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
This action is in response to communications filed on 5/20/2025. Claims 1-16 have been preliminarily cancelled and claims 17-36 have been newly added. Accordingly, claims 17-36 are pending.
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 17- 36—in particular Independent claims 17 & 26—are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite “sampling, extracting, determining, correlating and classifying…” data. These limitations, as drafted, are processes that, under its broadest reasonable interpretation, covers performance of the limitations in the mind. But for the vehicle processing device and vehicle memory language, the claims encompass a user simply comparing the collected data to a predetermined/configurable threshold in his/her mind. The mere nominal recitation of a generic bus, processor and memory does not take the claim limitation out of the mental processes grouping. Thus, the claims recite a mental process which is an abstract idea.
This judicial exception is not integrated into a practical application. The claims recite the elements of sampling, extracting, determining, correlating and classifying and that a generic computer preform these steps. The sampling and extracting steps are recited at a high level of generality (i.e., as a general means of receiving/transmitting and storing data for use in the correlating and classifying steps), and as such they amount to mere data gathering, which is a form of insignificant extra-solution activity. The processor that performs the correlating and classifying steps is recited at a high level of generality, and merely automates the correlating and classifying steps. Each of the additional limitations are no more than mere instructions to apply the exception using a generic computer component (the processor). The combination of these additional elements are no more than mere instructions to apply the exception using a generic computer component (the processor). Accordingly, even in combination, these additional elements do not integrate the abstract idea into a practical application. 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 discussed with respect to Step 2A Prong Two, the additional elements in the claim amount to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B and does not provide an inventive concept.
For the receiving, comparing, calculating and storing steps were considered extra-solution activity in Step 2A, this has been re-evaluated in Step 2B and determined to be well-understood, routine, conventional activity in the field. The background does not provide any indication that the processor is anything other than a generic, off-the-shelf computer component, and the Symantec, TLI, and OIP Techs. court decisions (MPEP 2106.05(d)(II)) 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 (as it is here). For these reasons, there is no inventive concept. The claim is not patent eligible.
As per claims 18-25 & 27-36 they all depend from claims 17 and 26 and as such are rejected for having the same deficiencies as those presented above with respect to claims 17 & 26 above.
Claim Rejections - 35 USC § 102
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 17-22 and 25-34 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Miller et al. (hereinafter Miller, US 8736434 B2).
Miller discloses:
17: A method involving first sensor data and second sensor data, the method comprising:
sampling the first sensor data within a first time window, wherein the first sensor data is generated by a first sensor of an onboard vehicle system, wherein the onboard vehicle system is configured to couple to a vehicle (see Miller at least fig. 1-8 and in particular fig. 1-2, 6-8 and Abstract; cameras aimed at interior of the vehicle, recording activity inside the vehicle);
electronically extracting interior activity data indicating a state of a driver from the first sensor data (see Miller at least fig. 1-8 and in particular fig. 1-2, 6-8 and Abstract; driver belt status, phone status and potential collision events);
determining an interior event based on the interior activity data (see Miller at least fig. 1-8 and in particular fig. 1-2, 6-8 and Abstract; detailed driver performance events);
sampling the second sensor data within a second time window, wherein the second sensor data is generated by a second sensor of the onboard vehicle system (see Miller at least fig. 1-8 and in particular fig. 1-2, 6-8 and Abstract; cameras aimed at exterior of the vehicle, recording activity outside the vehicle—e.g., LDW etc.);
electronically extracting exterior activity data from the second sensor data (see Miller at least fig. 1-8 and in particular fig. 1-2, 6-8 and Abstract; cameras aimed at interior/exterior of the vehicle);
determining an exterior event based on the exterior activity data (see Miller at least fig. 1-8 and in particular fig. 1-2, 6-8 and Abstract; potential collision events);
correlating the interior event and the exterior event to generate combined event data, wherein the act of correlating comprises (see Miller at least fig. 1-8 and in particular fig. 1-2, 6-8 and Abstract):
determining a first metric based on the interior event (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract; OCD usage, detailed driver performance events and calculate metrics from data),
determining a second metric associated with the exterior event (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract), and
determining a third metric based on the first metric and the second metric (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract; OCD usage, detailed driver performance events and calculate metrics from data); and
classifying the combined event data (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract; potential collision events);
wherein the act of determining the interior event, the act of determining the exterior event, and the act of correlating the interior event and the exterior event to generate combined event data, are performed by one or more electronic processing units (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
18: comprises: determining a relative distance between the vehicle and an object based on the second sensor data (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
19: wherein the object is a secondary vehicle, and wherein the act of determining the exterior event comprises determining that the relative distance between the vehicle and the secondary vehicle is below a threshold (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
20: wherein the exterior event comprises a near-miss event, wherein the near-miss event occurs within the first-time window, and wherein the act of correlating the interior event and the exterior event comprises associating the interior event with the near-miss event; and wherein the combined event data comprises the near-miss event, and the associated interior event (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
