DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
1. This action is in response to the communication filed on July 25, 2024. Claims 1-20 were originally received for consideration. No preliminary amendments for the claims have been received.
2. Claims 1-20 are currently pending consideration.
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 was made.shall not be negated by the manner in which the invention
3. Claim(s) 1,2, 7, and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (“Trust Model of Wireless Sensor Networks and Its Application in Data Fusion”) in view of Hamza et al. (U.S. Patent Pub. No. US 2007/0297696).
Regarding claim 1, Chen discloses:
A sensor platform comprising:
at least one sensor configured to acquire sensor data about an environment in which the sensor platform is located (Section 3, page 3: the sensor nodes collect data and transmit it to the relay nodes);
a wireless communication interface (section 3, page 3: wireless sensor nodes collect data and transmit it to the relay nodes); and
a computing platform configured to control the sensor platform (page 2: computation and storage of trust values are all located on the decision objects) to acquire first sensor data using the at least one sensor (Section 3, page 3, page 5: sensor nodes collect data),
acquire second sensor data, via the wireless communication interface, from at least one other sensor platform (Section 3, page 3: senor nodes collect data and transmit it to relay nodes and relay nodes carry out data fusion), and
the first sensor data and includes or excludes the second sensor data based on a level of trust assigned to the at least one other sensor platform and a trust setting of the sensor platform (Section 1, page 2, paragraph 4: using the trust model and the given threshold, we can exclude the abnormal data from the fused data; Section 3.2.2:, pages 7-8: trust list is updated according to the comprehensive trust of each sensor node; if the comprehensive trust is lower than the anomaly threshold, the sensor node is considered to be credible; Section 4, pages 8-9: in data fusion, sensor nodes need to satisfy two features, one is that they are included in the trust list).
Chan does not explicitly disclose displaying, via a user interface, a fused sensor view. In an analogous art, Hamza discloses a system and method for fusing sensor data and a synthetic data to form an integrated image (see Abstract). Hamza discloses a system for presenting the integrated imagine (paragraph 0020). The system combines sensor data received from more than one sensor (paragraph 0012). The system then combines the sensor data and synthetic view into an integrated image and the resulting image may be provided on a display providing a vehicle operator with a 3D view of the external environment of a vehicle (paragraphs 0053-0054). The sensor function may be applied selectively in some regions and excluded in some others to limit the noise in the fused image (paragraph 0028). The weights may be tuned based upon user choice of setting to weigh either source of information (paragraph 0012). It would have been obvious to one of ordinary skill in the art to use the display and fusing view of Hamza in the system of Chen to allow the user to interpret the fused information instead of trying to analyze multiple different sensor inputs (Hamza: paragraph 0054).
Claim 2 is rejected as applied above in rejecting claim 1. Furthermore, Mishra discloses:
The sensor platform of claim 1, wherein the second sensor data includes a first portion from a first other sensor platform assigned a first level of trust, and a second portion from a second other sensor platform assigned a second level of trust that is a higher trust level than the first level of trust (section 3, page 3: the trust value of the sensor nodes is calculated in the cluster heads); and
wherein, the computing platform is configured to:
based on the trust setting of the sensor platform being a first trust setting, display the fused sensor view including the first and second portions of the second sensor data (Section 3.2.2:, pages 7-8: trust list is updated according to the comprehensive trust of each sensor node; if the comprehensive trust is lower than the anomaly threshold, the sensor node is considered to be credible; Section 4, pages 8-9: in data fusion, sensor nodes need to satisfy two features, one is that they are included in the trust list), or
based on the trust setting of the sensor platform being a second trust setting, higher than the first trust setting, display the fused sensor view including the second portion of the second sensor data and excluding the first portion of the second sensor data (Section 3.2.2:, pages 7-8: trust list is updated according to the comprehensive trust of each sensor node; if the comprehensive trust is lower than the anomaly threshold, the sensor node is considered to be credible; Section 4, pages 8-9: in data fusion, sensor nodes need to satisfy two features, one is that they are included in the trust list).
