DETAILED ACTION
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 .
Priority
Receipt is acknowledged of certified copies of papers required by 37 CFR 1.55.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 12/5/2025, 7/19/2024 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claim 1-20 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Claim 1-20 recites the limitation " the safety score " and “the predicted safety score” while only introducing a safety score in 1, 9, 17. There is insufficient antecedent basis for this limitation in the claim. And similarly, the dependent claims are rejected.
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.
Alice type rejection – Abstract Idea Mental Process
As to claim 1-20 the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
101 Analysis – Step 1
Claim(s) 1-20 is/are directed to a mental process of determining a motion trajectory (Process claims 9-16 and apparatus for claim 1-8 and 17-20).
101 Analysis – Step 2A, Prong 1
Regarding Prong I of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether they recite subject matter that falls within one of the follow groups of abstract ideas: a) mathematical concepts, b) certain methods of organizing human activity, and/or c) mental processes.
Independent claim 1 includes limitations that recite an abstract idea – mental process (emphasized below) and will be used as a representative claim for the remainder of the 101 rejection. Claim 1 recites:
A system for assisting a vehicle in determining a safety of an environment about the vehicle, the system comprising:
a plurality of image sensors mounted to the vehicle and configured to capture images of the environment about the vehicle; and
a processor coupled to the plurality of image sensors and programmed to:
receive the images;
execute an object classification model on the images to determine a class of one or more first objects detected in the images;
predict a safety score based on the class of the one or more first objects detected in the images, wherein the predicted safety score is associated with the safety of the environment about the vehicle; and
record the images of the environment about the vehicle while the vehicle is parked in response to (a) one or more second objects being detected in the images by the object classification model, and (b) the safety score being below a threshold. (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”)
The examiner submits that the foregoing bolded limitation(s) constitute a “mental process” because under its broadest reasonable interpretation, the claim covers performance of the limitation in the human mind. For example, “predict” in the context of this claim encompasses a person looking at data collected and forming a simple judgement. Accordingly, the claim recites at least one abstract idea – mental process.
101 Analysis – Step 2A, Prong 2
Regarding Prong II of the Step 2A analysis in the 2019 PEG, the claims are to be analyzed to determine whether the claim, as a whole, integrates the abstract into a practical application. As noted in the 2019 PEG, it must be determined whether any additional elements in the claim beyond the abstract idea integrate the exception into a practical application in a manner that imposes a meaningful limit on the judicial exception. The courts have indicated that additional elements merely using a computer to implement an abstract idea, adding insignificant extra solution activity, or generally linking use of a judicial exception to a particular technological environment or field of use do not integrate a judicial exception into a “practical application.”
In the present case, the additional limitations beyond the above-noted abstract idea are as follows (where the underlined portions are the “additional limitations” while the bolded portions continue to represent the “abstract idea”) See above.
For the following reason(s), the examiner submits that the above identified additional limitations do not integrate the above-noted abstract idea into a practical application. Claim 1 includes a processing apparatus. Regarding the additional limitations of “processor” that merely describes how to generally “apply” the otherwise mental judgements in a generic or general-purpose processing environment. The processing is recited at a high level of generality and merely automates the determining process steps.
101 Analysis – Step 2B
Regarding Step 2B of the 2019 PEG, representative independent claim 1 does not include additional elements (considered both individually and as an ordered combination) that are sufficient to amount to significantly more than the judicial exception for the same reasons to those discussed above with respect to determining that the claim does not integrate the abstract idea into a practical application. As discussed above with respect to integration of the mental process into a practical application, the additional element of using a processor to perform the determining amounts to nothing more than applying the exception using a generic computer component. Generally applying an exception using a generic computer component cannot provide an inventive concept. The sensors are used in the generic conventional manner for their purpose.
Further, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be re-evaluated in Step 2B to determine if they are more than what is well understood, routine, conventional activity in the field. The additional limitations of processing with a processing apparatus are well-understood, routine, and conventional activities because the specification does not provide any indication that the processing apparatus is anything other than a conventional computer. MPEP 2106.05(d)(II), and the cases cited therein, including Intellectual Ventures I, LLC v. Symantec Corp., 838 F.3d 1307, 1321 (Fed. Cir. 2016), TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610 (Fed. Cir. 2016), and OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015), indicate that mere collection or receipt of data over a network is a well‐understood, routine, and conventional function when it is claimed in a merely generic manner. Here receiving of data is extra pre-solution activity and recording is extra solution post activity.
