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 .
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 10/24/2025 has been entered.
Response to Amendment
Claims 13, 16, 18, 19-22 and 24-28 are pending in this application.
Claim rejections 35 USC 101 are maintained.
Applicant’s arguments on claim rejections 35 USC 102 and 35 USC 103, filed 8/28/2025, 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 Therefore, the rejection has been withdrawn.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 in view of Rane and Thiyagarajah.
Response to Arguments
Applicant argues that the claims include wording to the effect of "if the comparison is successful, storing at least one validation measure for the first or second sensors in the distributed database and validating electrical consumption of the electrical load by an operator of the electrical power grid" and "wherein the at least one validation measure comprises triggering a settlement process based on a deviation between the first measurement dataset and the second measurement dataset", which provides an improvement to the technological field of electrical power management, where the automated processes may, for example, involve first and second sensors that are computer-based devices having at least a processor, memory and communication interface for communicating with other computer-based devices.
Examiner respectfully submits that MPEP recites that:
“The courts have not provided an explicit test for this consideration, but have instead illustrated how it is evaluated in numerous decisions. These decisions, and a detailed explanation of how examiners should evaluate this consideration are provided in MPEP § 2106.05(a). In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology. Second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement.” (MPEP 2106.04(d)(1), Emphasis added).
Examiner respectfully submits that the specification explicitly sets forth an improvement but in a conclusory manner such as providing an improvement to the technological field of electrical power management, where the automated processes may involve first and second sensors that are computer-based devices having at least a processor, memory and communication interface for communicating with other computer-based devices. In addition, the claims do not provide sufficient details to be apparent to a person of ordinary skill in the art. For example, the claims do not provide sufficient details for a person of ordinary skill in the art how to implement the “settlement process” Therefore, the examiner should not determine the claims improve technology.
Applicant’s arguments with respect to claim rejections 35 USC 102 and 35 USC 103 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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 13, 16, 18, 19-22 and 24-28 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claims 13 and 27:
Step 1:
Claim 13 recites “A computer-implemented method”. The claim recites a series of steps and therefore is a process.
Claim 27 recites “A device”. The claim recites the device comprising a communication interface, at least one processor and a non-transitory memory storing program code and therefore is a machine.
Step 2A Prong One:
Claims 13 and 27 recite the limitations “triggering” and “validating” which specifically recite “triggering a smart contract in the distributed database to compare the first measurement dataset and the second measurement dataset utilizing a metric based on variables in the first and second measurement datasets;” and “validating electrical consumption of the electrical load by an operator of the electrical power grid;” These limitations are processes that, under their broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other reciting a “communication interface”, at least one “processor” and a “non-transitory memory”, nothing in the claim element precludes the step from practically being performed in a human mind or with the aid of pen and paper. For example, “triggering” and “validating” in the context of this claim encompasses a user mentally, and with the aid of pen and paper comparing a first measurement dataset and a second measurement dataset utilizing a metric based on variables in the first and second measurement datasets and evaluating electrical consumption of an electrical load by an operator of an electrical power grid. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas (concepts performed in the human mind including an observation, evaluation, judgment and opinion).
Step 2A Prong Two: The judicial exception is not integrated into a practical application. The claims 13 and 27 recite the additional elements “obtaining a first measurement dataset from a first sensor detecting electrical characteristics of an electrical load connected to the electrical power grid and storing the first measurement dataset in the distributed database;” “obtaining a second measurement dataset from a second sensor detecting operational characteristics of the electrical load and storing the second measurement dataset in the distributed database;” and “if the comparison is successful, storing at least one validation measure for the first or second sensors in the distributed database;” The limitations amount to adding insignificant extra-solution activity to the judicial exception, such as data gathering (MPEP 2106.05(g)). The claims also recite the additional element “wherein the at least one validation measure comprises triggering a settlement process based on a deviation between the first measurement dataset and the second measurement dataset.” The limitation amounts to no more than mere instructions on a general purpose computer ((MPEP 2106.05(f)).