Chan does not explicitly disclose displaying, via a user interface, a fused sensor view. In an analogous art, Hamza discloses a system and method for fusing sensor data and a synthetic data to form an integrated image (see Abstract). Hamza discloses a system for presenting the integrated imagine (paragraph 0020). The system combines sensor data received from more than one sensor (paragraph 0012). The system then combines the sensor data and synthetic view into an integrated image and the resulting image may be provided on a display providing a vehicle operator with a 3D view of the external environment of a vehicle (paragraphs 0053-0054). The sensor function may be applied selectively in some regions and excluded in some others to limit the noise in the fused image (paragraph 0028). The weights may be tuned based upon user choice of setting to weigh either source of information (paragraph 0012). It would have been obvious to one of ordinary skill in the art to use the display and fusing view of Hamza in the system of Chen to allow the user to interpret the fused information instead of trying to analyze multiple different sensor inputs (Hamza: paragraph 0054).
Claim 7 is rejected as applied above in rejecting claim 2. Furthermore, Chen discloses:
The sensor platform of claim 2, wherein the computing platform is configured to temporarily assign the first level of trust to the second other sensor platform based on location information about the second other sensor platform (Section 1, page 2: trust model contains a data trust which is made up of real-time data, regional data (location) and historical data).
Claim 9 is rejected as applied above in rejecting claim 1. Furthermore, Hamza discloses:
The sensor platform of claim 1, wherein the computing platform is configured to change the trust setting based on a user input received via the user interface (paragraphs 0012, 0054: may be tuned based upon user choice of setting to weigh either source of information).
4. Claim(s) 3-6, and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (“Trust Model of Wireless Sensor Networks and Its Application in Data Fusion”) in view of Hamza et al. (U.S. Patent Pub. No. US 2007/0297696) further in view of Mishra (U.S. Patent Pub. No. US 2020/0106601).
Claim 3 is rejected as applied above in rejecting claim 2. Furthermore, the combination of Chen and Hamza does not explicitly disclose wherein the first portion of the second sensor data includes a first identifier that identifies the first other sensor platform, and the second portion of the second sensor data includes a second identifier that identifies the second other sensor platform. In an analogous art, Mishra discloses that the sensor data can be identified by a device identifier, device ID, identifying the senor or device issuing the data (paragraph 0003). The device generates a message which includes a device identifier, a network identifier of the service platform which forwards the encrypted sensor data to a blockchain (paragraph 0147). It would have been obvious to one of ordinary skill in the art to using Mishra’s blockchain-based storage of sensor data to store the data fused results of Chen-Hamza to ensure the authenticity and integrity of sensor data (Mishra: paragraph 0011).
Claim 4 is rejected as applied above in rejecting claim 3. Furthermore, the combination of Chen and Hamza do not explicitly disclose wherein the computing platform includes a computer-readable storage medium that stores information linking the first level of trust to the first identifier and the second level of trust to the second identifier. Chen discloses assigning trust per node (Section 3.2.2:, pages 7-8) but does not disclose linking them to identifiers. In an analogous art, Mishra discloses that sensor data is sent in a message to a service platform and then forwarded to a blockchain (paragraph 0147) and that the data is linked to a sensor by way of a device identifier (paragraphs 0001-0003). It would have been obvious to one of ordinary skill in the art to using Mishra’s blockchain-based storage of sensor data to store the data fused results of Chen-Hamza to ensure the authenticity and integrity of sensor data (Mishra: paragraph 0011).
Claim 5 is rejected as applied above in rejecting claim 3. Furthermore, the combination of Chen and Hamza does not explicitly disclose wherein the second sensor data includes a sensor ledger in which the first portion of the second sensor data is cryptographically linked to the first identifier, and the second portion of the second sensor data is cryptographically linked to the second identifier and to the first portion of the second sensor data. In an analogous art, Mishra discloses that the sensor data can be identified by a device identifier, device ID, identifying the senor or device issuing the data (paragraph 0003). The device generates a message which includes a device identifier, a network identifier of the service platform which forwards the encrypted sensor data to a blockchain (paragraph 0147). It would have been obvious to one of ordinary skill in the art to using Mishra’s blockchain-based storage of sensor data to store the data fused results of Chen-Hamza to ensure the authenticity and integrity of sensor data (Mishra: paragraph 0011).
