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 .
Status of Claims
Claims 1-8, and 10-20 have been examined and are pending in this Non-Final Rejection. Claims 1-20 are currently rejected.
Request for Continued Examination Under 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 04/02/2026 has been entered.
Priority
Application 18/481,136 was filed 10/04/2023.
Claim Interpretation
The limitations of method Claim 10 after “generating a Zero Knowledge (ZK) attestation” are interpreted as contingent limitations because the CFM may be above a threshold in view of Applicant’s Specification and the claim language itself, may be “less than a carbon footprint threshold” or “above a carbon footprint threshold”. “The broadest reasonable interpretation (BRI) of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent are not met.” MPEP § 2111.04(II). In the interest of compact prosecution, the remaining limitations here, are the same as the system Claim 1 limitations there. “The system claim interpretation differs from a method claim interpretation because the claimed structure must be present in the system regardless of whether the condition is met and the function is actually performed.” MPEP § 2111.04(II).
The Zero Knowledge (ZK) attestation, and proof is interpreted as a type of attestation and proof since there is no definition of Zero Knowledge in the specification.
The device is recited as having a processor, memory communicatively coupled to the processor, and a sustainability logic. The sustainability logic is not claimed to be residing in the memory or integrated into the processor and is interpreted as residing in the memory as Spec. Par. 0131 recites “the sustainability logic 1124 can be a set of instructions stored within a non-volatile memory”.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-20 are directed to a system, method, or product which are/is one of the statutory categories of invention. (Step 1: YES).
Claims 1, 10, and 15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites a method and computing device for generating attestations if a sum of carbon metrics is above a threshold, and verifying proof based on the attestation. For Claims 1, 10 and 15 the limitations of (Claim 1 being representative):
[…]
a sustainability logic, configured to: receive one or more normalized Carbon Footprint Metrics (CFMs) corresponding to a timeframe;
generate, in response to a sum of the one or more normalized CFMs being less than a carbon footprint threshold, a Zero Knowledge (ZK) attestation by:
determining a key value and an offset value based on the one or more normalized CFMs and the carbon footprint threshold such that a sum of the one or more normalized CFMs and the offset value is greater than the carbon footprint threshold; and
applying a hash on the key value;
generate a verifiable ZK proof based on the ZK attestation; and
transmit the verifiable ZK proof […];
determine an actual energy usage […] based on the one or more normalized CFMs; and
control an energy consumption of the device dynamically such that the actual energy usage of the device is less than a maximum energy usage indicated by the carbon footprint threshold.
The above limitations are reciting a process by which energy use is being determined, and energy consumption is being controlled. Under the broadest reasonable interpretation, controlling energy consumption based off of energy usage, covers certain methods of organizing human activity (i.e., managing personal behavior including following rules or instructions) but for recitation of generic computer components. The Examiner notes that “certain method[s] of organizing human activity” includes a person's interaction with a computer (see MPEP 2106.04(a)(2)(II)). If a claim limitation, under its broadest reasonable interpretation, covers managing personal behavior or interactions between people but for the recitation of generic computer components, then it falls within the “certain methods of organizing human activity” grouping of abstract ideas.
Additionally, generating in response to a sum of the one or more normalized CFMs being less than a carbon footprint threshold, a Zero Knowledge (ZK) attestation by: determining a key value and an offset value based on the one or more normalized CFMs and the carbon footprint threshold such that a sum of the one or more normalized CFMs and the offset value is greater than the carbon footprint threshold, and applying a hash on the key value, and generating a verifiable ZK proof based on the ZK attestation, as drafted, is a process that, under the broadest reasonable interpretation, covers mathematical concepts. The Examiner notes that “Mathematical Concepts” includes a mathematical relationships, mathematical formulas or equations, and mathematical calculations. If a claim limitation, under its broadest reasonable interpretation, covers a numerical formula or equation it will be considered as falling within the “mathematical concepts” grouping. In addition, there are instances where a formula or equation is written in text format that should also be considered as falling within this grouping. The types of identified abstract ideas are considered together as a single abstract idea for analysis purposes. Accordingly, Claims 1, 10 and 15 recite an abstract idea. (Step 2A- Prong 1: YES. The claims are abstract).
This judicial exception is not integrated into a practical application. Claims 1, 10, and 15 recite the additional elements of a device (Claims 1, and 15), a processor (Claims 1 and 15), a memory communicatively coupled to the processor (Claims 1 and 15), and auditing device (Claims 1, 10, and 15), that implements the identified abstract idea. These additional elements are not described by the applicant and are recited at a high-level of generality (i.e., one or more generic computers performing a generic computer functions) such that it amounts no more than mere instructions to apply the exception using a generic computer components. Accordingly, even in combination these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Claims 1, 10, and 15 are directed to an abstract idea. (Step 2A-Prong 2: NO: the additional claimed elements are not integrated into a practical application).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a device (Claims 1, and 15), a processor (Claims 1 and 15), a memory communicatively coupled to the processor (Claims 1 and 15), and auditing device (Claims 1, 10, and 15), to perform the noted steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”). Accordingly, even in combination, these additional elements do not provide significantly more. As such claims 1, 10, and 15 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more).
Dependent Claims 2-8, 11-14 and 16-20 are similarly rejected because they either further define/narrow the abstract idea of independent claims 1, 10 and 15 as discussed above. Claim(s) 2 & 16 merely describe(s) the verifiable ZK proof including the attestation, identifier of the deice, and time data. Claim(s) 3 & 17 merely describe(s) the time data. Claim(s) 6 & 12 merely describe(s) comparing the sum of carbon footprint metric with the threshold dynamically, generating proof is the sum in less that the threshold, and adjusting an energy consumption of the device if the sum is greater than the footprint threshold. Claim(s) 7 merely describe(s) the normalized carbon footprint metric corresponding to a single greenhouse gas metric, multiple greenhouse gas metric or a composite sustainability metric. Therefore claims 2, 3, 6, 7, 12, 16, and 17 are considered patent ineligible for the reasons given above.
Dependent Claim(s) 4, 5, 8, 11, 13, 14, 18, 19, and 20 recite limitations that further define the abstract idea noted in independent claims 1, 10, and 15. In addition, it recites the additional elements of a hash value, and telemetry data. The hash value, and telemetry data are recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computing component. Even in combination, these additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. Alternatively or in addition, the implementation of using cryptography (hash value) merely confines the use of the abstract idea to a particular technological environment or field of use (cryptography). MPEP 2106.04(d)(l) and MPEP 2106.05(A) indicate that merely “generally linking” the abstract idea to a particular technological environment or field of use cannot provide a practical application or significantly more. Therefore, dependent claims 2-8, 11-14 and 16-20 are considered patent ineligible for the reasons given above.