Dependent claim(s) 2-8, 10-16, and 18-20 do not recite any further limitations that cause the claim(s) to be patent eligible. Rather, the limitations of dependent claims are directed toward additional aspects of the judicial exception and/or well-understood, routine and conventional additional elements that do not integrate the judicial exception into a practical application because they merely add to the mental processing. Therefore, dependent claims 2-8, 10-16, and 18-20 are not patent eligible under the same rationale as provided for in the rejection of independent claims 1, 9, and 17.
Therefore, claim(s) 1-20 is/are ineligible under 35 USC §101. Examiner recommends a controlling step.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1-4, 6, 8-12, 14, and 16-20 is/are rejected under 35 U.S.C. 102(a)(1)/102(a)(2) as being anticipated by US 20180201227 A1 hereinafter Gao.
As to claims 1 and claim 9 and claim 17, Gao discloses a system for assisting a vehicle in determining a safety of an environment about the vehicle [GAO: Abstract “A vehicle controller is programmed to monitor image data for the presence of moving external objects within the vicinity, and to activate the user interface display to display image data in response to detecting a moving external object in the vicinity while the vehicle is at a rest condition. The controller is also programmed to assign a threat assessment value based on conditions in the vicinity of the vehicle, and upload image data to an off-board server in response to the threat assessment value being greater than a first threshold.”], the system comprising:
a plurality of image sensors mounted to the vehicle and configured to capture images of the environment about the vehicle [Gao: Fig.1, 0015, 0040]; and
a processor coupled to the plurality of image sensors and programmed to [Gao: 0013 “The cameras may be any digital video recording device in communication with a processing unit of the vehicle.”]:
receive the images [Gao: 0013 “Image data acquired by the cameras is passed to the vehicle processor for subsequent actions.”];
execute an object classification model on the images to determine a class of one or more first objects detected in the images [Gao: 0043 “As discussed above, the threat assessment may include inputs from at least one of a plurality of sensor outputs, the type of detected objects,” image sensors being included. Type here may mean threat/nonthreat, movement type, person or vehicle, still object, lane markings];
predict a safety score based on the class of the one or more first objects detected in the images [Gao: 0043 “… the threat assessment may include inputs from at least one of a plurality of sensor outputs, the type of detected objects, the behavior and intent of a detected object, the host vehicle location, time of day, external light levels, and user inputs.” Type here may mean threat/nonthreat, movement type, person or vehicle, still object, lane markings], wherein the predicted safety score is associated with the safety of the environment about the vehicle [Gao: 0043 “the algorithm includes generating a threat assessment value as an objective measurement of the vicinity of the vehicle.”];
and record the images of the environment about the vehicle while the vehicle is parked in response to [Gao: 0003, “Additional vehicle responses may include automatic storage of image data relevant to the source of the perceived threat.” 0030] (a) one or more second objects being detected in the images by the object classification model[Gao: 0043 “… the threat assessment may include inputs from at least one of a plurality of sensor outputs, the type of detected objects, the behavior and intent of a detected object, the host vehicle location, time of day, external light levels, and user inputs.” Type here may mean threat/nonthreat, movement type, person or vehicle, still object, lane markings], and (b) the safety score being below a threshold [Gao: 0003, “In some examples, a predetermined buffer is used to capture image data for a duration of time preceding the point in time which the threat assessment value exceeds a threshold.” 0030].
As to claims 2, 10, and 18, Gao discloses wherein the processor is further programmed to: while the vehicle is parked, (a) execute the object classification model to determine a class of the one or more second objects [Gao: 0043 “… the threat assessment may include inputs from at least one of a plurality of sensor outputs, the type of detected objects, the behavior and intent of a detected object, the host vehicle location, time of day, external light levels, and user inputs.” Type here may mean threat/nonthreat, movement type, person or vehicle, still object, lane markings, distance], and (b) adjust the safety score based on the determined class of the one or more second objects [Gao: 0049 reduce the threat based on the context with the classification. 0025 increase with less distance object classified close or far].
