DETAILED ACTION
This action is in reply to the amendments and arguments filed May 11th, 2026. Claims 1-5 are currently pending.
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.
Claims 1-4 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without significantly more and the judicial exception is not integrated into a practical application.
Claim 1 is rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without significantly more and the judicial exception is not integrated into a practical application.
Step 1:
The claim 1 is directed to a statutory category of product performing a method.
Step 2a Prong 1:
The method of claim 1 is a mental process. The method of claim 1 merely consists of determine whether recognition result of a recognition target included in the surrounding situation at a first time and the recognition result of the recognition target at a second time which is a time later than the first time coincide, recognition of the recognition target being performed by using the measurement result of the surrounding situation which under its BRI consists of a mental process of comparing pictures for differences. For example, during insurance claims on damaged vehicles it is common for the insurance company to review photographs of the vehicle in question before and after an accident to determine how much the vehicle has been damaged and thus how much to pay to the claim.
Step 2a Prong 2:
Claim 1 recites the additional element of [a] data collection device comprising a processor which is insufficient to integrate the judicial exception into a practical application. The additional element is merely indicating the technological environment the mental process is performed in. This additional element is insufficient to find a practical application because it is a mere indication of technological environment.
Claim 1 recites the additional elements of acquire at least measurement result of a surrounding situation in front of a host vehicle in a travel direction from a surrounding situation sensor which measures the surrounding situation; and perform a process of uploading the measurement result used for the recognition of the recognition target at the first time and the measurement result used for the recognition of the recognition target at the second time to a server in response to determining that the recognition result of the recognition target at the first time and the recognition result of the recognition target at the second time do not coincide, the measurement result of the surrounding situation sensor obtained when the surrounding situation sensor is away from the recognition target corresponds to a measurement result with issues, which is extracted in response to a switching by the recognition result from an incorrect recognition result to a correct recognition result with the movement of the host vehicle which are insufficient to integrate the judicial exception into a practical application. The additional elements are merely insignificant extra solution activity. These additional elements are insufficient to find a practical application because they merely are steps of gathering data and outputting data which are both well-known activities for computers.
Step 2b:
The additional element of [a] data collection device comprising a processor, which was considered mere indication of the technological environment the invention is to be executed in in step 2a, is similarly insufficient for a finding of significantly more because merely indicating the technological environment the mental process is performed in. For example, the MPEP provides that “limitations that amount to merely indicating a field of use or technological environment in which to apply a judicial exception do not amount to significantly more than the exception itself, and cannot integrate a judicial exception into a practical application”. See MPEP 2106.05(h)(iv) “Specifying that the abstract idea of monitoring audit log data relates to transactions or activities that are executed in a computer environment, because this requirement merely limits the claims to the computer field, i.e., to execution on a generic computer, FairWarning v. Iatric Sys., 839 F.3d 1089, 1094-95, 120 USPQ2d 1293, 1295 (Fed. Cir. 2016)”.
The additional element of acquire at least measurement result of a surrounding situation in front of a host vehicle in a travel direction from a surrounding situation sensor which measures the surrounding situation…, the measurement result of the surrounding situation sensor obtained when the surrounding situation sensor is away from the recognition target corresponds to a measurement result with issues, which is extracted in response to a switching by the recognition result from an incorrect recognition result to a correct recognition result with the movement of the host vehicle, which was considered insignificant extra solution activity in step 2a, is similarly insufficient for a finding of significantly more because it is merely insignificant extra solution activity of data gathering. For example, the MPEP provides that extra solution activities that are well-known such as steps of merely gathering data during pre-solution are insufficient for a showing of significantly more. See MPEP 2106.05(g)(ii) “Testing a system for a response, the response being used to determine system malfunction, In re Meyers, 688 F.2d 789, 794; 215 USPQ 193, 196-97 (CCPA 1982)”.
The additional element of perform a process of uploading the measurement result used for the recognition of the recognition target at the first time and the measurement result used for the recognition of the recognition target at the second time to a server in response to determining that the recognition result of the recognition target at the first time and the recognition result of the recognition target at the second time do not coincide, which was considered insignificant extra solution activity in step 2a, is similarly insufficient for a finding of significantly more because it is a well-known, routine, and conventional activity for computers. For example, the MPEP provides that sending and receiving data over a network and electronic recordkeeping are well-understood, routine, and conventional functions of computers. See MPEP 2106.05(d)(i) “Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); but see DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d 1245, 1258, 113 USPQ2d 1097, 1106 (Fed. Cir. 2014) ("Unlike the claims in Ultramercial, the claims at issue here specify how interactions with the Internet are manipulated to yield a desired result‐‐a result that overrides the routine and conventional sequence of events ordinarily triggered by the click of a hyperlink." (emphasis added))”.