Claim Rejections - 35 USC § 103
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.
Claim(s) 1-8, and 10-20 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar (US 20220327538 A1), in view of Roy (US 20230245009 A1), in view of Miura (JP2023168121A), and in further view of Chen (TW I872336 B).
Regarding Claim 1, and Claim 10
Kumar discloses, A device, comprising: a processor; a memory communicatively coupled to the processor; and (Kumar Par. 0122-0125).
a sustainability logic, configured to: receive one or more normalized Carbon Footprint Metrics (CFMs) "The present invention is directed to monitoring and assessing the entire carbon chain or footprint of an enterprise from source to recycle or reuse. The entire carbon chain or footprint of the enterprise includes for example tracking, monitoring and assessing the carbon usage or generation associated with the raw materials that are sourced for making for example a device or a building or equipment, the activities associated with transporting the raw materials to a processing or production location, the processing of the raw materials, the activities associated with assembling or manufacturing the designed product, the activities associated with the storing, distributing, and the selling of the product to customers including the enterprise, and customers using the product. The carbon chain also includes activities associated with the enterprise (e.g., customer), such as operating their facilities, the reuse or recycling of emissions or materials, and the like. Specifically, the environmental data including emission data, the enriched data, the machine learning models and techniques applied to the data, and the insights and conclusions generated by the enrichment unit can be stored in a blockchain of a digital trust infrastructure unit, thus enabling the system to cryptographically verify and store the logic and structure applied to the data so as to curate the data. The stored and verifiable data can also be used for subsequent reporting and analysis. The present invention is directed to a data collection and processing system comprising a plurality of data sources for generating environmental data and a data analysis module for receiving the environmental data from the plurality of data sources. The data analysis module includes an enrichment unit for storing and enriching the environmental data from the plurality of data sources to form enriched environmental data. The enrichment unit includes a financial subsystem for analyzing and processing the environmental data and for generating financial data and non-financial data therefrom. The data analysis module also includes a digital trust infrastructure unit for storing the financial data and the non-financial data, where the enriched environmental data or the environmental data is stored in the data layer in a secure and verifiable format. The system also includes a post-processing unit for processing the environmental data and the financial data stored in the digital trust infrastructure so as to generate one or more reports from the environmental data and the financial data. The data sources include a plurality of measuring devices coupled to one or more structures for measuring one or more selected parameters including one or more of power generation, power consumption, humidity, occupancy, and emissions of various fluids and gases, to form the environmental data. The data sources can also include pre-stored data including data from data libraries related to the parameters being measured by the measurement devices. The environmental data and associated attribute data can be scored and then ranked, and then the resulting ranked environmental data can be normalized. The environmental data can be normalized by applying thereto standards data from one or more related or relevant standards and regulation data from one or more related or relevant regulations" (Kumar Par. 0006-0009).
corresponding to a timeframe; "The devices are configured to generate the environmental data and includes one or more attributes associated therewith. The devices can include, for example, one or more sensors. The partition unit comprises a scoring unit for determining based on the environmental data generated by the devices a data attribute score associated with each device, where the data attribute score corresponds to the number of attributes associated with each device, and a ranking unit for ranking the devices based on the data attribute score. The ranking unit is configured to rank the devices based on a reliability of the device. According to one practice, the ranking unit is configured to check the reliability of the device by analyzing output data of the devices over a selected period of time and by comparing the output data to a preselected device output data range. The ranking unit is also configured to determine the reliability of the device based on the output data generated by one or more additional devices" (Kumar Par. 0015).
generate, in response to a sum of the one or more normalized CFMs being less than a carbon footprint threshold, a Zero Knowledge (ZK) attestation by: "As shown in FIG. 11, the estimate of the total emissions of the enterprise 183 and the estimate of the net impact of the climate actions of the enterprise 207 can be utilized by the system to estimate the net emissions of the enterprise (e.g., enterprise A), step 208. The system 10 can compare the net emission amounts to a threshold level, such as a cap level, established for the individual clusters within the operational boundaries of an enterprise in accordance with one or more sustainability development target initiatives (SBTi) or enterprise determined climate or decarbonization goals, step 210. If the net emission total or amounts are less than a cap level, then the difference between the threshold and the net amounts can be tokenized, such as by the token creation unit 60, to create a carbon credit, step 212. The tokens can be published, if desired, to a carbon credit marketplace for sale by the enterprise. The tokenized carbon credit can be sold to another enterprise through the marketplace or directly thereto, step 214. The transaction details associated with the sale of the carbon credit can be recorded, such as to the blockchain 20A, step 216" (Kumar Par. 01117).
generate a verifiable ZK proof based on the ZK attestation; and "The blockchain 20A thus functions as a decentralized or distributed ledger having data associated with each block that can be subsequently reviewed and/or processed. The data in the blockchain can be tracked, traced, and presented chronologically in a cryptographically-verified ledger format of the blockchain to each participant of the blockchain. As such, the blockchain can provide an audit trail corresponding to all of the data in the blocks, and thus can determine who interacted with the data and when, as well as the sources of the data and any actions taken in response to the data. According to one embodiment, each node of the blockchain network can include one or more computer servers which provides processing capability and memory storage. Any changes made by any of the nodes to a corresponding block in the blockchain are automatically reflected in every other ledger in the blockchain. As such, with the distributed ledger format in the blockchain, provenance can be provided with the dissemination of identical copies of the ledger, which has cryptographic proof of its validity, to each of the nodes in the network. Consequently, all of the various types of data (e.g., original data, enriched data, the software and models and techniques employed to enrich the data, and the insights and recommendations generated therefrom) can be stored in the blockchain 20A, and the blockchain 20A can be used to verify, prove and create an immutable record of the data, various rule based models and techniques, risk models, and machine learning and artificial intelligence models and techniques stored therein as well as to track users accessing the data and any associated insights generated by the enrichment unit" (Kumar Par. 0062).