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claims 13 and 27 recite the limitation “if the comparison is successful, storing at least one validation measure for the first or second sensors in the distributed database;” The limitation amounts to well‐understood, routine, and conventional functions, e.g. storing and retrieving information in memory (See MPEP 2106.05(d)). As discussed above, the additional elements of using a “communication interface”, at least one “processor” and a “non-transitory memory” to perform the steps amounts to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
Claim 16 is dependent on the claim 13 and includes all the limitations of claim 13. Therefore, claim 16 recites the same abstract idea of claim 13. The claim also recites the additional element “the at least one validation measure further comprises storing a variable indicative of at least one of the result of the comparison, the first measurement dataset, and the second measurement dataset in the distributed database.” The limitation amounts to adding insignificant extra-solution activity to the judicial exception, such as data gathering and outputting (MPEP 2106.05(g)). The limitation also amounts to well‐understood, routine, and conventional functions, e.g. storing and retrieving information in memory (See MPEP 2106.05(d)). The claim is not patent eligible.
Claim 18 is dependent on the claim 13 and includes all the limitations of claim 13. Therefore, claim 18 recites the same abstract idea of claim 13. The claim also recites the additional element “the comparison is based on a predefined agreement indicative of a metric of the comparison” which further elaborates on the abstract idea and therefore, does not amount to significant more. The claim is not patent eligible.
Regarding claims 19 and 28:
Step 1:
Claim 19 recites “A computer-implemented method”. The claim recites a series of steps and therefore is a process.
Claim 28 recites “A device”. The claim recites the device comprising a communication interface, at least one processor and a non-transitory memory storing program code and therefore is a machine.
Step 2A Prong One:
Claims 19 and 28 recite the limitations “performing” and “validating” which specifically recite “performing, at the second sensor, a comparison between the first measurement dataset and the second measurement dataset utilizing a metric based on variables in the first and second measurement datasets;” and “validating electrical consumption of the electrical load by an operator of the electrical power grid;” These limitations are processes that, under their broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other reciting a “communication interface”, at least one “processor” and a “non-transitory memory”, nothing in the claim element precludes the step from practically being performed in a human mind or with the aid of pen and paper. For example, “performing” and “validating” in the context of this claim encompasses a user mentally, and with the aid of pen and paper comparing a first measurement dataset and a second measurement dataset utilizing a metric based on variables in the first and second measurement datasets and evaluating electrical consumption of an electrical load by an operator of an electrical power grid. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, then it falls within the “Mental Processes” grouping of abstract ideas (concepts performed in the human mind including an observation, evaluation, judgment and opinion).
Step 2A Prong Two: The judicial exception is not integrated into a practical application. The claims 19 and 28 recite the additional elements “obtaining a first measurement dataset from a first sensor detecting at least one electrical characteristic of an electrical load connected to the electrical power grid and storing the first measurement data set in a distributed database;” “capturing a second measurement dataset from a second sensor detecting at least one operational characteristic of the electrical load and storing the second measurement data set in the distributed database;” and “if the comparison is successful, storing at least one validation measure for the first or second sensors in the distributed database;” The limitations amount to adding insignificant extra-solution activity to the judicial exception, such as data gathering (MPEP 2106.05(g)). The claims also recite the additional element “wherein the at least one validation measure comprises triggering a settlement process based on a deviation between the first measurement dataset and the second measurement dataset.” The limitation amounts to no more than mere instructions on a general purpose computer ((MPEP 2106.05(f)).
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The claims 19 and 28 recite the limitation “if the comparison is successful, storing at least one validation measure for the first or second sensors in the distributed database;” The limitation amounts to well‐understood, routine, and conventional functions, e.g. storing and retrieving information in memory (See MPEP 2106.05(d)). As discussed above, the additional elements of using a “communication interface”, at least one “processor” and a “non-transitory memory” to perform the steps amounts to no more than mere instructions to apply the exception using generic computer components (See MPEP 2106.05(f)). Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
Claim 20 is dependent on the claim 19 and includes all the limitations of claim 19. Therefore, claim 20 recites the same abstract idea of claim 19. The claim also recites the additional element “the at least one validation measure further comprises storing a variable indicative of at least one of the result of the comparison, the first measurement dataset, and the second measurement dataset in the distributed database.” The limitation amounts to adding insignificant extra-solution activity to the judicial exception, such as data gathering and outputting (MPEP 2106.05(g)). The limitation also amounts to well‐understood, routine, and conventional functions, e.g. storing and retrieving information in memory (See MPEP 2106.05(d)). The claim is not patent eligible.
