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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 07/22/2026 has been entered.
Response to Amendment
The Amendment filed 07/22/2026 has been entered. Claims 12, 19, 20 and 29 were canceled and claims 38-39 are new. Claims 1-11, 13-18 and 21-28 and 30-39 are now pending in the application.
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.
Claims 1, 3, 11, 13, 15, 18, 28, 31, 34-35 and 37-38 are rejected under 35 U.S.C. 103 as being unpatentable over Chandra et al. (US 20020138582 A1 hereinafter Chandra) in view of Laganiere et al. (US 20120195363 A1) hereinafter Laganiere and Boenisch et al. (US 20150301803 A1) hereinafter Boenisch.
As to independent claim 1, Chandra teaches method of identifying desired information comprising:
determining a coarse filter based on a rule; [a rule has a coarse filter ¶583-584 "Each rule comprises an association with one event through a coarse-grain filter, a fine-grain filter that has one or more conditions, zero or more constants, one or more actions or handler"]
coarse filtering data with the coarse filter [¶545, ¶573 a coarse filter to filter based on event header Fig. 17B 1712 ¶584 "coarse-grain filters carry out filtering only on a header portion of an event message."]
determining a fine filter based on the rule; and [rule includes a fine filter ¶583-585 "Rule conditions may be created as coarse-grain filters or fine-grain filters"]
fine filtering the filtered data with the fine filter; [The coarse filter first selects event messages based on basic criteria in the message header. Then, the fine filter further examines these pre-selected messages in detail, applying more specific conditions that must all be met for the associated action to trigger ¶602 "If the event message matches one of the coarse-grain filters, then in block 1742, one or more rules with fine-grain filters are retrieved. Rule constants are extracted from the rules in block 1746. In block 1748, the fine-grain filters are applied to the event message"]
Chandra does not specifically teach coarse filtering data received in real-time with the coarse filter, defining filtered data; and wherein said coarse filtering is remote from said fine filtering.
However, Laganiere teaches coarse filtering data received in real-time with the coarse filter, defining filtered data; and [streams data (real-time) at 30FPS with processing ¶6, ¶34 "pre-processing reduces the bandwidth requirement for transmitting the video data by an amount that is sufficient to result in a data stream that requires an amount of bandwidth below a bandwidth limit of WAN "]
wherein said coarse filtering is remote from said fine filtering. [first video analytics (filtering) at source then sends over WAN for second processing (remote) ¶8 "using video analytics other than a data compression process, pre-processing the video data at the source end to reduce the bandwidth requirement for transmitting the video data to below a bandwidth limit of a Wide Area Network (WAN) over which the video data is to be transmitted; transmitting the pre-processed video data to a central server via the WAN; performing other video analytics processing of the pre-processed video data at other than the source end"]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the filtering system by Chandra by incorporating the coarse filtering data received in real-time with the coarse filter, defining filtered data; and wherein said coarse filtering is remote from said fine filtering disclosed by Laganiere because both techniques address the same field of detection analysis and by incorporating Laganiere into Chandra provides improved communications for remote systems can operate sufficiently [Laganiere ¶6]
Chandra and Laganiere do not specifically teach the filtered data are signed.