Claims 2-4 fall under the same judicial exceptions of claim 1 and are similarly rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e. an abstract idea) without significantly more and the judicial exception is not integrated into a practical application.
Regarding claim 4, claim 4 recites the same mental process of claim 1 but has the statutory category of method.
Regarding claim 2, claim 2 recites the same mental process of claim 1 but with the additional element of the information uploaded to the server also includes time series measurement result including the measurement result used for the recognition of the recognition target at the first time and the measurement result used for the recognition of the recognition target at the second time to the server which does not integrate the mental process into a practical application nor amount to significantly more as this is merely adding to the insignificant extra-solution activity of gather data by defining the data to be gathered and transmitted. See MPEP 2106.05(iii) “Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)”.
Regarding claim 3, claim 3 recites the same mental process of claim 1 but with the additional element of acquire sensor information indicating mounting position and posture of the surrounding situation sensor with respect to the host vehicle and vehicle information indicating speed and yaw rate of the host vehicle; and perform the process of uploading the sensor information and the vehicle information to the server which does not integrate the mental process into a practical application nor amount to significantly more as this is merely adding to the insignificant extra-solution activity of gather data by defining the data to be gathered and transmitted. See MPEP 2106.05(iii) “Selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)”.
Given the above analysis, examiner has determined that claims 1-4 are not eligible subject matter under 101 and are thus rejected.
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 (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 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 1, 4, and 5 are rejected under 35 U.S.C. 103 as being unpatentable over previously cited of record Suzuki et al. (US Pub. No 20130033603 A1), herein after Suzuki as, and further in view of Ehmann; Sebastian (US Pub. No. 20230145472 A1), herein after Ehmann.
Regarding claim 1, Suzuki teaches [a] data collection device comprising a processor configured to: acquire at least measurement result of a surrounding situation in front of a host vehicle in a travel direction from a surrounding situation sensor which measures the surrounding situation (examiner interprets that the measurement result is an image of an object captured by the sensor) (Suzuki: Para. 0078; teaching a camera that photographs the front and sides of a vehicle to generate photographed images of the area around the vehicle); determine whether recognition result of a recognition target included in the surrounding situation at a first time and the recognition result of the recognition target at a second time which is a time later than the first time coincide, recognition of the recognition target being performed by using the measurement result of the surrounding situation; and perform a process of uploading the measurement result used for the recognition of the recognition target at the first time and the measurement result used for the recognition of the recognition target at the second time to a server in response to determining that the recognition result of the recognition target at the first time and the recognition result of the recognition target at the second time do not coincide (Suzuki: Para. 0079, teaching an image recognition unit that applies image recognition to the received image to detect objects in the image such as road facilities including a recognition reliability score of how reliable the recognition is; and Para. 0129, teaching comparing the photographed image to images that were acquired and stored at an earlier time to detect differences between the images to detect abnormalities in the environment and uploading the photographed image to a server when an abnormality in the image is detected).
Suzuki is silent to the measurement result of the surrounding situation sensor obtained when the surrounding situation sensor is away from the recognition target corresponds to a measurement result with issues, which is extracted in response to a switching by the recognition result from an incorrect recognition result to a correct recognition result with the movement of the host vehicle.
In a similar field, Ehmann teaches the measurement result of the surrounding situation sensor obtained when the surrounding situation sensor is away from the recognition target corresponds to a measurement result with issues, which is extracted in response to a switching by the recognition result from an incorrect recognition result to a correct recognition result with the movement of the host vehicle (Ehmann: Para. 0038, teaching determining how far an object is from a camera on a vehicle and determining the image collected is inaccurate if the object is too far away; and Para. 0089, teaching an example where a camera is collecting images as it approaches an object and using the images that are from a closer distance that are more accurate for navigation purposes) for the benefit of improving the accuracy of the navigation and response of autonomous and semi-autonomous vehicles.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the image abnormality detection and reporting to a server from Suzuki to determine that images that are taken far away from the vehicle are less accurate than images taken closer to a subject and using the close-up images for navigation and abnormality detection, as taught by Ehmann, for the benefit of improving the accuracy of the navigation and response of autonomous and semi-autonomous vehicles.