Claim 21 is dependent on the claim 19 and includes all the limitations of claim 19. Therefore, claim 21 recites the same abstract idea of claim 19. The claim also recites the additional element “checking the variable by the first sensor” which further elaborates on the abstract idea and therefore, does not amount to significant more. The claim is not patent eligible.
Claim 22 is rejected under the same rationale as claim 21.
Claim 24 is dependent on the claim 19 and includes all the limitations of claim 19. Therefore, claim 24 recites the same abstract idea of claim 19. The claim also recites the additional element “the comparison is based on a predefined agreement indicative of a metric of the comparison” which further elaborates on the abstract idea and therefore, does not amount to significant more. The claim is not patent eligible.
Claim 25 is dependent on the claim 24 and includes all the limitations of claim 19. Therefore, claim 25 recites the same abstract idea of claim 19. The claim also recites the additional element “the metric is based on at least one of (i) a time-shift between capturing the at least one electrical characteristic and capturing the at least one operational characteristic, and (ii) a tolerance range between the first and second measurement datasets” which further elaborates on the abstract idea and therefore, does not amount to significant more. The claim is not patent eligible.
Claim 26 is dependent on the claim 19 and includes all the limitations of claim 19. Therefore, claim 26 recites the same abstract idea of claim 19. The claim also recites the additional element “the at least one electrical characteristic is different from the at least one operational characteristic” which further elaborates on the abstract idea and therefore, does not amount to significant more. The claim is not patent eligible.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 13, 16, 18 and 27 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Rane (US 2019/0087571).
Regarding claim 13, Rane teaches A computer-implemented method for validating measurement datasets from sensors in an electrical power grid utilizing a distributed database stored in non-transitory memory ([0002]: discussing about a cyber-physical system can include control systems and infrastructures for, e.g., an electric power grid; [0047], [0051] and Fig. 6: discussing about storage device 608 can store data 632. Data 632 can include any data that is required as input or that is generated as output by the methods and/or processes described in this disclosure.), comprising:
obtaining a first measurement dataset from a first sensor detecting electrical characteristics of an electrical load connected to the electrical power grid and storing the first measurement dataset in the distributed database ([0002]: discussing about a cyber-physical system can include control systems and infrastructures for, e.g., an electric power grid; [0024]: The block chain allows each stakeholder to write data received from devices in the control system (e.g., sensors in an electric power plant). [0042]: FIG. 4 presents a flow chart 400 illustrating a method by a distributed entity for facilitating detection of attacks in a cyber-physical system, in accordance with an embodiment of the present invention. During operation, the system receives, by a first entity of a plurality of entities, a first reading from a first set of sensors of a cyber-physical system via a first network, wherein the first sensors are operating on the first network (operation 402).);
obtaining a second measurement dataset from a second sensor detecting operational characteristics of the electrical load and storing the second measurement dataset in the distributed database ([0002]: discussing about a cyber-physical system can include control systems and infrastructures for, e.g., an electric power grid; [0024]: discussing about writing data received from devices in the control system (e.g., sensors in an electric power plant); [0042]: The system receives, by the first entity, a second reading from a second set of sensors of the cyber-physical system via a second network, wherein the second set is a set of redundant sensors for the first sensors, wherein the second set of sensors are operating on a second network, and wherein the second network includes security measures which prevent access by any external entity or any of the plurality of entities (operation 404). The second network is a redundant network for the first network.);
triggering a smart contract in the distributed database to compare the first measurement dataset and the second measurement dataset utilizing a metric based on variables in the first and second measurement datasets ([0043]:The system executes, by the other entities, the smart contract based on the first reading and the second reading (operation 410), and the operation continues as described at Label A of FIG. 5. [0045]: The system can also determine if the result of the executed smart contract matches an expected condition (decision 512). The expected condition can be based on, e.g.: receiving the first reading and the second reading within a predetermined interval; whether the first reading and the second reading are equal; whether the first reading and the second reading are within a predetermined range; whether a function performed based on the first reading and the second reading yields a result within a predetermined range; whether the first reading and the second reading indicate a same physical quantity; whether the first reading and the second reading indicate a different physical quantity; and a change in device settings, firmware, or software associated with the first sensors and the second sensors.); and
if the comparison is successful, storing at least one validation measure for the first or second sensors in the distributed database and validating electrical consumption of the electrical load by an operator of the electrical power grid ([0044]: If the system does determine a consensus, the system writes the result to a block chain (operation 504). The result can be indicated as described above in exemplary data structures 320 and 340 of FIG. 3 (e.g., in smart contract result field 304). Note that any of the distributed entities can determine the consensus and write the result to the block chain. [0047] and Fig. 6: discussing about storage device 608 can store data 632. [0051]: Data 632 can include any data that is required as input or that is generated as output by the methods and/or processes described in this disclosure.);
wherein the at least one validation measure comprises triggering a settlement process based on a deviation between the first measurement dataset and the second measurement dataset ([0044]: The result can be indicated as described above in exemplary data structures 320 and 340 of FIG. 3 (e.g., in smart contract result field 304). [0037]: discussing about a condition indicator 308 of whether the result of the smart contract executed by the respective entity matches an expected condition (e.g., a flag that indicates whether the condition was “Expected” or “Not Expected”)).