Claim 6 is rejected as applied above in rejecting claim 5. Furthermore, the combination of Chen and Hamza do not explicitly disclose wherein to cryptographically link the second portion of the second sensor data to the first portion of the second sensor data, a ledger entry including the second portion of the second sensor data includes a cryptographic hash of the first portion of the second sensor data. In an analogous art, Mishra discloses hashing the first decrypted data and storing the hashed data int eh blockchain together with the first device identifier (paragraphs 0016, 0076). It would have been obvious to one of ordinary skill in the art to using Mishra’s blockchain-based storage of sensor data to store the data fused results of Chen-Hamza to ensure the authenticity and integrity of sensor data (Mishra: paragraph 0011).
Claim 8 is rejected as applied above in rejecting claim 1. Furthermore, the combination of Chen and Hamza do not explicitly disclose wherein the computing platform is configured to add the first sensor data as a ledger entry to a sensor ledger, wherein the ledger entry includes an identifier that identifies the sensor platform and is cryptographically linked to at least one previous ledger entry in the sensor ledger and transmit the sensor ledger, including the ledger entry, to the at least one other sensor platform via the wireless communication interface. In an analogous art, Mishra discloses collecting sensor data and hashing that first decrypted sensor data and storing the hashed sensor data in the blockchain together with the identifiers (paragraphs 0016, 0076). It would have been obvious to one of ordinary skill in the art to using Mishra’s blockchain-based storage of sensor data to store the data fused results of Chen-Hamza to ensure the authenticity and integrity of sensor data (Mishra: paragraph 0011).
5. Claim(s) 10-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Chen et al. (“Trust Model of Wireless Sensor Networks and Its Application in Data Fusion”) in view of Mishra (U.S. Patent Pub. No. US 2020/0106601) further in view of Hamza et al. (U.S. Patent Pub. No. US 2007/0297696).
Regarding claim 10, Chen discloses:
A method of data sharing in a distributed sensor network that includes a plurality of sensor platforms (section 1, page 1: wireless sensor nodes are composed of many sensor nodes which perform monitoring tasks in an area), the method comprising:
acquiring own sensor data about an environment in which the distributed sensor network is located using a sensor platform from among the plurality of sensor platforms (Section 3, page 3: the sensor nodes collect data and transmit it to the relay nodes); and
producing, with the sensor platform, a fused sensor view based on the own sensor data and a selected portion of the other sensor data (Section 3, page 3: relay nodes carry out data fusion and transfer data to the sink) from the sensor ledger, wherein the selected portion of the other sensor data is selected by the sensor platform based on a trust setting of the sensor platform and levels of trust assigned by the sensor platform to respective other sensor platforms among the plurality of sensor platforms (Section 3.2.2:, pages 7-8: trust list is updated according to the comprehensive trust of each sensor node; if the comprehensive trust is lower than the anomaly threshold, the sensor node is considered to be credible; Section 4, pages 8-9: in data fusion, sensor nodes need to satisfy two features, one is that they are included in the trust list).