Regarding claim 4, Suzuki teaches [a] data collection method comprising: acquiring at least measurement result of a surrounding situation in front of a host vehicle in a travel direction from a surrounding situation sensor which measures the surrounding situation (examiner interprets that the measurement result is an image of an object captured by the sensor) (Suzuki: Para. 0078; teaching a camera that photographs the front and sides of a vehicle to generate photographed images of the area around the vehicle); determining whether recognition result of a recognition target included in the surrounding situation at a first time and the recognition result of the recognition target at a second time which is a time later than the first time coincide, recognition of the recognition target being performed by using the measurement result of the surrounding situation; and performing a process of uploading the measurement result used for the recognition of the recognition target at the first time and the measurement result used for the recognition of the recognition target at the second time to a server in response to determining that the recognition result of the recognition target at the first time and the recognition result of the recognition target at the second time do not coincide (Suzuki: Para. 0079, teaching an image recognition unit that applies image recognition to the received image to detect objects in the image such as road facilities including a recognition reliability score of how reliable the recognition is; and Para. 0129, teaching comparing the photographed image to images that were acquired and stored at an earlier time to detect differences between the images to detect abnormalities in the environment and uploading the photographed image to a server when an abnormality in the image is detected).
Suzuki is silent to the measurement result of the surrounding situation sensor obtained when the surrounding situation sensor is away from the recognition target corresponds to a measurement result with issues, which is extracted in response to a switching by the recognition result from an incorrect recognition result to a correct recognition result with the movement of the host vehicle.
In a similar field, Ehmann teaches the measurement result of the surrounding situation sensor obtained when the surrounding situation sensor is away from the recognition target corresponds to a measurement result with issues, which is extracted in response to a switching by the recognition result from an incorrect recognition result to a correct recognition result with the movement of the host vehicle (Ehmann: Para. 0038, teaching determining how far an object is from a camera on a vehicle and determining the image collected is inaccurate if the object is too far away; and Para. 0089, teaching an example where a camera is collecting images as it approaches an object and using the images that are from a closer distance that are more accurate for navigation purposes) for the benefit of improving the accuracy of the navigation and response of autonomous and semi-autonomous vehicles.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the image abnormality detection and reporting to a server from Suzuki to determine that images that are taken far away from the vehicle are less accurate than images taken closer to a subject and using the close-up images for navigation and abnormality detection, as taught by Ehmann, for the benefit of improving the accuracy of the navigation and response of autonomous and semi-autonomous vehicles.
Regarding claim 5, Suzuki teaches [a] non-transitory recording medium having recorded thereon a computer program for causing a processor to perform a process comprising (Suzuki: Para. 0147, teaching the use of flash memory to store programs to perform the steps of the invention): acquiring at least measurement result of a surrounding situation in front of a host vehicle in a travel direction from a surrounding situation sensor which measures the surrounding situation (examiner interprets that the measurement result is an image of an object captured by the sensor) (Suzuki: Para. 0078; teaching a camera that photographs the front and sides of a vehicle to generate photographed images of the area around the vehicle); determining whether recognition result of a recognition target included in the surrounding situation at a first time and the recognition result of the recognition target at a second time which is a time later than the first time coincide, recognition of the recognition target being performed by using the measurement result of the surrounding situation; and performing a process of uploading the measurement result used for the recognition of the recognition target at the first time and the measurement result used for the recognition of the recognition target at the second time to a server in response to determining that the recognition result of the recognition target at the first time and the recognition result of the recognition target at the second time do not coincide (Suzuki: Para. 0079, teaching an image recognition unit that applies image recognition to the received image to detect objects in the image such as road facilities including a recognition reliability score of how reliable the recognition is; and Para. 0129, teaching comparing the photographed image to images that were acquired and stored at an earlier time to detect differences between the images to detect abnormalities in the environment and uploading the photographed image to a server when an abnormality in the image is detected).
Suzuki is silent to the measurement result of the surrounding situation sensor obtained when the surrounding situation sensor is away from the recognition target corresponds to a measurement result with issues, which is extracted in response to a switching by the recognition result from an incorrect recognition result to a correct recognition result with the movement of the host vehicle.
In a similar field, Ehmann teaches the measurement result of the surrounding situation sensor obtained when the surrounding situation sensor is away from the recognition target corresponds to a measurement result with issues, which is extracted in response to a switching by the recognition result from an incorrect recognition result to a correct recognition result with the movement of the host vehicle (Ehmann: Para. 0038, teaching determining how far an object is from a camera on a vehicle and determining the image collected is inaccurate if the object is too far away; and Para. 0089, teaching an example where a camera is collecting images as it approaches an object and using the images that are from a closer distance that are more accurate for navigation purposes) for the benefit of improving the accuracy of the navigation and response of autonomous and semi-autonomous vehicles.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the image abnormality detection and reporting to a server from Suzuki to determine that images that are taken far away from the vehicle are less accurate than images taken closer to a subject and using the close-up images for navigation and abnormality detection, as taught by Ehmann, for the benefit of improving the accuracy of the navigation and response of autonomous and semi-autonomous vehicles.