transmit the verifiable ZK proof to an auditing device; "The data stored in the blockchain 20A of the digital trust infrastructure unit 20 can be viewed, retrieved and processed using the post-processing unit 24. For example, the post-processing unit 24 can include one or more software applications that processes and integrates the data stored in the digital trust infrastructure unit 20 so as to generate one or more reports that are configured to provide information to a system user that is related to the data. For example, the post-processing unit 24 can employ data visualization software that analyzes the data and then displays the data in selected visualization formats, such as graph-type visualization formats. The post-processing unit 24 can also be configured to create standardized and configurable reports for clients specific to their jurisdictional compliance …. The display region can include one or more displays or monitors for displaying the reports. The displays can be separate display devices or can form part of any suitable electronic device, such as for example a computer, tablet or smartphone" (Kumar Par. 0063). “The illustrated method can also include a prove step 112 for processing, enriching and validating or verifying the emissions data. …The method employed by the data collection and processing system 10 can also include a process for assuring the data, step 112E, by analyzing or comparing the data to established accounting and estimation standards and principles as a way to improve the confidence score of or confidence in the environmental or emissions data, as well as confidence in any information derived from the data for decision makers” (Kumar Par. 0087). “The system then can process and record the emission data attributes associated with each emission contributors and/or climate action performed so as to verify the environmental data of each climate action of the cluster or the enterprise, step 188. That is, the system verifies the emissions attributes of each climate action taken by the enterprise for a selected cluster. The environmental data (e.g., emission data) of each climate action taken by the enterprise is processed by the partition unit 130 to improve the fidelity or veracity of the environmental data, step 190” (Kumar Par. 0115).
based on the one or more normalized CFMs; and "The data can also include power related data that includes for example the consumption of power by different types of building equipment to maintain occupant comfort, air quality, lighting, and the like, as well as power data related to the generation of power from any selected power source and/or feedstock, including for example oil-based power generation, gas-based power generation, coal-based power generation, solar energy, nuclear-based power generation, hydrogen-based power generation, wind energy, or tidal or water generated energy, and any emissions data associated therewith" (Kumar Par. 0048). " The data analysis module also includes a digital trust infrastructure unit for storing the financial data and the non-financial data, where the enriched environmental data or the environmental data is stored in the data layer in a secure and verifiable format. The system also includes a post-processing unit for processing the environmental data and the financial data stored in the digital trust infrastructure so as to generate one or more reports from the environmental data and the financial data. …The environmental data and associated attribute data can be scored and then ranked, and then the resulting ranked environmental data can be normalized. The environmental data can be normalized by applying thereto standards data from one or more related or relevant standards and regulation data from one or more related or relevant regulations" (Kumar Par. 0008-0009).
Kumar discloses receiving carbon metrics corresponding to a time frame, generating attestation of a sum is less than a threshold, generating proof based on the attestation, and transmitting the proof to an auding device to prove compliance with the carbon footprint threshold, but fails to disclose determining a key value and an offset value based on the one or more normalized CFMs and the carbon footprint threshold such that a sum of the one or more normalized CFMs and the offset value is greater than the carbon footprint threshold, applying a hash on the key value, determining an actual energy usage of the device, and controlling an energy consumption of the device dynamically such that the actual energy usage of the device is less than a maximum energy usage indicated by the carbon footprint threshold. Roy, however, discloses determining a carbon footprint of the computing devices based on the utilization data and the location data and comparing the carbon footprint against a carbon footprint threshold. Roy teaches:
determine an actual energy usage of the device "In another implementation utilization data may correspond to peripheral utilization data. A reference usage in watts per minute may be extracted from the telemetry agent. The processor 102 may calculate the peripheral active time by determining the active time of the host computing device. A peripheral energy usage may be the peripheral active time multiplied by the watts per minute. The peripheral energy usage may be stored as part of the set of utilization data. In another implementation utilization data may correspond to connected network devices. In this implementation, a reference usage in watts per minute may be extracted from the telemetry agent on the connected network device. A connected network energy usage may be the reference usage multiplied by twenty four hours (as network connected device is available all day). The network connected device energy usage may be stored as part of the set of utilization data" (Roy Par. 0018-0019).
control an energy consumption of the device dynamically such that the actual energy usage of the device is less than a maximum energy usage indicated by the carbon footprint threshold. "In another implementation, the processor 102 may compare the carbon footprint to a carbon footprint threshold. The carbon footprint threshold may correspond to an internal green energy goal of the organization. In another example, the threshold may correspond to governmental regulatory values. Likewise, the worksite or location specific carbon footprints may compare to a worksite or location specific carbon footprint threshold. In this latter example, the worksite or location specific carbon footprint threshold may be utilized to validate that a worksite is complaint with governmental regulatory values. At 210, the processor 102 creates a remediation recommendation. Upon a comparison of a carbon footprint between two resultant carbon footprints, a recommendation may be made. If a site has a higher carbon footprint rate, a remediation system may recommend pushing a known system configuration to a fleet of devices. For example, if an organization receives a comparison between worksites, the larger carbon footprint worksite may receive a recommendation that notebook computers of a certain make and model be configured to run in low performance/energy saver mode. In another example, a recommendation to disable network connected devices in a low utilization area may be created. An endpoint management system may be utilized to push a configuration to a computing device, peripheral or network connected device. Additionally, the recommendation may also include changing of hardware. Older computing devices, peripherals, and network connected devices may be identified with high utilization data (in watts per minute). Those devices may be recommended to be exchanged for more energy efficient models. (Roy Par. 0025-0027).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the monitoring and assessing method of carbon footprint of Kumar with determining an actual energy usage of the device, and controlling an energy consumption of the device dynamically such that the actual energy usage of the device is less than a maximum energy usage indicated by the carbon footprint threshold of Roy to validate that a worksite is complaint with governmental regulatory values (Roy Par. 0025).
The combination of Kumar and Roy disclose a carbon monitoring system with remediations. The combination of Kumar and Roy fail to disclose determining a key value and an offset value based on the one or more normalized CFMs and the carbon footprint threshold such that a sum of the one or more normalized CFMs and the offset value is greater than the carbon footprint threshold, applying a hash on the key value. Alternatively, Miura discloses greenhouse gas emissions. Miura teaches determining a key value and an offset value based on the one or more normalized CFMs and the carbon footprint threshold such that a sum of the one or more normalized CFMs and the offset value is greater than the carbon footprint threshold; and "The control unit 11 determines the difference (gap) between the total amount of GHG emissions and the GHG emissions corresponding to each account item, and the target value of the total amount and the target value corresponding to each account item. If the total amount of GHG emissions exceeds the target value, the control unit 11 refers to the difference between each account item and identifies the account item with the largest amount of excess from the target value as the account item in question. . The control unit 11 determines that the issue is to optimize the amount of GHG emissions related to the account item. The control unit 11 acquires a case corresponding to the task. The control unit 11 outputs the difference, the problem, and the example" (Miura Par. 0097).