Chen does not explicitly disclose receiving a sensor ledger from at least one other sensor platform in the distributed sensor network, the sensor ledger comprising a plurality of ledger entries, wherein individual ledger entries of the plurality of ledger entries include a respective portion of other sensor data and an identifier that identifies an individual sensor platform from among the plurality of sensor platforms as a source of the respective portion of the other sensor data, wherein the individual ledger entries are cryptographically linked to one another in the sensor ledger. In an analogous art, Mishra discloses receiving data from a sensor (paragraph 0003) that includes a device ID (paragraph 0003). Mishra discloses storing and securing data from sensors in a blockchain (paragraphs 0001-0002). Furthermore, the device identifier in the blockchain is linked with the user account in the blockchain (paragraphs 0058-0061, 0107-0108). The service platform of Mishra is in charge of collecting and processing data from sensors, and this data can be associated with a user account (paragraph 0088) which are associated with device identifiers (paragraph 0091). The device in Mishra tries to upload data to the blockchain (paragraph 0137) wherein the device was a sensor and collected environmental data (paragraph 0138). The message contains data encrypted by a key and the message is forwarded to the service platform (paragraph 0146) which takes the message, checks the device identifier and retrieves manufacturing information and forwarded to the blockchain (paragraph 0147). It would have been obvious to one of ordinary skill in the art to using Mishra’s blockchain-based storage of sensor data to store the data fused results of Chen to ensure the authenticity and integrity of sensor data (Mishra: paragraph 0011).
The combination of Chen and Mishra does not explicitly disclose a fused sensor view. In an analogous art, Hamza discloses a system and method for fusing sensor data and a synthetic data to form an integrated image (see Abstract). Hamza discloses a system for presenting the integrated imagine (paragraph 0020). The system combines sensor data received from more than one sensor (paragraph 0012). The system then combines the sensor data and synthetic view into an integrated image and the resulting image may be provided on a display providing a vehicle operator with a 3D view of the external environment of a vehicle (paragraphs 0053-0054). The sensor function may be applied selectively in some regions and excluded in some others to limit the noise in the fused image (paragraph 0028). The weights may be tuned based upon user choice of setting to weigh either source of information (paragraph 0012). It would have been obvious to one of ordinary skill in the art to use the display and fusing view of Hamza in the system of Chen to allow the user to interpret the fused information instead of trying to analyze multiple different sensor inputs (Hamza: paragraph 0054).
Claim 11 is rejected as applied above in rejecting claim 10. Furthermore, Mishra discloses:
The method of claim 10, further comprising: with the sensor platform, updating the sensor ledger to produce an updated sensor ledger by recording the own sensor data as an additional ledger entry in the sensor ledger, the additional ledger entry including the own sensor data and an identifier that identifies the sensor platform as a source of the own the sensor data, wherein updating the sensor ledger further includes cryptographically linking the additional ledger entry to at least one other ledger entry of the plurality of ledger entries in the updated sensor ledger (paragraphs 0016, 0076: hashing the first decrypted data and storing the hashed data in the blockchain together with the first device identifier).
Claim 12 is rejected as applied above in rejecting claim 11. Furthermore, Mishra discloses:
The method of claim 11, wherein cryptographically linking the additional ledger entry to the at least one other ledger entry includes producing a cryptographic hash of the at least one other ledger entry and including the cryptographic hash in the additional ledger entry (paragraph 0002: a block of index n also comprises the hash value of the data hashed for the previous block of index n-1).
Claim 13 is rejected as applied above in rejecting claim 11. Furthermore, Mishra discloses:
The method of claim 11, further comprising: transmitting the updated sensor ledger from the sensor platform to one or more other sensor platforms in the distributed sensor network (paragraph 0002: The blockchain is then shared among all the nodes of the network and is updated in all the nodes each time a new block is added and validated by all the nodes, via a process called “proof of work “or “proof of stake” or any other validation algorithm).
