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
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 6/9/2026 has been entered.
Response to Amendment
In response to applicant’s amendment received on 6/9/2026, all requested changes to the claims have been entered.
Response to Argument
Applicant’s arguments filed on 6/9/2026 have been considered but they are moot in view of the new ground(s) of rejection.
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 of this title, 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 text of those sections of Title 35, U.S. Code not included in this action can be found in a prior Office action.
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.
Claims 1, 12, 13 and 16 are rejected under 35 USC 103 as being unpatentable over Musk et al. (US 2020/0265247).
With respect to claim 1, Musk et al. teach an image sensor configured to output sensor data, wherein the sensor data comprises a sensor image ( para [0018], Fig. 1, vision sensors 101 (such as front-facing camera sensors) configured to capture and output visual image data (sensor images));
a control unit configured to receive the sensor image from the image sensor (para [0012], A system comprising one or more processors coupled to memory is configured to receive image data based on an image captured using a camera of a vehicle. For example, a processor such as an artificial intelligence (AI) processor installed on an autonomous vehicle receives image data from a camera);
execute a feature amount conversion process to convert the sensor image into a specific feature amount , wherein the control unit comprises a convolutional neural network, ,the convolutional neural network is configured to execute the feature amount conversion process , and the specific feature amount includes one of a convolution layer or a pooling layer of the convolutional neural network ( para [0041 and 0044], AI processor 109 executing a deep learning network 107 comprising a convolutional neural network (CNN) with multiple intermediate layers, including convolution and pooling layers, to process image data );
execute a recognition process on the specific feature amount to obtain a recognition process result (para [0044], executing object recognition and parameter inference (e.g., identifying vehicles/pedestrians and determining distance, direction, and velocity vectors) using the deep learning network);
execute a feature amount generation process on the specific feature amount, to generate first feature amount data, wherein the first feature amount data comprises metadata associated with the recognition process result ( para [0048], capturing metadata (the direction, field of view, frame rate, resolution, timestamp) and associating that metadata with captured visual features and recognition results);
a transmission unit configured to transmit the generated first feature amount data by wireless communication (para [0054], results of deep learning analysis at 405 and/or vehicle control parameters used at 409 are transmitted to a computer server, collected data is transmitted wirelessly, for example, via a WiFi or cellular connection).
Musk et al. does not explicitly disclose extracting an intermediate numerical output from a convolution or pooling layer as the designated "specific feature amount." However, it would have been obvious to a PHOSITA at the time of the invention to extract intermediate activation values from a CNN convolution or pooling layer to represent compressed visual feature data, motivated by Musk et al.'s explicit teaching to optimize input bandwidth and computational requirements .
Musk et al. does not explicitly teach generating "first feature amount data" by bundling intermediate convolution/pooling layer activation values together with recognition metadata. However, packaging intermediate CNN feature representations along with their corresponding recognition metadata into a unified data structure is a routine design choice for a PHOSITA to ensure temporal synchronization and contextual tracking across remote processing systems.
Therefore, it would have been obvious to modify Musk et al. al. to obtain the invention as specified in claim 1.
With respect to claim 12, Musk et al. teach that the first feature amount data is information indicating a change amount of the sensor data detected in a monitoring target area. (para [0022], velocities).
With respect to claim 13, Musk et al. teach that the first feature amount data is information indicating distribution data of the sensor data detected in a monitoring target area (para [0045], distances and directions of neighboring objects are predicted and a corresponding drivable space and driving path is identified.).
Claim 16 is rejected as same reason as claim 1 above.
Claim 2 is rejected under 35 USC 103 as being unpatentable over Musk et al. (US 2020/0265247) in view of Rutschman et al. (US 2018/0239948).
Musk et al. teach all the limitations of claim 1 as applied above from which claim 2 respectively depend.
Musk et al. do not teach expressly that transmits the feature amount data to an artificial satellite by the wireless communication.
Rutschman et al. teach transmits the feature amount data to an artificial satellite by the wireless communication. (para [0208], The image data can be processed on-board by a processor 504N (para [0202], neural network comparisons performed by the processor 504N) the parking data (feature amount) can be transmitted to another satellite 500N trailing the satellite 500 in its orbital path).
At the time of effective filing, it would have been obvious to a person of ordinary skill in the art to transmits the feature amount data to an artificial satellite by the wireless communication in the method of Musk et al.
The suggestion/motivation for doing so would have been that it can continuously process a geographical area when one satellite is moving away from the geographical area and other satellite is moving into the geographical area.
Therefore, it would have been obvious to combine Rutschman et al. with Musk et al. to obtain the invention as specified in claim 2.
Claim 3 is rejected under 35 USC 103 as being unpatentable over Musk et al. (US 2020/0265247) in view of Chan (US 2019/0236793).
Musk et al. teach all the limitations of claim 1 as applied above from which claim 3 respectively depend.
Musk et al. do not teach expressly that the control unit is further configured to cause a storage unit to store the first feature amount data, wherein the storage unit excludes storage of the sensor data.
Chan teaches the control unit is further configured to cause a storage unit to store the first feature amount data, wherein the storage unit excludes storage of the sensor data (para [0010], the captured images are discarded from said analytic device after analyzing, and only a structured data set containing an identity and said path of movement of said object across time is retained).