However, Boenisch teaches the filtered data are signed. [signs the filtered vibration data for example with SSL ¶20, ¶37-38 "data being signed by a trusted source). Secure and trusted connections can be set up using standard methods from cryptography for encrypting signing data including key negotiation based on asymmetric key cryptography"]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the filtering system by Chandra and Laganiere by incorporating the filtered data are signed disclosed by Boenisch because all techniques address the same field of detection analysis and by incorporating Boenisch into Chandra and Laganiere provides more secure and trusted communications better authenticating the source of data [Boenisch ¶20-21]
As to dependent claim 3, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch further teach wherein the coarse filter comprises a feature of interest. [Laganiere regions and events of interest in video ¶38]
As to dependent claim 11, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch further teach deleting all filtered sensor data. [Chanda deletes actions ¶590]
As to dependent claim 13, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch further teach compressing the desired information. [Laganiere compression ¶ 38]
As to dependent claim 15, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch further teach encoding the desired information. [Laganiere encoding ¶3]
As to independent claim 18, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch further teach System for identifying desired information comprising a processor configured for the method of claim 1. [Chandra system and processor ¶191-192]
As to dependent claim 28, the rejection of claim 34 is incorporated Chandra, Laganiere and Boenisch further teach wherein said receiving comprises an actor. [Chandra user defined rules ¶536]
As to independent claim 31, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch further teach computer-readable medium configured for storing instructions configured for the method of claim 1. [Chandra medium and computer program ¶815]
As to independent claim 34, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch further teach further comprising, prior to said determining, receiving the rule. [Chandra user defined rules ¶536]
As to independent claim 35, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch further teach further comprising tuning said coarse filtering and said fine filtering. [Chandra modify the rules that control filtering (tune) ¶581]
As to independent claim 37, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch further teach further comprising transmitting the coarse-filtered sensor data to a second filter module. [Laganiere first video analytics (filtering) at source then sends over WAN for second processing (remote) ¶8 "using video analytics other than a data compression process, pre-processing the video data at the source end to reduce the bandwidth requirement for transmitting the video data to below a bandwidth limit of a Wide Area Network (WAN) over which the video data is to be transmitted; transmitting the pre-processed video data to a central server via the WAN; performing other video analytics processing of the pre-processed video data at other than the source end"]
As to independent claim 38, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch further teach wherein the data are encrypted in place before said coarse filtering. [Boenisch encrypted prior to transmission (claim 2 ¶38)]
Claims 2, 14, 24 and 36 are rejected under 35 U.S.C. 103 as being unpatentable over Chandra in view of Laganiere and Boenisch as applied to the rejection of claim 1 above, and further in view of Darche et al. (US 10587483 B1 hereinafter Darche)
As to dependent claim 2, the combination of Chandra, Laganiere and Boenisch teach all the limitations of claim 1 that is incorporated.
Chandra, Laganiere and Boenisch do not specifically teach encrypting in place the filtered sensor data and defining encrypted sensor data.
However, Darche teaches encrypting in place the filtered sensor data and defining encrypted sensor data. [encrypting Col. 7 ln. 20-27 "The sensor computer 106 compresses the current file, performs any other operations such as encrypting the current file"]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the encrypting in place the filtered sensor data and defining encrypted sensor data disclosed by Darche because all techniques address the same field of data analysis and by incorporating Darche into Chandra, Laganiere and Boenisch provide more effective collection of data and filters deployed [Darche Col. 3 ln. 1-15]
As to dependent claim 14, the combination of Chandra, Laganiere and Boenisch teach all the limitations of claim 1 that is incorporated.
Chandra, Laganiere and Boenisch do not specifically teach encrypting the desired information.
However, Darche teaches encrypting the desired information. [encrypting Col. 7 ln. 20-27 "The sensor computer 106 compresses the current file, performs any other operations such as encrypting the current file"]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the encrypting the desired information disclosed by Darche because all techniques address the same field of data analysis and by incorporating Darche into Chandra, Laganiere and Boenisch provide more effective collection of data and filters deployed [Darche Col. 3 ln. 1-15]
As to dependent claim 24, the combination of Chandra, Laganiere, Boenisch and Darche teach all the limitations of claim 2 that is incorporated. Chandra, Laganiere, Boenisch and Darche further teach storing the encrypted sensor data. [Darche encrypting Col. 7 ln. 20-27 "The sensor computer 106 compresses the current file, performs any other operations such as encrypting the current file"]
As to dependent claim 36, the combination of Chandra, Laganiere and Boenisch teach all the limitations of claim 1 that is incorporated.
Chandra, Laganiere and Boenisch do not specifically teach further comprising transmitting the coarse filter to a filter module.
However, Darche teaches further comprising transmitting the coarse filter to a filter module. [sends filters to a sensor computer Col. 3 ln. 34-46 “ provide packet capture filters to each of the sensor computer”]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the further comprising transmitting the coarse filter to a filter module disclosed by Darche because all techniques address the same field of data analysis and by incorporating Darche into Chandra, Laganiere and Boenisch provide more effective collection of data and filters deployed [Darche Col. 3 ln. 1-15]
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Chandra, Laganiere and Boenisch, as applied to the rejection of claim 3 above, and further in view of Izenson et al. (US 20210191926 A1 hereinafter Izenson)
As to dependent claim 4, the combination of Chandra, Laganiere and Boenisch teach all the limitations of claim 3 that is incorporated.
Chandra, Laganiere and Boenisch do not specifically teach wherein the feature comprises a height of a subject.