Examiner note: The key value is the total amount of emissions, the offset value is the difference (gap), the normalized carbon footprint metrics is the amount of GHG emissions related to the account item, and the threshold is the target value.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar and Roy with determining a key value and an offset value based on the one or more normalized CFMs and the carbon footprint threshold such that the sum of the one or more normalized CFMs and the offset value is greater than the carbon footprint threshold of Miura to determine the amount of GHG corresponding to each item, and the problem with the largest amount of excess (Miura Par. 0097).
The combination of Kumar, Roy and Miura disclose monitoring carbon footprints and determining a key value and offset value based on a threshold. The combination of Kumar, Roy and Miura fail to disclose applying a hash on the key value. Alternatively, Chen discloses a blockchain system for managing carbon footprints. Chen teaches, applying a hash on the key value; “Specifically, the carbon footprint accounting management certificate module 100 generates a carbon footprint accounting management certificate code, a data block (m), and a hash value of the data block (m). The hash value of the carbon footprint accounting management certificate data 120 of the transaction in this embodiment is calculated based on the carbon footprint accounting management certificate code, the accounting certificate, and the unique information identifiable in the carbon footprint record information content” (Chen Par. 0033-0034).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise with an offset and key value of Kumar, Roy and Miura with applying a hash on the key value of Chen to obtain accurate carbon footprints for each activity (Chen Par. 0006).
Regarding Claim 15,
Kumar discloses, (Currently Amended) A device, comprising: a processor; a memory communicatively coupled to the processor; and a sustainability logic, configured to: (Kumar Par. 0122-0125).
receive one or more normalized Carbon Footprint Metrics (CFMs) "The present invention is directed to monitoring and assessing the entire carbon chain or footprint of an enterprise from source to recycle or reuse. The entire carbon chain or footprint of the enterprise includes for example tracking, monitoring and assessing the carbon usage or generation associated with the raw materials that are sourced for making for example a device or a building or equipment, the activities associated with transporting the raw materials to a processing or production location, the processing of the raw materials, the activities associated with assembling or manufacturing the designed product, the activities associated with the storing, distributing, and the selling of the product to customers including the enterprise, and customers using the product. The carbon chain also includes activities associated with the enterprise (e.g., customer), such as operating their facilities, the reuse or recycling of emissions or materials, and the like. Specifically, the environmental data including emission data, the enriched data, the machine learning models and techniques applied to the data, and the insights and conclusions generated by the enrichment unit can be stored in a blockchain of a digital trust infrastructure unit, thus enabling the system to cryptographically verify and store the logic and structure applied to the data so as to curate the data. The stored and verifiable data can also be used for subsequent reporting and analysis. The present invention is directed to a data collection and processing system comprising a plurality of data sources for generating environmental data and a data analysis module for receiving the environmental data from the plurality of data sources. The data analysis module includes an enrichment unit for storing and enriching the environmental data from the plurality of data sources to form enriched environmental data. The enrichment unit includes a financial subsystem for analyzing and processing the environmental data and for generating financial data and non-financial data therefrom. The data analysis module also includes a digital trust infrastructure unit for storing the financial data and the non-financial data, where the enriched environmental data or the environmental data is stored in the data layer in a secure and verifiable format. The system also includes a post-processing unit for processing the environmental data and the financial data stored in the digital trust infrastructure so as to generate one or more reports from the environmental data and the financial data. The data sources include a plurality of measuring devices coupled to one or more structures for measuring one or more selected parameters including one or more of power generation, power consumption, humidity, occupancy, and emissions of various fluids and gases, to form the environmental data. The data sources can also include pre-stored data including data from data libraries related to the parameters being measured by the measurement devices. The environmental data and associated attribute data can be scored and then ranked, and then the resulting ranked environmental data can be normalized. The environmental data can be normalized by applying thereto standards data from one or more related or relevant standards and regulation data from one or more related or relevant regulations" (Kumar Par. 0006-0009).
corresponding to a timeframe; "The devices are configured to generate the environmental data and includes one or more attributes associated therewith. The devices can include, for example, one or more sensors. The partition unit comprises a scoring unit for determining based on the environmental data generated by the devices a data attribute score associated with each device, where the data attribute score corresponds to the number of attributes associated with each device, and a ranking unit for ranking the devices based on the data attribute score. The ranking unit is configured to rank the devices based on a reliability of the device. According to one practice, the ranking unit is configured to check the reliability of the device by analyzing output data of the devices over a selected period of time and by comparing the output data to a preselected device output data range. The ranking unit is also configured to determine the reliability of the device based on the output data generated by one or more additional devices" (Kumar Par. 0015).
based on the one or more normalized CFMs; "The data can also include power related data that includes for example the consumption of power by different types of building equipment to maintain occupant comfort, air quality, lighting, and the like, as well as power data related to the generation of power from any selected power source and/or feedstock, including for example oil-based power generation, gas-based power generation, coal-based power generation, solar energy, nuclear-based power generation, hydrogen-based power generation, wind energy, or tidal or water generated energy, and any emissions data associated therewith" (Kumar Par. 0048). " The data analysis module also includes a digital trust infrastructure unit for storing the financial data and the non-financial data, where the enriched environmental data or the environmental data is stored in the data layer in a secure and verifiable format. The system also includes a post-processing unit for processing the environmental data and the financial data stored in the digital trust infrastructure so as to generate one or more reports from the environmental data and the financial data. …The environmental data and associated attribute data can be scored and then ranked, and then the resulting ranked environmental data can be normalized. The environmental data can be normalized by applying thereto standards data from one or more related or relevant standards and regulation data from one or more related or relevant regulations" (Kumar Par. 0008-0009).
generate a Zero Knowledge (ZK) attestation in response to determining that the sum of the one or more normalized CFMs is less than the carbon footprint threshold by: "As shown in FIG. 11, the estimate of the total emissions of the enterprise 183 and the estimate of the net impact of the climate actions of the enterprise 207 can be utilized by the system to estimate the net emissions of the enterprise (e.g., enterprise A), step 208. The system 10 can compare the net emission amounts to a threshold level, such as a cap level, established for the individual clusters within the operational boundaries of an enterprise in accordance with one or more sustainability development target initiatives (SBTi) or enterprise determined climate or decarbonization goals, step 210. If the net emission total or amounts are less than a cap level, then the difference between the threshold and the net amounts can be tokenized, such as by the token creation unit 60, to create a carbon credit, step 212. The tokens can be published, if desired, to a carbon credit marketplace for sale by the enterprise. The tokenized carbon credit can be sold to another enterprise through the marketplace or directly thereto, step 214. The transaction details associated with the sale of the carbon credit can be recorded, such as to the blockchain 20A, step 216" (Kumar Par. 01117).