Claim 2 is rejected under 35 U.S.C. 103 as being unpatentable over Suzuki in view of Ehmann as applied to claim 1 above, and further in view of previously cited of record Li et al. (US Pub. No. 20220279111 A1), herein after Li.
Regarding claim 2, Suzuki and Ehmann remain as applied as in claim 1, however they are silent to [t]he data collection device according to claim 1, wherein the processor is further configured to perform the process of uploading time series measurement result including the measurement result used for the recognition of the recognition target at the first time and the measurement result used for the recognition of the recognition target at the second time to the server.
In a similar field, Li teaches [t]he data collection device according to claim 1, wherein the processor is further configured to perform the process of uploading time series measurement result including the measurement result used for the recognition of the recognition target at the first time and the measurement result used for the recognition of the recognition target at the second time to the server (Li: Para. 0063, teaching periodically obtaining and uploading to a server images from the environment within a preset time period) for the benefit of providing successive images for comparison in case there is an issue with the original image that is uploaded.
It would have been obvious to one ordinarily skilled in the art before the effective filing date of the applicant’s claimed invention to modify the image abnormality detection and reporting to a server from Suzuki in view of Ehmann to upload multiple images taken by the camera over a period of time, as taught by Li, for the benefit of providing successive images for comparison in case there is an issue with the original image that is uploaded.
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Suzuki in view of Ehmann as applied to claim 1 above, and further in view of previously cited of record Kim; Cheolseung (US Pub. No. 20200012295 A1), herein after Kim.
Regarding claim 3, Suzuki and Ehmann remain as applied as in claim 1 and Suzuki goes on to further teach [t]he data collection device according to claim 1, wherein the processor is further configured to: acquire sensor information indicating mounting position and posture of the surrounding situation sensor with respect to the host vehicle and vehicle information indicating speed (Suzuki: Para. 0078; teaching that the camera is mounted to the vehicle at an angle to photograph the front and sides of the vehicle to generate photographed images of the area around the vehicle; and Para. 0093, teaching that the photographed images are transmitted to the server alongside transmission image information on the vehicle including its speed and location) and perform the process of uploading the sensor information and the vehicle information to the server (Suzuki: Para. 0076, teaching that the transmitted image information is uploaded to the server).
Suzuki in view of Ehmann are silent to the vehicle information comprises the vehicle’s yaw rate.
In a similar field, Kim teaches acquiring sensor information indicating… vehicle information indicating speed and yaw rate of the host vehicle (Kim: Para. 0184 and 0186, teaching that determining a vehicle's location is done using an image captured by a camera and data from a sensing unit including the vehicle's motion, yaw, roll, pitch, speed, and other relevant information) for the benefit of accurately determining the vehicle’s position and orientation in relation to the imaged environment.
It would have been obvious to one ordinarily skilled in the art before the filing of the application to modify the image abnormality detection and reporting to a server from Suzuki in view of Ehmann to include in the vehicle information the vehicle’s yaw rate, as taught by Kim, for the benefit of accurately determining the vehicle’s position and orientation in relation to the imaged environment.
Response to Arguments
Applicant's arguments filed May 11th, 2026 have been fully considered but they are not persuasive.
Applicant's arguments filed May 11th, 2026 with respect to the 101 rejection of claims 1-4 have been fully considered but they are not persuasive.
Applicant contends (see page 6 line 33 through page 8 line 26, filed May 11th, 2026) that the newly presented amendments render independent claims 1 and 4 patent eligible under 101 as the obtaining a measurement result and comparison thereto being done as the vehicle moves provides a practical applicant and showing of significantly more to the identified invention. The examiner respectfully disagrees. The examiner notes that the newly presented limitations are presented in a manner that is considered insignificant extra solution activity. In particular, the language the claims use includes “the measurement result of the surrounding situation sensor obtained when the surrounding situation sensor is away” and “which is extracted in response to a switching by the recognition result from” (emphasis added) indicates that these limitations are pre-solution activities that are performed before the invention takes place and are merely describing the type of data being compared and uploaded during the steps of the invention.
Applicant’s arguments, see page 9, filed May 11th, 2026, with respect to the rejection(s) of claim(s) 1, 4, and 5 under 102(a)(1) in view of Suzuki have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made under 103 in view of Suzuki in further view of Ehmann.
Conclusion
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.
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/A.K.M./Examiner, Art Unit 3663
/ANGELA Y ORTIZ/Supervisory Patent Examiner, Art Unit 3663
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