However, Izenson teaches wherein the feature comprises a height of a subject. [Izenson height ¶23]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein the feature comprises a height of a subject disclosed by Izenson because all techniques address the same field of data analysis and by incorporating Izenson into Chandra, Laganiere and Boenisch provides user with more effective or consistent results preventing wastes of time [Izenson ¶2-3]
Claims 5-7, 9-10, 16-17, 21-23, 25-27, 30 and 32-33 are rejected under 35 U.S.C. 103 as being unpatentable over Chandra, Laganiere and Boenisch as applied to the rejection of claim 3 above, and further in view of Boykin.
As to dependent claim 5, the rejection of claim 3 is incorporated Chandra, Laganiere and Boenisch do not specifically teach wherein the feature comprises a model of a vehicle.
However, Boykin teaches wherein the feature comprises a model of a vehicle. [Boykin features for vehicle model ¶67 "vehicle identification parameters/characteristics (makes, models, colors, etc.)"]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein the feature comprises a model of a vehicle by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9]
As to dependent claim 6, the rejection of claim 3 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach wherein the feature comprises a color of a vehicle.
However, Boykin teaches wherein the feature comprises a color of a vehicle. [Boykin features for vehicle color ¶67 "vehicle identification parameters/characteristics (makes, models, colors, etc.)"]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein the feature comprises a color of a vehicle by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 7, the rejection of claim 28 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach wherein the actor comprises a law enforcement agency.
However, Boykin teaches wherein the actor comprises a law enforcement agency. [Boykin law enforcement agencies, applications and offices ¶67-68 ]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein the actor comprises a law enforcement agency by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 9, the rejection of claim 1 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach wherein the desired information comprises an identity of a subject. [Boykin recognition of people ¶72 including facial recognition ¶93]
However, Boykin teaches wherein the desired information comprises an identity of a subject. [Boykin recognition of people ¶72 including facial recognition ¶93]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein the desired information comprises an identity of a subject by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 10, the rejection of claim 1 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach wherein the desired information comprises a license plate number.
However, Boykin teaches wherein the desired information comprises a license plate number. [Boykin ¶174 "analyzing the captured visual data, processor may detect the presence of (suspect's) vehicle 3407 and various characteristics thereof (e.g., vehicle type, make, model, color, license plate number, etc.)"]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein the desired information comprises a license plate number by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 16, the rejection of claim 1 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach wherein said coarse filtering is configured for determining human subjects.
However, Boykin teaches wherein said coarse filtering is configured for determining human subjects. [Boykin people Fig. 4 ¶72 " FIG. 4 depicts the recognition of multiple “people” shapes (shown in bounding boxes) 41 "]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein said coarse filtering is configured for determining human subjects by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 17, the rejection of claim 1 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach wherein said coarse filtering is configured for determining license plate numbers.
However, Boykin teaches wherein said coarse filtering is configured for determining license plate numbers. [Boykin filters images for license plate ¶59/ ¶69]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein said coarse filtering is configured for determining license plate numbers by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 21, the rejection of claim 1 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach transmitting the desired information.
However, Boykin teaches transmitting the desired information. [Boykin remote storage and analysis transmits data ¶66, ¶70]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the transmitting the desired information by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 22, the rejection of claim 28 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach confirming an authorization of the actor.
However, Boykin teaches confirming an authorization of the actor. [Boykin authorized users ¶94]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the confirming an authorization of the actor by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 23, the rejection of claim 1 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach securing said transmitting.
However, Boykin teaches securing said transmitting. [Boykin authorized users and RTSP has security ¶93]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the securing said transmitting by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 25, the rejection of claim 1 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach storing the desired information.
However, Boykin teaches storing the desired information. [Boykin remote storage ¶66, ¶70]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the storing the desired information by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 26, the rejection of claim 1 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach wherein said coarse filtering occurs on an autonomous vehicle and said fine filtering occurs in a cloud.
However, Boykin teaches wherein said coarse filtering occurs on an autonomous vehicle and said fine filtering occurs in a cloud. [Boykin cloud ¶66, autonomous ¶90]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein said coarse filtering occurs on an autonomous vehicle and said fine filtering occurs in a cloud by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 27, the rejection of claim 1 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach wherein the data comprise a location of the collection device.
However, Boykin teaches wherein the data comprise a location of the collection device. [Boykin GPS metadata (location) ¶59]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein the data comprise a location of the collection device by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to dependent claim 30, the rejection of claim 1 is incorporated. Chandra, Laganiere and Boenisch do not specifically teach wherein the collection device is fixed relative to an autonomous vehicle.