Claim 14 is rejected as applied above in rejecting claim 10. Furthermore, Chen discloses:
The method of claim 10, wherein the other sensor data includes a first portion from a first other sensor platform in the plurality of sensor platforms and a second portion from a second other sensor platform in the plurality of sensor platforms, wherein the first other sensor platform is assigned a first level of trust by the sensor platform, and the second other sensor platform is assigned a second level of trust by the sensor platform, the second level of trust being higher trust level than the first level of trust; and
wherein, producing the fused sensor view comprises:
based on the trust setting of the sensor platform being a first trust setting, selecting the selected portion of the other sensor data to include the first and second portions of the other sensor data (Section 3.2.2:, pages 7-8: trust list is updated according to the comprehensive trust of each sensor node; if the comprehensive trust is lower than the anomaly threshold, the sensor node is considered to be credible; Section 4, pages 8-9: in data fusion, sensor nodes need to satisfy two features, one is that they are included in the trust list), or
based on the trust setting of the sensor platform being a second trust setting, higher than the first trust setting, selecting the selected portion of the other sensor data to include the second portion of the other sensor data and exclude the first portion of the other sensor data (Section 3.2.2:, pages 7-8: trust list is updated according to the comprehensive trust of each sensor node; if the comprehensive trust is lower than the anomaly threshold, the sensor node is considered to be credible; Section 4, pages 8-9: in data fusion, sensor nodes need to satisfy two features, one is that they are included in the trust list).
Claim 15 is rejected as applied above in rejecting claim 10. Furthermore, Hamza discloses:
The method of claim 10, further comprising:
changing the trust setting of the sensor platform based on a user input (paragraphs 0012, 0054: may be tuned based upon user choice of setting to weigh either source of information).
Claim 16 is rejected as applied above in rejecting claim 10. Furthermore, Chen discloses:
The method of claim 10, wherein the sensor platform is configured to assign the first level of trust to the first other sensor platform and to assign the second level of trust to the second other sensor platform based on one or more trust factors (Section 3, page 3: the trust value of the sensor nodes is calculated in the cluster heads), wherein the trust factors include locations of the plurality of sensor platforms, operators of the plurality of sensor platforms, sensor capabilities of the plurality of sensor platforms, and/or environmental conditions affecting the plurality of sensor platforms (page 5: the regional relative trust is calculated by the real-time monitoring of the i-th sensor node and the average value of the real-time monitoring data of the other sensor nodes in the region).
Regarding claim 17, Chen discloses:
A computer program product comprising one or more non-transitory machine-readable mediums having instructions encoded thereon that when executed by at least one processor cause a sensor platform to perform a method of data aggregation in a distributed sensor network, the method comprising:
acquiring, with the sensor platform, own sensor data about an environment in which the distributed sensor network is located (Section 3, page 3: the sensor nodes collect data and transmit it to the relay nodes); and
producing, with the sensor platform, a fused sensor view based on the own sensor data and a selected portion of the other sensor data (Section 3, page 3: relay nodes carry out data fusion and transfer data to the sink), wherein the selected portion of the other sensor data is selected by the sensor platform based on a trust setting of the sensor platform and levels of trust assigned by the sensor platform to respective other sensor platforms in the distributed sensor network (Section 3.2.2:, pages 7-8: trust list is updated according to the comprehensive trust of each sensor node; if the comprehensive trust is lower than the anomaly threshold, the sensor node is considered to be credible; Section 4, pages 8-9: in data fusion, sensor nodes need to satisfy two features, one is that they are included in the trust list).
Chen does not explicitly disclose receiving a sensor ledger from at least one other sensor platform in the distributed sensor network, the sensor ledger comprising a plurality of ledger entries, wherein individual ledger entries of the plurality of ledger entries include a respective portion of other sensor data and an identifier that identifies an individual sensor platform from among the plurality of sensor platforms as a source of the respective portion of the other sensor data, wherein the individual ledger entries are cryptographically linked to one another in the sensor ledger. In an analogous art, Mishra discloses receiving data from a sensor (paragraph 0003) that includes a device ID (paragraph 0003). Mishra discloses storing and securing data from sensors in a blockchain (paragraphs 0001-0002). Furthermore, the device identifier in the blockchain is linked with the user account in the blockchain (paragraphs 0058-0061, 0107-0108). The service platform of Mishra is in charge of collecting and processing data from sensors, and this data can be associated with a user account (paragraph 0088) which are associated with device identifiers (paragraph 0091). The device in Mishra tries to upload data to the blockchain (paragraph 0137) wherein the device was a sensor and collected environmental data (paragraph 0138). The message contains data encrypted by a key and the message is forwarded to the service platform (paragraph 0146) which takes the message, checks the device identifier and retrieves manufacturing information and forwarded to the blockchain (paragraph 0147). It would have been obvious to one of ordinary skill in the art to using Mishra’s blockchain-based storage of sensor data to store the data fused results of Chen to ensure the authenticity and integrity of sensor data (Mishra: paragraph 0011).