Kumar discloses receiving carbon metrics corresponding to a time frame, generating attestation of a sum is less than a threshold, generating proof based on the attestation, and transmitting the proof to an auding device to prove compliance with the carbon footprint threshold, but fails to disclose determining a key value and an offset value based on the one or more normalized CFMs and the carbon footprint threshold such that a sum of the one or more normalized CFMs and the offset value is greater than the carbon footprint threshold, applying a hash on the key value, determining an actual energy usage of the device, and controlling an energy consumption of the device dynamically such that the actual energy usage of the device is less than a maximum energy usage indicated by the carbon footprint threshold. Roy, however, discloses determining a carbon footprint of the computing devices based on the utilization data and the location data and comparing the carbon footprint against a carbon footprint threshold. Roy teaches:
determine an actual energy usage of the device "In another implementation utilization data may correspond to peripheral utilization data. A reference usage in watts per minute may be extracted from the telemetry agent. The processor 102 may calculate the peripheral active time by determining the active time of the host computing device. A peripheral energy usage may be the peripheral active time multiplied by the watts per minute. The peripheral energy usage may be stored as part of the set of utilization data. In another implementation utilization data may correspond to connected network devices. In this implementation, a reference usage in watts per minute may be extracted from the telemetry agent on the connected network device. A connected network energy usage may be the reference usage multiplied by twenty four hours (as network connected device is available all day). The network connected device energy usage may be stored as part of the set of utilization data" (Roy Par. 0018-0019).
compare a sum of the one or more normalized CFMs with a carbon footprint threshold dynamically; Control an energy consumption of the device dynamically such that the actual energy usage of the device is less than a maximum energy usage indicated by the carbon footprint threshold; and "In another implementation, the processor 102 may compare the carbon footprint to a carbon footprint threshold. The carbon footprint threshold may correspond to an internal green energy goal of the organization. In another example, the threshold may correspond to governmental regulatory values. Likewise, the worksite or location specific carbon footprints may compare to a worksite or location specific carbon footprint threshold. In this latter example, the worksite or location specific carbon footprint threshold may be utilized to validate that a worksite is complaint with governmental regulatory values. At 210, the processor 102 creates a remediation recommendation. Upon a comparison of a carbon footprint between two resultant carbon footprints, a recommendation may be made. If a site has a higher carbon footprint rate, a remediation system may recommend pushing a known system configuration to a fleet of devices. For example, if an organization receives a comparison between worksites, the larger carbon footprint worksite may receive a recommendation that notebook computers of a certain make and model be configured to run in low performance/energy saver mode. In another example, a recommendation to disable network connected devices in a low utilization area may be created. An endpoint management system may be utilized to push a configuration to a computing device, peripheral or network connected device. Additionally, the recommendation may also include changing of hardware. Older computing devices, peripherals, and network connected devices may be identified with high utilization data (in watts per minute). Those devices may be recommended to be exchanged for more energy efficient models. (Roy Par. 0025-0027).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the monitoring and assessing method of carbon footprint of Kumar with determining an actual energy usage of the device, and controlling an energy consumption of the device dynamically such that the actual energy usage of the device is less than a maximum energy usage indicated by the carbon footprint threshold of Roy to validate that a worksite is complaint with governmental regulatory values (Roy Par. 0025).
The combination of Kumar and Roy disclose a carbon monitoring system with remediations. The combination of Kumar and Roy fail to disclose determining a key value and an offset value based on the one or more normalized CFMs and the carbon footprint threshold such that a sum of the one or more normalized CFMs and the offset value is greater than the carbon footprint threshold, applying a hash on the key value. Alternatively, Miura discloses greenhouse gas emissions. Miura teaches determining a key value and an offset value based on the one or more normalized CFMs and the carbon footprint threshold such that a sum of the one or more normalized CFMs and the offset value is greater than the carbon footprint threshold; and "The control unit 11 determines the difference (gap) between the total amount of GHG emissions and the GHG emissions corresponding to each account item, and the target value of the total amount and the target value corresponding to each account item. If the total amount of GHG emissions exceeds the target value, the control unit 11 refers to the difference between each account item and identifies the account item with the largest amount of excess from the target value as the account item in question. . The control unit 11 determines that the issue is to optimize the amount of GHG emissions related to the account item. The control unit 11 acquires a case corresponding to the task. The control unit 11 outputs the difference, the problem, and the example" (Miura Par. 0097).
Examiner note: The key value is the total amount of emissions, the offset value is the difference (gap), the normalized carbon footprint metrics is the amount of GHG emissions related to the account item, and the threshold is the target value.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar and Roy with determining a key value and an offset value based on the one or more normalized CFMs and the carbon footprint threshold such that the sum of the one or more normalized CFMs and the offset value is greater than the carbon footprint threshold of Miura to determine the amount of GHG corresponding to each item, and the problem with the largest amount of excess (Miura Par. 0097).
The combination of Kumar, Roy and Miura disclose monitoring carbon footprints and determining a key value and offset value based on a threshold. The combination of Kumar, Roy and Miura fail to disclose applying a hash on the key value. Alternatively, Chen discloses a blockchain system for managing carbon footprints. Chen teaches, applying a hash on the key value “Specifically, the carbon footprint accounting management certificate module 100 generates a carbon footprint accounting management certificate code, a data block (m), and a hash value of the data block (m). The hash value of the carbon footprint accounting management certificate data 120 of the transaction in this embodiment is calculated based on the carbon footprint accounting management certificate code, the accounting certificate, and the unique information identifiable in the carbon footprint record information content” (Chen Par. 0033-0034).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise with an offset and key value of Kumar, Roy and Miura with applying a hash on the key value of Chen to obtain accurate carbon footprints for each activity (Chen Par. 0006).