However, Boykin teaches wherein the collection device is fixed relative to an autonomous vehicle. [Boykin a collection device, such as a camera or microphone mounted on the docking station (which can be considered an autonomous vehicle when referring to police vehicles equipped with advanced technological capabilities), is fixed relative to the autonomous vehicle it is attached to ¶10-12]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein the collection device is fixed relative to an autonomous vehicle by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to independent claim 32, the rejection of claim 1 is incorporated Chandra, Laganiere and Boenisch do not specifically teach further comprising, prior to said fine filtering, receiving the coarse-filtered sensor data.
However, Boykin teaches further comprising, prior to said fine filtering, receiving the coarse-filtered sensor data. [Boykin remotely a collecting device such as Fig.1 vehicle computer 12 and server 48 device do filtering for tiered or second level filtering (multiple object recognition with different neural nets) ¶77-78 "the analytics for recognition and detection of the designated content is distributed among the vehicle 10 computer 12 and one or more remote computers (e.g. the server 15 in the police station 14)."…"use a separate neural network to instantly achieve multiple object recognition as described herein"]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the further comprising, prior to said fine filtering, receiving the coarse-filtered sensor data by Boykin because all techniques address the same field of data analysis and by incorporating Boykin into Chandra, Laganiere and Boenisch saves the time of operators of sensors by automating tasks in simple ways [Boykin ¶8-9].
As to independent claim 33, the rejection of claim 32 is incorporated Chandra, Vitek and Boykin further teach comprising securing said receiving. [Boykin authorized users and RTSP has security ¶93]
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Chandra, Laganiere and Boenisch, as applied to the rejection of claim 1 above, and further in view of Muetzel et al. (US 20140376778 A1 hereinafter Muetzel).
As to dependent claim 8, the combination of Chandra, Laganiere and Boenisch teach all the limitations of claim 1 that is incorporated.
Chandra, Laganiere and Boenisch do not specifically teach wherein the rule is based on a warrant
However, Muetzel teaches wherein the rule is based on a warrant [analysis server processes data by doing extractions (filtering) based on a warrant ¶35 “Based on the extracted license plate string, analysis server 150 may determine if the mini-van 320 is, for example, a stolen vehicle, subject to a search warrant, subject to emergency recall, registered to a person or company subject to a search warrant or police investigation, or more”]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the wherein the rule is based on a warrant disclosed by Muetzel because all techniques address the same field of data analysis and by incorporating Muetzel into Chandra, Laganiere and Boenisch helps users better identify objects and locations without intervention or automatically [Muetzel ¶33]
Claim 39 is rejected under 35 U.S.C. 103 as being unpatentable over Chandra, Laganiere and Boenisch, as applied to the rejection of claim 1 above, and further in view of Patel et al. (US 20200159891 A1) hereinafter Patel.
As to dependent claim 39, the combination of Chandra, Laganiere and Boenisch teach all the limitations of claim 1 that is incorporated.
Chandra, Laganiere and Boenisch do not specifically teach tracking a chain of custody of the data from collecting the data through said fine filtering.
However, Patel teaches tracking a chain of custody of the data from collecting the data through said fine filtering. [provides a blockchain for tracking signatures (custody) ¶134-135 "The private key is kept secret and used to digitally sign messages sent to other blockchain participants. The signature is included in the message so that the recipient can verify using the public key of the sender. This way, the recipient can be sure that only the sender could have sent this message."]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the sensor systems disclosed by Chandra, Laganiere and Boenisch by incorporating the tracking a chain of custody of the data from collecting the data through said fine filtering disclosed by Patel because all techniques address the same field of data analysis and by incorporating Patel into Chandra, Laganiere and Boenisch improves protection of user data reducing security breaches [Patel ¶2].
Response to Arguments
Applicant's arguments filed 07/22/2026. In the remark, applicant argues that:
Chandra and Vitek fail to teach “the filtered data are signed.” As recited by amended claim 1.
As to point (1) Applicant’s arguments with respect to claims have been considered but are moot in view of a new ground of rejection made under 35 U.S.C. 103 as being unpatentable over Chandra in view of Laganiere and Boenisch as set forth above.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
Sun et al. (US 20190171843 A1) teaches in place encryption for sensitive information (see ¶16).
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 U.S.P.Q. 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 U.S.P.Q. 275, 277 (C.C.P.A. 1968)).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Beau Spratt whose telephone number is 571 272 9919. The examiner can normally be reached 8:30am to 5:00pm (PST).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jennifer Welch can be reached at 571 272 7212. The fax phone number for the organization where this application or proceeding is assigned is 571 483 7388.
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/BEAU D SPRATT/Primary Examiner, Art Unit 2143
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