As to claims 3, 11, and 19, Gao discloses wherein the processor is further programmed to: prevent recording of the images in response to (a) the one or more second objects being detected in the images and[Gao: 0026 0025 disregard sensed objects with trajectories and distances that are not a threat] (b) the safety score exceeding the threshold [Gao: 0045 “if the threat assessment is greater than Threshold 2 at step 226 the algorithm includes causing more impactful vehicle responses. In at least one example, the algorithm includes storing one or more images by initiating a local recording at step 228.”].
As to claims 4 and 12, Gao discloses wherein the processor is further programmed to adjust the predicted safety score based further on a time of day [Gao: 0043 “At step 220 the algorithm includes generating a threat assessment value as an objective measurement of the vicinity of the vehicle. As discussed above, the threat assessment may include inputs from at least one of a plurality of sensor outputs, … time of day”].
As to claims 6 and 14, Gao discloses wherein the processor is further programmed to: access a crime-related database containing crime-related information associated with a current location of the vehicle[Gao: 0021 “geographical location information may be used as a basis to vary the sensitivity of visual detection performed by the vision system when at high-risk locations. More specifically, the diligence mode algorithm may include a crime risk assessment value based on statistical crime data associated with a given geographic location.”]; and adjust the predicted safety score based on the crime-related information [Gao: 0041 “At 216 the algorithm may include determining whether the current vehicle location is at a high crime risk location. As discussed above, statistical crime data may be used to determine weighting factors to increase or reduce threat levels based on the location of the vehicle. For example, commerce locations may receive a higher threat assessment rating due to the potential exposure of user finances.”].
As to claims 8, 16, and 20, Gao discloses wherein the execution of the object classification model determines the class of the one or more first objects while the vehicle is being driven and prior to the vehicle being parked [Gao: Fig.3 shows a driven vehicle performing the method, 0052].
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 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.
Claim 5 and 13 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gao in view of US 20240217479 A1 hereinafter Russo.
As to claims 5 and 13, Gao adjusts threat/safety scores based on context (time of day, lighting, etc.) but does not explicitly disclose using machine learning. However, wherein the processor is further programmed to: execute a context-aware machine learning model on the images to determine a safety threat in the environment about the vehicle [Russo: 0133 “Put another way, in the carjacking threshold conditions 138 next described, image data from the one or more cameras 126c may be processed and/or analyzed by the controller 218 and/or the device 102 (e.g., via one or more layers of a neural network of the machine learning algorithm 104) to confirm that the person 120 is not a public-safety officer, such as a police officer, or a valet, and/or any other suitable type of person that may have been previously determined to lawfully approach a vehicle when the vehicle is stopped, and/or traveling below a threshold velocity, and the like.”]; .
Claim 7 and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Gao in view of US 20190080313 A1 hereinafter Van Wiemeersch.
As to claims 7 and 15, Gao discloses adjusting safety scores based on changing threats from sensor input, but does not disclose where one of the sensors is a microphone associated with breaking glass. Van Wiemeersch discloses further comprising a microphone mounted to the vehicle and configured to detect a sound of broken glass [Van Wiemeersch: 0011, 0021 the sound data is provided to the boundary alert (i.e., the teachings of Gao.)]; Wiemeersch) in a known way (Goa’s processing of sensor inputs to determine threat/safety scores) with predictable results and a good likelihood of success for the benefit of having more comprehensive view on threat/safety.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 11650309 B2 Low-power vehicle sentinel systems and methods are disclosed herein. An example method includes obtaining electromagnetic signals in a target area surrounding a vehicle. The electromagnetic signals can be obtained from electromagnetic elements mounted to the vehicle. The method can include determining attributes or behaviors of an object in the target area based on the electromagnetic signals and executing a response measure based on the attributes or behaviors of the object.
The examiner has pointed out particular references contained in the prior art of record in the body of this action for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. Applicant should consider the entire prior art as applicable as to the limitations of the claims. It is respectfully requested from the applicant, in preparing the response, to consider fully the entire references as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner.
Inquiry
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FREDERICK M BRUSHABER whose telephone number is (313)446-4839. The examiner can normally be reached Monday-Friday 8am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Hunter Lonsberry can be reached at (571) 272-7298. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/FREDERICK M BRUSHABER/
Primary Examiner
Art Unit 3665
/FREDERICK M BRUSHABER/Primary Examiner, Art Unit 3665