Regarding claim 16, Rane teaches wherein the at least one validation measure further comprises storing a variable indicative of at least one of the result of the comparison, the first measurement dataset, and the second measurement dataset in the distributed database ([0044]: The result can be indicated as described above in exemplary data structures 320 and 340 of FIG. 3 (e.g., in smart contract result field 304). [0037]: discussing about a condition indicator 308 of whether the result of the smart contract executed by the respective entity matches an expected condition (e.g., a flag that indicates whether the condition was “Expected” or “Not Expected”)).
Regarding claim 18, Rane teaches wherein the comparison is based on a predefined agreement indicative of a metric of the comparison ([0045]: The system can also determine if the result of the executed smart contract matches an expected condition (decision 512). The expected condition can be based on, e.g.: receiving the first reading and the second reading within a predetermined interval; whether the first reading and the second reading are equal; whether the first reading and the second reading are within a predetermined range; whether a function performed based on the first reading and the second reading yields a result within a predetermined range; whether the first reading and the second reading indicate a same physical quantity; whether the first reading and the second reading indicate a different physical quantity; and a change in device settings, firmware, or software associated with the first sensors and the second sensors.).
Claim 27 is rejected under the same rationale as claim 13. Rane also teaches A device for validating measurement datasets from sensors in an electrical power grid, comprising: a communication interface ([0030]:The plurality of distributed entities may communicate with each other either directly or via another distributed entity.); and at least one processor; a non-transitory memory storing program code which, when executed by the at least one processor, perform a method ([0047]: Computer system 602 includes a processor 604, a memory 606, and a storage device 608. Memory 606 can include a volatile memory (e.g., RAM) that serves as a managed memory, and can be used to store one or more memory pools.).
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 19-22, 24-26 and 28 are rejected under 35 U.S.C. 103 as being unpatentable over Rane in view of Thiyagarajah et al. (US 2018/0308340, hereinafter “Thiyagarajah”).
Regarding claim 19, Rane teaches A computer-implemented method for validating measurement datasets from sensors in an electrical power grid utilizing a distributed database stored in non-transitory memory ([0002]: discussing about a cyber-physical system can include control systems and infrastructures for, e.g., an electric power grid; [0047], [0051] and Fig. 6: discussing about storage device 608 can store data 632. Data 632 can include any data that is required as input or that is generated as output by the methods and/or processes described in this disclosure.), comprising:
obtaining a first measurement dataset from a first sensor detecting at least one electrical characteristic of an electrical load connected to the electrical power grid and storing the first measurement data set in a distributed database ([0002]: discussing about a cyber-physical system can include control systems and infrastructures for, e.g., an electric power grid; [0024]: The block chain allows each stakeholder to write data received from devices in the control system (e.g., sensors in an electric power plant). [0042]: FIG. 4 presents a flow chart 400 illustrating a method by a distributed entity for facilitating detection of attacks in a cyber-physical system, in accordance with an embodiment of the present invention. During operation, the system receives, by a first entity of a plurality of entities, a first reading from a first set of sensors of a cyber-physical system via a first network, wherein the first sensors are operating on the first network (operation 402).);
capturing a second measurement dataset from a second sensor detecting at least one operational characteristic of the electrical load and storing the second measurement data set in the distributed database ([0002]: discussing about a cyber-physical system can include control systems and infrastructures for, e.g., an electric power grid; [0024]: discussing about writing data received from devices in the control system (e.g., sensors in an electric power plant); [0042]: The system receives, by the first entity, a second reading from a second set of sensors of the cyber-physical system via a second network, wherein the second set is a set of redundant sensors for the first sensors, wherein the second set of sensors are operating on a second network, and wherein the second network includes security measures which prevent access by any external entity or any of the plurality of entities (operation 404). The second network is a redundant network for the first network.);
