0034-¶0035, determining various states at each time instance; see also Abstract)
wherein generating the sensor data by the one or more sensors of the mobile computing device includes generating sensor data at times between the first point in time and the second point in time. ( see also ¶0034-¶0035, determining various states at each time instance; see also Abstract)
Claim 3:
Grokop and Basir disclose claim 2. Grokop further discloses:
receiving an indication of the vehicle entry event and an indication of the vehicle exit event based on an execution of a supervised classification algorithm on the sensor data generated by the mobile computing device. (see at least ¶0022, motion state classification; see also ¶0016,classifier decision refers to a determination of the present motion state of a mobile device; see also ¶0025-¶0027, motion classifiers)
Claim 4:
Grokop and Basir disclose claim 1. Grokop further discloses:
further comprising: continuously generating the sensor data by the one or more sensors of the mobile computing device. (see at least ¶0050, sensor data is logged continuously; see also ¶0072, motion sensor peripherals)
Claim 5:
Grokop and Basir disclose claim 1. Grokop further discloses:
further comprising: generating sensor data that includes data by a geographic positioning system (GPS) receiver that is integrated with the mobile computing device. (see at least ¶0019, sensors associated with the mobile device may include a GPS receiver)
Claim 6:
Grokop and Basir disclose claim 1. Grokop further discloses:
wherein the sensor data generated by the one or more sensors of the mobile computing device includes at least one of accelerometer data, gyroscope data, microphone data, video data, barometer data, compass data, ambient light data, proximity data, and magnetometer data. (see at least ¶0045, acceleration readings; see also ¶0019, accelerometer; see also ¶0068)
Claim 7:
While Grokop and Basir disclose claim 1, Grokop further discloses (see also ¶0025, motion state machine based on sensor data determines whether the use of mobile device is walking, standing, sitting in an automobile, etc.; see also ¶0032, detect a user is riding in a vehicle, walks to a car, enters or exits), Grokop does not explicitly disclose the following limitation; however, Basir does disclose
further comprising: capturing in the trip log an originating point having the first geographic location associated [with the vehicle entry event ]and a destination point having the second geographic location associated [with the vehicle exit event.] (see at least ¶0034, start and end locations; see also ¶0013, GPS receiver),
It would have been obvious to one of ordinary skill in the art at the time of the
invention to combine the detection of various motion states of a mobile device as taught
in Grokop with the vehicle monitoring system and data classification of Basir
in order to collect vehicle usage data which can be used to determine user and/or vehicle behavior (see ¶0002-¶0003) as well as vehicle utilization.
Claim 8:
While Grokop and Basir disclose claim 1, Grokop does not explicitly disclose the following limitation; however, Basir does disclose:
further comprising using a learning algorithm to cluster the trip log and the previous trip logs associated with the mobile computing device into a primary vehicle trip log group or one or more other vehicle trip log groups. (see at least ¶0024-¶0026, trip based analysis includes clustering driving patterns and using a classifier assigning each driver to a cluster; see also ¶0040, unsupervised learning such as k-means clustering)
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the detection of various motion states of a mobile device as taught in Grokop and the vehicle monitoring system and data classification of Basir with the scoring algorithm based on regression analysis as in Rippel in order to collect vehicle usage data which can be used to determine user and/or vehicle behavior (see ¶0002-¶0003) as well as vehicle utilization.
Claims 11 for a mobile computing device (Grokop see Figure 9 and associated text) and Claim 18 (Grokop see ¶0067) substantially recite the subject matter of Claim 1 and are rejected based on the same rationale.
Claims 12-15 for a mobile computing device substantially recites the subject matter of Claims 2-6 and are rejected based on the same rationale.
Claims 9, 16 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Grokop et al. (US 2013/0245986) in view of Basir et al. (US 2013/0041521) in view of Abramson et al. (US 2012/00711151).
Claim 9:
While Grokop and Basir disclose claim 1, neither explicitly disclose the following limitations; however, Abramson does disclose:
wherein the sensor data generated by the one or more sensors of the mobile computing device includes data indicating engine sounds of the initially unidentified vehicle that is generated via a microphone associated with the mobile computing device. (see at least ¶0254, an on board cell phone includes a microphone for hearing engine sounds)
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the detection of various motion states of a mobile device as taught in Grokop and the vehicle monitoring system and data classification of Basir with the mobile device microphone of Abramson since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 16 for a mobile computing device and Claim 19 for a CRM substantially recites the subject matter of Claim 9 and are rejected based on the same rationale.
Claims 10, 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Grokop et al. (US 2013/0245986) in view of Basir et al. (US 2013/0041521) in view of Desai et al. (US 2010/0228604).
Claim 10:
While Grokop and Basir disclose claim 1 and Basir further discloses k-means clustering, neither explicitly disclose the following limitation; however, Desai does disclose:
wherein the analysis is performed on the sensor data in a weighted manner. (see at least ¶0083, weighting factors may be provided to a clustering algorithm module to generate product clusters using k-means clustering)
It would have been obvious to one of ordinary skill in the art at the time of the invention to combine the detection of various motion states of a mobile device as taught in Grokop and the vehicle monitoring system and data classification of Basir with the weighting factors of Desai to provide importance values to various factors in analyzing data.
Claim 17 for a mobile computing device and Claim 20 for a CRM substantially recites the subject matter of Claim 1 and is rejected based on the same rationale.
Conclusion
The prior art made of record and not relied upon is considered relevant but not applied:
Hassib et al. (US 2013/0190967) discloses monitoring drivers of a vehicle such as someone other than the primary policyholder may have driven the vehicle, or the mobile communications device may have been powered down or not present. Such information may indicate that the vehicle was operated without being monitored by a specific mobile computing device.
Armitage et al. (US 2011/0281564) discloses receiving activity information for a transportation vehicle, receiving mobile phone usage information associated with the transportation vehicle, and processing the activity information and the mobile phone usage information to determine behavior of a driver operating the transportation vehicle.
Robertson et al. (US 2008/0192056) discloses a charting animator …
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Renae Feacher whose telephone number is 571-270-5485. The Examiner can normally be reached Monday-Friday, 9:00 am - 5:00 pm. If attempts to reach the examiner by telephone are unsuccessful, the Examiner's supervisor, Beth Boswell can be reached at 571-272-6737.
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/Renae Feacher/
Primary Examiner, Art Unit 3625
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