21: wherein the state of the driver comprises a distracted state, and the electronically extracted interior activity data indicates the distracted state of the driver (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
22: wherein the second metric associated with the exterior event indicates a severity of the exterior event (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
25: wherein the first metric comprises a weight (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
26: A method involving a first sensor data and a second sensor data, the method comprising: sampling the first sensor data within a first time window, wherein the first sensor data is generated by a first sensor of an onboard vehicle system that is configured to couple to a vehicle; electronically extracting interior activity data from the first sensor data; determining an interior event based on the interior activity data; sampling the second sensor data within a second time window, wherein the second sensor data is generated by a second sensor of the onboard vehicle system; electronically extracting exterior activity data from the second sensor data; determining an exterior event based on the exterior activity data; correlating the exterior event and the interior event to generate combined event data, wherein the act of correlating the interior event with the exterior event comprises calculating a probability that the interior event and the exterior event are related, wherein the combined event data comprises the exterior event, the interior event, the probability, or any combination of the foregoing; and classifying the combined event data; wherein the act of determining the interior event, the act of determining the exterior event, and the act of correlating the exterior event and the interior event to generate the combined event data, are performed by one or more electronic processing units (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract; see claim 1 above).
27: wherein the first sensor data comprises gyroscope data (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
28: wherein the act of electronically extracting the interior activity data comprises determining a mean time interval between steering inputs based on the gyroscope data; and wherein the act of determining the interior event comprises determining a driver distraction event based on the mean time interval exceeding a threshold (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
29: wherein the act of correlating the exterior event and the interior event comprises: determining a first metric based on the interior event; determining a second metric associated with the exterior event; and determining a third metric based on the first metric and the second metric (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
30: wherein the first metric comprises a weight (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
31: wherein the onboard vehicle system is integrated into a mountable unit configured to couple to the vehicle (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
32: wherein the interior event and the exterior event are correlated based on relative geometric arrangement between the first sensor and the second sensor (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
33: wherein the first sensor data comprises a first image data, and the first sensor comprises a first camera of the onboard vehicle system; and wherein the second sensor data comprises a second image data, and the second sensor comprises a second camera of the onboard vehicle system (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
34: wherein the first time window is coextensive with the second time window (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract).
Claim Rejections - 35 USC § 103
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.
Claims 23-24 & 35-36 are rejected under 35 U.S.C. 103 as being unpatentable over Miller in view of Breed (US 2008/0036580 A1).
As per claim 23, Miller discloses the invention as detailed above.
However, Miller does not appear to explicitly disclose further comprising generating training data based on the classified combined event data.
Nevertheless, Breed—who is in the same field of endeavor--discloses further comprising generating training data based on the classified combined event data (see Breed at least fig. 1-64 and in particular fig. 1-8E & par. 238, 251, 345, 353, 357; training data and training database, data used for training process and training stage).
One of ordinary skill in the art would have been motivated to combine Breed’s use of data for training purposes with those of Miller’s in order to form an overall more efficient and safer system (i.e., by analyzing the data to determine points of concern/weakness).
Motivation to combine Breed with Miller not only comes from knowledge well known in the art, but also from Breed (see Bree at least Abstract and Summary).
Both Miller and Breed disclose claim 24: further comprising: training a model using the training data; and transmitting a copy of the model to the vehicle (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract and see Breed at least fig. 1-64 and in particular fig. 1-8E & par. 238, 251, 345, 353, 357).
Motivation to combine Miller and Breed, in the instant claim, is the same as that in claim 23 above.
Both Miller and Breed disclose claim 35: further comprising generating training data based on the classified combined event data (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract and see Breed at least fig. 1-64 and in particular fig. 1-8E & par. 238, 251, 345, 353, 357).
Motivation to combine Miller and Breed, in the instant claim, is the same as that in claim 23 above.
Both Miller and Breed disclose claim 36: further comprising: outputting the training data for training a model (see Miller at least fig. 1-8 and in particular fig. 1-2, 5-8 and Abstract and see Breed at least fig. 1-64 and in particular fig. 1-8E & par. 238, 251, 345, 353, 357).
Motivation to combine Miller and Breed, in the instant claim, is the same as that in claim 23 above.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MACEEH ANWARI whose telephone number is 571-272-7591. The examiner can normally be reached on 9-9:30.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Angela Ortiz can be reached on 571-272-1206. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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MACEEH . ANWARI
Primary Examiner
Art Unit 3663
/MACEEH ANWARI/ Primary Examiner, Art Unit 3663
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