performing a comparison between the first measurement dataset and the second measurement dataset utilizing a metric based on variables in the first and second measurement datasets ([0045]: The system can also determine if the result of the executed smart contract matches an expected condition (decision 512). The expected condition can be based on, e.g.: receiving the first reading and the second reading within a predetermined interval; whether the first reading and the second reading are equal; whether the first reading and the second reading are within a predetermined range; whether a function performed based on the first reading and the second reading yields a result within a predetermined range; whether the first reading and the second reading indicate a same physical quantity; whether the first reading and the second reading indicate a different physical quantity; and a change in device settings, firmware, or software associated with the first sensors and the second sensors.); and
if the comparison is successful, storing at least one validation measure for the first or second sensors in the distributed database and validating electrical consumption of the electrical load by an operator of the electrical power grid ([0044]: If the system does determine a consensus, the system writes the result to a block chain (operation 504). The result can be indicated as described above in exemplary data structures 320 and 340 of FIG. 3 (e.g., in smart contract result field 304). Note that any of the distributed entities can determine the consensus and write the result to the block chain. [0047], [0051] and Fig. 6: discussing about storage device 608 can store data 632. Data 632 can include any data that is required as input or that is generated as output by the methods and/or processes described in this disclosure.);
wherein the at least one validation measure comprises triggering a settlement process based on a deviation between the first measurement dataset and the second measurement dataset ([0044]: The result can be indicated as described above in exemplary data structures 320 and 340 of FIG. 3 (e.g., in smart contract result field 304). [0037]: discussing about a condition indicator 308 of whether the result of the smart contract executed by the respective entity matches an expected condition (e.g., a flag that indicates whether the condition was “Expected” or “Not Expected”)).
Rane does not explicitly teach performing, at the second sensor, a comparison between the first measurement dataset and the second measurement dataset utilizing a metric based on variables in the first and second measurement datasets
Thiyagarajah teaches performing, at the second sensor, a comparison between the first measurement dataset and the second measurement dataset utilizing a metric based on variables in the first and second measurement datasets ([0055]: The IoT sensor can be different sensors such as, for example, motion, temperature, voltage, current, and proximity sensors. The IoT sensor can an ISO electric opto coupler. The IoT sensor can a comparator that compares two values and generates usage data as a result of the comparison.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the control system of Rane with the teaching about the IoT sensor of Thiyagarajah because it provides significant advantages by connecting devices to improve efficiency, automate tasks, and enhance data-driven decision-making. It would reduce operational costs through predictive maintenance, increase productivity, improve safety and security monitoring, better resource management, and enhance convenience in daily life.
Regarding claim 20, Rane in view of Thiyagarajah teaches wherein the at least one validation measure further comprises storing a variable indicative of at least one of the result of the comparison, the first measurement dataset, and the second measurement dataset in the distributed database (Rane, [0044]: The result can be indicated as described above in exemplary data structures 320 and 340 of FIG. 3 (e.g., in smart contract result field 304). [0037]: discussing about a condition indicator 308 of whether the result of the smart contract executed by the respective entity matches an expected condition (e.g., a flag that indicates whether the condition was “Expected” or “Not Expected”)).