At the time of effective filing, it would have been obvious to a person of ordinary skill in the art to store the first feature amount data, wherein the storage unit excludes storage of the sensor data in the method of Giuffrida et al.
The suggestion/motivation for doing so would have been to save resources in edge computing.
Therefore, it would have been obvious to combine Chan with Musk et al. to obtain the invention as specified in claim 3.
Claims 7-9 are rejected under 35 USC 103 as being unpatentable over Musk et al. (US 2020/0265247) in view of Ricaert et. al. (JP 2019513315, English translation).
With respect to claim 7, Musk et al. teach all the limitations of claim 1 as applied above from which claim 7 respectively depend.
Musk et al. do not teach expressly that perform an image capturing operation again by the image sensor, based on the generated first feature amount data is insufficient data for the recognition process.
Ricaert et. al. teach perform an image capturing operation again by the image sensor, based on the generated first feature amount data is insufficient data for the recognition process (page 36, 2nd para., acquire a second set of images based at least in part on the first subset of images providing an unobstructed view).
At the time of effective filing, it would have been obvious to a person of ordinary skill in the art to capture image again based on the generated first feature amount data is insufficient data in the method of Musk et al.
The suggestion/motivation for doing so would have been to get higher accuracy image analysis result.
Therefore, it would have been obvious to combine Ricaert et. al. with Musk et al. to obtain the invention as specified in claim 7.
With respect to claim 8, Ricaert et. al. teach control to increase a resolution of the image sensor. and perform the image-capturing operation again (page 36, 2nd para., the second of the images The set of is acquired by a second sensor having a higher resolution than the first sensor).
With respect to claim 9, Ricaert et. al. teach perform the image-capturing operation again of a specific area of the sensor image captured by the image sensor (page 36, 2nd para., narrow field of view sensor).
Claims 10 is rejected under 35 USC 103 as being unpatentable over Musk et al. (US 2020/0265247) in view of Chien (US 2020/0126253).
With respect to claim 10, Musk et al. teach all the limitations of claim 1 as applied above from which claim 10 respectively depend.
Musk et al. do not teach that execute processing operation for generation of a second of generating additional feature amount data, based on the generated first feature amount data is insufficient data for the recognition process.
Khisa et al. teach that execute processing operation for generation of a second of generating additional feature amount data, based on the generated first feature amount data is insufficient data for the recognition process (para [0090], Fig. 7, the local host 10 determines that the accuracy rate of this object-recognizing model is insufficient, the learning training is necessary to be executed again, and the local host 10 performs step S411).
At the time of effective filing, it would have been obvious to a person of ordinary skill in the art to generate additional feature amount data when generated first feature amount data is insufficient data in the method of Musk et al.
The suggestion/motivation for doing so would have been to get more accurate data.
Therefore, it would have been obvious to combine Chien with Musk et al. to obtain the invention as specified in claim 10.
Claims 14-15 are rejected under 35 USC 103 as being unpatentable over Musk et al. (US 2020/0265247) in view of Perrier (US 2005/0271266).
With respect to claim 14, Musk et al. teach all the limitations of claim 1 as applied above from which claim 14 respectively depend.
Musk et al. do not teach that the sensor device is installed on one of a mobile object on an ocean.
Perrier teaches that the sensor device is installed on one of a mobile object on an ocean (claim 9, on buoy).
At the time of effective filing, it would have been obvious to a person of ordinary skill in the art to capture image on buoy in the method of Musk et al.
The suggestion/motivation for doing so would have been to capture image from the optimal position.
Therefore, it would have been obvious to combine Perrier with Musk et al. to obtain the invention as specified in claim 14.
With respect to claim 15, Perrier teach that the transmission unit is further configured to transmit the feature amount data to an unmanned aircraft by the wireless communication (para [0060] remote data stream).
Claims 17 is rejected under 35 USC 103 as being unpatentable over Musk et al. (US 2020/0265247) in view of Khisa et al. (“Medium Access Control Protocols for the Internet of Things Based on Unmanned Aerial Vehicles: A Comparative Survey”, Sensors 2020, 20, 5586; doi:10.3390/s20195586).
With respect to claim 17, Musk et al. teach all the limitations of claim 1 as applied above from which claim 17 respectively depend.
Musk et al. do not teach that the transmission unit to transmit at least a piece of the first feature amount data at a specific timing at which the wireless communication to the unmanned aircraft is possible.
Khisa et al. teach that the transmission unit to transmit at least a piece of the first feature amount data at a specific timing at which the wireless communication to the unmanned aircraft is possible (page 11, The reader sends an “ack” packet to the tag if it receives the RN16 packet, which indicates the successful reservation of the slot. Finally, the tag transmits its stored data to the UAV,).
At the time of effective filing, it would have been obvious to a person of ordinary skill in the art to transmit data to UAV when it is possible in the method of Musk et al.
The suggestion/motivation for doing so would have been that to optimize resources..
Therefore, it would have been obvious to combine Perrier with Musk et al. to obtain the invention as specified in claim 17.
Allowable Subject Matter
1. Claim 11 is objected to as being dependent upon a rejected base claim, but would be allowable of rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Randolph Chu whose telephone number is 571-270-1145. The examiner can normally be reached on Monday to Thursday from 7:30 am - 5 pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Bella can be reached on (571) 272-7778.
The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RANDOLPH I CHU/
Primary Examiner, Art Unit 2667
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