The combination of Chen and Mishra does not explicitly disclose a fused sensor view. In an analogous art, Hamza discloses a system and method for fusing sensor data and a synthetic data to form an integrated image (see Abstract). Hamza discloses a system for presenting the integrated imagine (paragraph 0020). The system combines sensor data received from more than one sensor (paragraph 0012). The system then combines the sensor data and synthetic view into an integrated image and the resulting image may be provided on a display providing a vehicle operator with a 3D view of the external environment of a vehicle (paragraphs 0053-0054). The sensor function may be applied selectively in some regions and excluded in some others to limit the noise in the fused image (paragraph 0028). The weights may be tuned based upon user choice of setting to weigh either source of information (paragraph 0012). It would have been obvious to one of ordinary skill in the art to use the display and fusing view of Hamza in the system of Chen to allow the user to interpret the fused information instead of trying to analyze multiple different sensor inputs (Hamza: paragraph 0054).
Claim 18 is rejected as applied above in rejecting claim 17. Furthermore, Mishra discloses:
The computer program product of claim 17, wherein the method further comprises:
with the sensor platform, updating the sensor ledger to produce an updated sensor ledger by recording the own sensor data as an additional ledger entry in the sensor ledger, the additional ledger entry including the own sensor data and an identifier that identifies the sensor platform as a source of the own the sensor data, wherein updating the sensor ledger further includes cryptographically linking the additional ledger entry to at least one other ledger entry of the plurality of ledger entries in the updated sensor ledger (paragraphs 0016, 0076: hashing the first decrypted data and storing the hashed data in the blockchain together with the first device identifier).
Claim 19 is rejected as applied above in rejecting claim 17. Furthermore,
The computer program product of claim 17, wherein the other sensor data includes a first portion from a first other sensor platform in the distributed sensor network and a second portion from a second other sensor platform in the distributed sensor network, the method comprising:
assigning, by the sensor platform, a first level of trust to the first other sensor platform (Section 3, page 3: the trust value of the sensor nodes is calculated in the cluster heads); and
assigning, by the sensor platform, a second level of trust to the second other sensor platform, the second level of trust being higher trust level than the first level of trust (Section 3.2.2:, pages 7-8: trust list is updated according to the comprehensive trust of each sensor node; if the comprehensive trust is lower than the anomaly threshold, the sensor node is considered to be credible; Section 4, pages 8-9: in data fusion, sensor nodes need to satisfy two features, one is that they are included in the trust list);
and
wherein, producing the fused sensor view comprises:
based on the trust setting of the sensor platform being a first trust setting, selecting the selected portion of the other sensor data to include the first and second portions of the other sensor data, or based on the trust setting of the sensor platform being a second trust setting, higher than the first trust setting, selecting the selected portion of the other sensor data to include the second portion of the other sensor data and exclude the first portion of the other sensor data (Section 1, page 2, paragraph 4: using the trust model and the given threshold, we can exclude the abnormal data from the fused data; Section 3.2.2:, pages 7-8: trust list is updated according to the comprehensive trust of each sensor node; if the comprehensive trust is lower than the anomaly threshold, the sensor node is considered to be credible; Section 4, pages 8-9: in data fusion, sensor nodes need to satisfy two features, one is that they are included in the trust list).
Claim 20 is rejected as applied above in rejecting claim 17. Furthermore, Hamza discloses:
The computer program product of claim 17, wherein the method further comprises changing the trust setting of the sensor platform based on a user input (paragraphs 0012, 0054: may be tuned based upon user choice of setting to weigh either source of information).
Conclusion
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/KAVEH ABRISHAMKAR/
02/25/2026Primary Examiner, Art Unit 2494