Regarding claim 21, Rane in view of Thiyagarajah teaches checking the variable by the first sensor (Rane, [0024]: The block chain allows each stakeholder to write data received from devices in the control system (e.g., sensors in an electric power plant). The block chain also allows a stakeholder to sign and write data into blocks, and can further encrypt the data. Examples of data which may be written to the block chain by a stakeholder include: primary sensor readings and actuator actions at regular time intervals; redundant sensor readings at regular time intervals; firmware upgrades on sensors, actuators, and controller modules; and instances at which observed behavior of the system deviates from the expected behavior, and a duration for which the deviation occurs. [0042]: During operation, the system receives, by a first entity of a plurality of entities, a first reading from a first set of sensors of a cyber-physical system via a first network, wherein the first sensors are operating on the first network (operation 402). Thiyagarajah, [0018]: Example sensors or electronics include motion, temperature, voltage, current clamp, motion/proximity sensor, humidity, environment, pressure, temperature, lighting, volatile organic compounds (e.g. C02), passive electronic devices that can detect pulse e.g. ISO electric opto coupler, a comparator that receives two different values and compares them and if one is higher gives a 1 and if lower gives 0 to determine if there is a positive or negative signal, and so on.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the control system of Rane with the teaching about the IoT sensor of Thiyagarajah because it provides significant advantages by connecting devices to improve efficiency, automate tasks, and enhance data-driven decision-making. It would reduce operational costs through predictive maintenance, increase productivity, improve safety and security monitoring, better resource management, and enhance convenience in daily life.
Claim 22 is rejected under the same rationale as claim 21.
Regarding claim 24, Rane in view of Thiyagarajah teaches wherein the comparison is based on a predefined agreement indicative of a metric of the comparison (Rane, [0045]: The system can also determine if the result of the executed smart contract matches an expected condition (decision 512). The expected condition can be based on, e.g.: receiving the first reading and the second reading within a predetermined interval; whether the first reading and the second reading are equal; whether the first reading and the second reading are within a predetermined range; whether a function performed based on the first reading and the second reading yields a result within a predetermined range; whether the first reading and the second reading indicate a same physical quantity; whether the first reading and the second reading indicate a different physical quantity; and a change in device settings, firmware, or software associated with the first sensors and the second sensors.).
Regarding claim 25, Rane in view of Thiyagarajah teaches wherein the metric is based on at least one of (i) a time-shift between capturing the at least one electrical characteristic and capturing the at least one operational characteristic, and (ii) a tolerance range between the first and second measurement datasets (Rane, [0043]: discussing about the expected condition can be based on, e.g.: receiving the first reading and the second reading within a predetermined interval; whether the first reading and the second reading are equal; whether the first reading and the second reading are within a predetermined range; whether a function performed based on the first reading and the second reading yields a result within a predetermined range…).
Regarding claim 26, Rane in view of Thiyagarajah teaches wherein the at least one electrical characteristic is different from the at least one operational characteristic (Rane, [0002]: A cyber-physical system can include control systems and infrastructures for, e.g., an electric power grid, hydroelectric power plants, building environmental control systems, robotics systems, and aircraft systems. [0029]: Environment 100 can include an industrial plant, such as a power plant 120, including a cooling tower 122, flue-gas stacks 124, and a containment building 126. Building 126 can include physical equipment measured by primary sensors 130.1-130.5 which operate on a first network 102, and by redundant sensors 140.1-140.5 which operate on a second network 104.).
Claim 28 is rejected under the same rationale as claim 19. Rane also teaches A device for validating measurement datasets from sensors in an electrical power grid, comprising: a communication interface ([0030]:The plurality of distributed entities may communicate with each other either directly or via another distributed entity.); and at least one processor; a non-transitory memory storing program code which, when executed by the at least one processor, perform a method ([0047]: Computer system 602 includes a processor 604, a memory 606, and a storage device 608. Memory 606 can include a volatile memory (e.g., RAM) that serves as a managed memory, and can be used to store one or more memory pools.).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Ordanis (US 2015/0355245) discloses that data accumulated by the nodal junction is used for analysis of wave patterns to detect anomalies in the local electrical network and/or loads connected to the local electrical network. Anomalies can be detected in various ways, including: comparison of data with historical data acquired from the local node sensors; comparison of data with known wave pattern profiles for similar loads; and comparison of data with data acquired from local node sensors at other locations.
Schoenfelder (US 4,103,493) discloses that electrical impulse sensors 98 and 100 sense the current in each line and sends signals back to the load monitor 92. Load monitor 92 compares the signals from sensors 98 and 100 and if the current in sensor 100 is greater than the current load in sensor 98, load monitor 92 opens contact 88 and closes contact 90.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PHONG H NGUYEN whose telephone number is (571)270-1766. The examiner can normally be reached Monday-Friday, 8:30am-5pm EST.
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/PHONG H NGUYEN/ Primary Examiner, Art Unit 2156
February 18, 2026