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 .
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.
Claim 1-10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites detecting a vehicle located within an area, detecting a person approaching the vehicle, an in response to a person approaching the vehicle executing a deterrence action.
The limitations of detecting a vehicle located within an area, detecting a person approaching the vehicle, an in response to a person approaching the vehicle executing a deterrence action, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting “by a computer executing a machine-learning model,” nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the “by a computer executing a machine-learning model” language, “detecting” in the context of this claim encompasses the user detecting an individual in an area.
This judicial exception is not integrated into a practical application. In particular, the claim only recites one additional element – using a computer executing a machine-learning model detecting and response. The computer executing a machine-learning model in both steps is recited at a high-level of generality (i.e., as a generic processor
performing a generic computer function of detecting and responding based on a determined amount of use) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
The dependent claims 2-10 do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a processor to perform both the ranking and determining steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
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 (i.e., changing from AIA to pre-AIA ) 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.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Panthri (Pub. No.: 2025/0115272 A1).
1) In regard to claim 11, Panthri discloses the claimed apparatus (fig. 3) comprising:
an image sensor (fig. 3: 320 and ¶0031); and
a processor (fig. 3: 210) executing a machine-learning model (¶0083) to:
detect a vehicle located within an area (¶0070);
detect a person approaching the vehicle (¶0034); and
in response to the person approaching the vehicle, execute a deterrence action (¶0035-¶0036),
wherein the machine-learning model is trained by applying the machine-learning model on historical data including image data of vehicles (¶0049 and it is inherent a machine learning model would use historical data to determine when a suspicious activity occurs).
2) In regard to claim 12 (dependent on claim 11), Panthri further disclose the apparatus of claim 11, wherein detecting the vehicle located within the area
includes tracking the vehicle entering the area (figs. 5-8).
3) In regard to claim 13 (dependent on claim 11), Panthri further disclose the apparatus of claim 11, wherein detecting the vehicle located within the area includes determining that the vehicle is parked (figs. 5-8).
4) In regard to claim 14 (dependent on claim 11), Panthri further disclose the apparatus of claim 11, wherein detecting the vehicle located within the area includes determining a location of the vehicle using multiple sensors (¶0027).
5) In regard to claim 15 (dependent on claim 11), Panthri further disclose the apparatus of claim 11, wherein detecting the vehicle located within the area includes identifying the vehicle (¶0044).
6) In regard to claim 16 (dependent on claim 11), Panthri further disclose the apparatus of claim 11, wherein detecting the vehicle located within the area includes determining a state of the vehicle (¶0049).
7) In regard to claim 17 (dependent on claim 11), Panthri further disclose the apparatus of claim 11, wherein detecting the person approaching the vehicle
includes determining one or more characteristics or actions of the person (¶0049).
8) In regard to claim 18 (dependent on claim 17), Panthri further disclose the apparatus of claim 17, wherein detecting the person approaching the vehicle
includes determining that the one or more characteristics or actions of the person are indicative of theft (¶0049).
9) In regard to claim 19 (dependent on claim 11), Panthri further disclose the apparatus of claim 11, wherein executing the deterrence action includes
emitting one or more audiovisual signals (¶0053).
10) In regard to claim 20 (dependent on claim 11), Panthri further disclose the apparatus of claim 11, wherein executing the deterrence action includes generating, by the processor executing the machine-learning model, one or more audiovisual signals (¶0053).
11) In regard to claim 1, claim 1 is rejected and analyzed with respect to claim 11 and the references applied.
12) In regard to claim 2 (dependent on claim 1), claim 2 is rejected and analyzed with respect to claim 12 and the references applied.
13) In regard to claim 3 (dependent on claim 1), claim 3 is rejected and analyzed with respect to claim 13 and the references applied.
14) In regard to claim 4 (dependent on claim 1), claim 4 is rejected and analyzed with respect to claim 14 and the references applied.
15) In regard to claim 5 (dependent on claim 1), claim 5 is rejected and analyzed with respect to claim 15 and the references applied.
16) In regard to claim 6 (dependent on claim 1), claim 6 is rejected and analyzed with respect to claim 16 and the references applied.
17) In regard to claim 7 (dependent on claim 1), claim 7 is rejected and analyzed with respect to claim 17 and the references applied.
18) In regard to claim 8 (dependent on claim 7), claim 8 is rejected and analyzed with respect to claim 18 and the references applied.
19) In regard to claim 9 (dependent on claim 1), claim 9 is rejected and analyzed with respect to claim 19 and the references applied.
20) In regard to claim 10 (dependent on claim 1), claim 10 is rejected and analyzed with respect to claim 20 and the references applied.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CURTIS J KING whose telephone number is (571)270-5160. The examiner can normally be reached Mon-Fri 6:00 - 2:00 EST.
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/CURTIS J KING/Primary Examiner, Art Unit 2685