Regarding Claim 2,
The combination of Kumar, Roy, Miura, and Chen disclose the device of claim 1, as shown above. Kumar further discloses, The device of claim 1, wherein the verifiable ZK proof includes the ZK attestation, a "The digital trust infrastructure unit 20 preferably stores the original data and the enriched data in a trusted and verifiable format. According to one practice, the data can be stored using blockchain technology. In a blockchain 20A, as is known, the original data or the enriched data can be stored in a series of batches or blocks that include among other things a time stamp, a hash value of the data stored in the block, a copy of the hash value from the previous block, as well as other types of information, including for example the origins of the data…. The data in the blockchain can be tracked, traced, and presented chronologically in a cryptographically-verified ledger format of the blockchain to each participant of the blockchain. As such, the blockchain can provide an audit trail corresponding to all of the data in the blocks, and thus can determine who interacted with the data and when, as well as the sources of the data and any actions taken in response to the data" (Kumar Par. 0062).
device identifier corresponding to the device, "According to the present invention, the method initially determines the number and types of emission sources (e.g., emission contributors) associated with a specific cluster (e.g., cluster 142A) and then records this information to form an inventory of emission contributors on the blockchain 20A, step 160. The emissions data (e.g., environmental data) of each of the emission contributors in the inventory list associated with each cluster 142A is then determined and recorded, step 162. The system 10 can also determine the emissions data associated with a set of emissions contributors within a different cluster (e.g., cluster 142B) or from third party sources 110F. The emissions data of each of the emission contributors has attribute data associated therewith. The emission contributors correspond in a sense to data objects in a data model, and each data object has attribute data associated therewith. The attribute data is information about the data object. In the current example, the data objects can correspond to sensors, detectors, transportation, manufacturing, and the like, and the attribute data can be an identification of the types of sensor, location of the sensor, readings associated with the sensor, the purpose of the measurement, operational limits, quality, type of fuel, and the like" (Kumar Par. 0112).
and a time data. "The Party A transactional information is reflected in a data object referenced as Version 1 (V1) in a block 302 of the blockchain 304 (e.g., blockchain transaction log). Block 302 also contains the object key 1234. In addition to the blockchain transaction log 304, the distributed ledger also comprises a world state database 306 that holds the current attributes and attribute values associated with object key 1234 and provided by the SKA. Accordingly, following the Party A transaction, the world state database contains the transactional attributes for Party A (A1, A2, A3) and corresponding attribute values as well as the shared attributes (S1, S2, S3) and corresponding attribute values. In some embodiments the world state database may further include additional metadata, such as a version number of the data object, a timestamp that indicates when the current version was created or updated, an identity of the party and/or user who submitted the current version, etc." (Kumar Par. 0107).
Regarding Claim 3,
The combination of Kumar, Roy, Miura, and Chen disclose the device of claim 2, as shown above. Kumar further discloses, The device of claim 2, wherein the time data includes at least one of: the timeframe, or a timestamp indicative of a time of generation of the verifiable ZK proof. "The Party A transactional information is reflected in a data object referenced as Version 1 (V1) in a block 302 of the blockchain 304 (e.g., blockchain transaction log). Block 302 also contains the object key 1234. In addition to the blockchain transaction log 304, the distributed ledger also comprises a world state database 306 that holds the current attributes and attribute values associated with object key 1234 and provided by the SKA. Accordingly, following the Party A transaction, the world state database contains the transactional attributes for Party A (A1, A2, A3) and corresponding attribute values as well as the shared attributes (S1, S2, S3) and corresponding attribute values. In some embodiments the world state database may further include additional metadata, such as a version number of the data object, a timestamp that indicates when the current version was created or updated, an identity of the party and/or user who submitted the current version, etc." (Kumar Par. 0107).
Regarding Claim 4, and Claim 11
The combination of Kumar, Roy, Miura, and Chen disclose the device of claim 3, and claim 10 as shown above. Chen further discloses, apply the hash on the key value based on at least one of: [the carbon footprint threshold, the offset value, or the sum of the one or more normalized CFMs “Specifically, the carbon footprint accounting management certificate module 100 generates a carbon footprint accounting management certificate code, a data block (m), and a hash value of the data block (m). The hash value of the carbon footprint accounting management certificate data 120 of the transaction in this embodiment is calculated based on the carbon footprint accounting management certificate code, the accounting certificate, and the unique information identifiable in the carbon footprint record information content” (Chen Par. 0033-0034). “More specifically, the carbon footprint accounting management certificate module performs field operations (e.g., associative table operations) based on the data in the accounting certificate data and carbon footprint data read to the nth transaction. In addition to merging the two data columns and presenting them together, it also adds fields for the total carbon footprint of each item and the subtotal carbon footprint of each stage of the item life cycle. The field content includes: (1) The total carbon emissions generated by a certain item in the nth transaction subject, which is calculated as the sum of the "unit carbon footprint value" of each item in the transaction subject multiplied by the "transaction quantity" (Chen Par. 0052). "As a preferred solution of the present invention, step S22 specifically includes: the carbon emission related data is stored in the block in the form of a binary tree Merkle tree, each carbon emission related data has a hash value, and the hash values corresponding to the two carbon emission related data are combined and then hashed to form a unique Merkle root of the block, which is stored in the block header; if any data is tampered with, the hash value corresponding to the tampered data will also be changed, and the tampered data can be found by tracing back from the Merkle root to the leaf node according to the Merkle tree." (Chen Par. 0040). "The Merkle tree, also known as the hash tree, is an algorithm for data storage in blockchain technology. In a Merkle tree, each node is labeled with a cryptographic hash value of a data block. The Merkle tree is a tree data structure that can be a binary tree or a multi-branch tree and has all the characteristics of a tree structure. The value on the leaf node of the Merkle tree is the data to be stored, and the value of the non-leaf node is the hash value obtained by combining all the child nodes of the node and then performing a hash calculation on the combined result" (Chen Par. 0099).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise with an offset and key value of Kumar, Roy, Miura, and Chen with applying the hash on the key value based on at least one of the carbon footprint threshold, the offset value, or the sum of the one or more normalized CFMs of Chen to obtain accurate carbon footprints for each activity (Chen Par. 0006).
Regarding Claim 5,
The combination of Kumar, Roy, Miura, and Chen disclose the device of claim 4. Kumar further discloses, The device of claim 4, the verifiable ZK proof based on the carbon footprint threshold. "As shown in FIG. 11, the estimate of the total emissions of the enterprise 183 and the estimate of the net impact of the climate actions of the enterprise 207 can be utilized by the system to estimate the net emissions of the enterprise (e.g., enterprise A), step 208. The system 10 can compare the net emission amounts to a threshold level, such as a cap level, established for the individual clusters within the operational boundaries of an enterprise in accordance with one or more sustainability development target initiatives (SBTi) or enterprise determined climate or decarbonization goals, step 210. If the net emission total or amounts are less than a cap level, then the difference between the threshold and the net amounts can be tokenized, such as by the token creation unit 60, to create a carbon credit, step 212. The tokens can be published, if desired, to a carbon credit marketplace for sale by the enterprise. The tokenized carbon credit can be sold to another enterprise through the marketplace or directly thereto, step 214. The transaction details associated with the sale of the carbon credit can be recorded, such as to the blockchain 20A, step 216" (Kumar Par. 01117).
Chen further discloses, wherein the verifiable ZK proof is verified by the auditing device by applying the hash "stores the carbon footprint accounting management certificate data 120 in the data block (m) in the blockchain 200 . Specifically, the carbon footprint accounting management voucher module 100 will generate the carbon footprint accounting management voucher code, the data block (m) and the hash value (Hash Value) of the data block (m)”. (Chen Par. 0033). “The carbon footprint accounting management voucher module 100 can also confirm whether it is necessary to request a third-party agency (third-party verification module 110) to verify the carbon footprint accounting management voucher data of the nth transaction subject according to the preset response conditions. If necessary, it can be uploaded After carbon footprint accounting manages the voucher data (generates the data block and its hash value), it requests the third-party verification module 110 to confirm whether the content of the data block is correct. At this time, the hash value can be calculated in addition to accounting documents and carbon footprint record information” (Chen Par. 0035).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Roy, Miura, and Chen with the verifiable proof being verified by a device by applying a hash of Chen to obtain accurate carbon footprints for each activity (Chen Par. 0006).
Regarding Claim 6, and Claim 12
The combination of Kumar, Roy, Miura, Chen, disclose the device of claim 5, and device of claim 11, as shown above. Kumar further discloses, The device of claim 5, wherein the sustainability logic is further configured to: generate the verifiable ZK proof if the sum of the one or more normalized CFMs is less than the carbon footprint threshold; and "As shown in FIG. 11, the estimate of the total emissions of the enterprise 183 and the estimate of the net impact of the climate actions of the enterprise 207 can be utilized by the system to estimate the net emissions of the enterprise (e.g., enterprise A), step 208. The system 10 can compare the net emission amounts to a threshold level, such as a cap level, established for the individual clusters within the operational boundaries of an enterprise in accordance with one or more sustainability development target initiatives (SBTi) or enterprise determined climate or decarbonization goals, step 210. If the net emission total or amounts are less than a cap level, then the difference between the threshold and the net amounts can be tokenized, such as by the token creation unit 60, to create a carbon credit, step 212. The tokens can be published, if desired, to a carbon credit marketplace for sale by the enterprise. The tokenized carbon credit can be sold to another enterprise through the marketplace or directly thereto, step 214. The transaction details associated with the sale of the carbon credit can be recorded, such as to the blockchain 20A, step 216" (Kumar Par. 01117).
Roy further teaches: compare the sum of the one or more normalized CFMs with the carbon footprint threshold dynamically; "At 208, the processor 102 compares a carbon footprint. The processor 102 may compare location specific aggregate carbon footprints. As a resultant value may be in kg of CO2 per year, a numeric comparison operator may be suited for the comparison. For example, worksite A may produce a total X kg of Caper year compared to worksite B which produces a total X-20 kg of CO2 per year. In this example, worksite A may have a larger overall carbon footprint. In another example, worksite A hosts Y computing devices, peripherals and network connected devices, while worksite B hosts Y-400 computing devices, peripherals and network connected devices. In this example, worksite A has a lower per device carbon footprint. Likewise, different organizations may be compared for overall carbon footprints, site carbon footprints, and per device carbon footprints. In another implementation, the processor 102 may compare the carbon footprint to a carbon footprint threshold. The carbon footprint threshold may correspond to an internal green energy goal of the organization. In another example, the threshold may correspond to governmental regulatory values. Likewise, the worksite or location specific carbon footprints may compare to a worksite or location specific carbon footprint threshold. In this latter example, the worksite or location specific carbon footprint threshold may be utilized to validate that a worksite is complaint with governmental regulatory values." (Roy Par. 0024-0025).
adjust an energy consumption of the device dynamically if the sum of the one or more normalized CFMs is not less than the carbon footprint threshold. "[0026] At 210, the processor 102 creates a remediation recommendation. Upon a comparison of a carbon footprint between two resultant carbon footprints, a recommendation may be made. If a site has a higher carbon footprint rate, a remediation system may recommend pushing a known system configuration to a fleet of devices. For example, if an organization receives a comparison between worksites, the larger carbon footprint worksite may receive a recommendation that notebook computers of a certain make and model be configured to run in low performance/energy saver mode. In another example, a recommendation to disable network connected devices in a low utilization area may be created. An endpoint management system may be utilized to push a configuration to a computing device, peripheral or network connected device" (Roy Par. 0026).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Roy, Miura, and Chen, with comparing the sum of the one or more normalized CFMs with the carbon footprint threshold dynamically, and adjusting an energy consumption of the device dynamically if the sum of the one or more normalized CFMs is not less than the carbon footprint threshold of Roy to validate that a worksite is complaint with governmental regulatory values (Roy Par. 0025).
Regarding Claim 7,
The combination of Kumar, Roy, Miura, and Chen disclose the device of claim 1, as shown above. Kumar further discloses, The device of claim 1, wherein the one or more normalized CFMs correspond to at least one of: a single greenhouse gas metric, multiple greenhouse gas metrics, or a composite sustainability metric. "The data collection and processing system 10 of the present invention can measure, collect and calculate the different greenhouse gas (GHG) emissions from the operation related energy consumption of the enterprise for climate accounting purposes. The data collection and processing system 10 can also be configured to manage the emissions of the building as well as the related auditing functions, including monitoring, audit and control of the environmental parameters of the building. The system 10 can also be configured to optimize the environmental performance of the building and reduce the operational costs of the building, while concomitantly reporting the climate impact of the building in an accurate and transparent manner" (Kumar Par. 0076). "The normalization unit 100 thus generates normalized emissions data associated with the clusters and the enterprise. The equations used to estimate emissions for the cluster(s) and enterprise can be summarized as…. K is the number of greenhouse gases in a natural resource consumed by the built and operated system ‘a’ and any of its subsystem or component systems in the cluster i in the operational boundary of an enterprise and its suppliers" (Kumar Par. 0113).
Regarding Claim 8, and Claim 14, and Claim 20
The combination of Kumar, Roy, Miura, and Chen disclose the device of claim 1, and method of claim 10, and device of claim 15 as shown above. Kumar further discloses: wherein the sustainability logic is further configured to: collect a real-time telemetry data indicative of a diverse sustainability data; and " The data collection and processing system 10 of the present invention for example can employ data received from sensors, detectors, and other data sources related to emissions emitters of the enterprise, as well as employ other types of environmental data, including for example water usage, real estate or land use, waste generation and the like. The information can be collected from the various data sources via suitable measuring devices, such as meters, as well as from non-device third parties. The system 10 can also evaluate the impact of the different decarbonization paths that enterprises can adopt or pursue to account for emissions reduction while assessing the effectiveness of the paths to achieve the climate goals of the enterprise." (Kumar Par. 0084).
generate the one or more normalized CFMs based on the real-time telemetry data. "As shown in FIG. 11, the estimate of the total emissions of the enterprise 183 and the estimate of the net impact of the climate actions of the enterprise 207 can be utilized by the system to estimate the net emissions of the enterprise (e.g., enterprise A), step 208. The system 10 can compare the net emission amounts to a threshold level, such as a cap level, established for the individual clusters within the operational boundaries of an enterprise in accordance with one or more sustainability development target initiatives (SBTi) or enterprise determined climate or decarbonization goals, step 210. If the net emission total or amounts are less than a cap level, then the difference between the threshold and the net amounts can be tokenized, such as by the token creation unit 60, to create a carbon credit, step 212. The tokens can be published, if desired, to a carbon credit marketplace for sale by the enterprise. The tokenized carbon credit can be sold to another enterprise through the marketplace or directly thereto, step 214. The transaction details associated with the sale of the carbon credit can be recorded, such as to the blockchain 20A, step 216" (Kumar Par. 01117). "The emissions data of each of the emission contributors has attribute data associated therewith. The emission contributors correspond in a sense to data objects in a data model, and each data object has attribute data associated therewith. The attribute data is information about the data object. In the current example, the data objects can correspond to sensors, detectors, transportation, manufacturing, and the like, and the attribute data can be an identification of the types of sensor, location of the sensor, readings associated with the sensor, the purpose of the measurement, operational limits, quality, type of fuel, and the like" (Kumar Par. 0112).
Regarding Claim 13, and Claim 19
The combination of Kumar, Roy, Miura, and Chen disclose the method of claim 12, and device of claim 18 as shown above. Kumar further discloses, the verifiable ZK proof based on the carbon footprint threshold. "As shown in FIG. 11, the estimate of the total emissions of the enterprise 183 and the estimate of the net impact of the climate actions of the enterprise 207 can be utilized by the system to estimate the net emissions of the enterprise (e.g., enterprise A), step 208. The system 10 can compare the net emission amounts to a threshold level, such as a cap level, established for the individual clusters within the operational boundaries of an enterprise in accordance with one or more sustainability development target initiatives (SBTi) or enterprise determined climate or decarbonization goals, step 210. If the net emission total or amounts are less than a cap level, then the difference between the threshold and the net amounts can be tokenized, such as by the token creation unit 60, to create a carbon credit, step 212. The tokens can be published, if desired, to a carbon credit marketplace for sale by the enterprise. The tokenized carbon credit can be sold to another enterprise through the marketplace or directly thereto, step 214. The transaction details associated with the sale of the carbon credit can be recorded, such as to the blockchain 20A, step 216" (Kumar Par. 01117).
Chen further discloses, the verifiable ZK proof by applying the hash "stores the carbon footprint accounting management certificate data 120 in the data block (m) in the blockchain 200 . Specifically, the carbon footprint accounting management voucher module 100 will generate the carbon footprint accounting management voucher code, the data block (m) and the hash value (Hash Value) of the data block (m)”. (Chen Par. 0033). “The carbon footprint accounting management voucher module 100 can also confirm whether it is necessary to request a third-party agency (third-party verification module 110) to verify the carbon footprint accounting management voucher data of the nth transaction subject according to the preset response conditions. If necessary, it can be uploaded After carbon footprint accounting manages the voucher data (generates the data block and its hash value), it requests the third-party verification module 110 to confirm whether the content of the data block is correct. At this time, the hash value can be calculated in addition to accounting documents and carbon footprint record information” (Chen Par. 0035).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Roy, Miura, and Chen with the verifiable ZK proof by applying the hash of Chen to obtain accurate carbon footprints for each activity (Chen Par. 0006).
Regarding Claim 16,
The combination of Kumar, Roy, Miura, and Chen disclose the device of claim 15, as shown above. Kumar further discloses, wherein the sustainability logic is further configured to: generate a verifiable ZK proof that includes the ZK attestation, "The digital trust infrastructure unit 20 preferably stores the original data and the enriched data in a trusted and verifiable format. According to one practice, the data can be stored using blockchain technology. In a blockchain 20A, as is known, the original data or the enriched data can be stored in a series of batches or blocks that include among other things a time stamp, a hash value of the data stored in the block, a copy of the hash value from the previous block, as well as other types of information, including for example the origins of the data…. The data in the blockchain can be tracked, traced, and presented chronologically in a cryptographically-verified ledger format of the blockchain to each participant of the blockchain. As such, the blockchain can provide an audit trail corresponding to all of the data in the blocks, and thus can determine who interacted with the data and when, as well as the sources of the data and any actions taken in response to the data" (Kumar Par. 0062).
a device identifier corresponding to the device, "According to the present invention, the method initially determines the number and types of emission sources (e.g., emission contributors) associated with a specific cluster (e.g., cluster 142A) and then records this information to form an inventory of emission contributors on the blockchain 20A, step 160. The emissions data (e.g., environmental data) of each of the emission contributors in the inventory list associated with each cluster 142A is then determined and recorded, step 162. The system 10 can also determine the emissions data associated with a set of emissions contributors within a different cluster (e.g., cluster 142B) or from third party sources 110F. The emissions data of each of the emission contributors has attribute data associated therewith. The emission contributors correspond in a sense to data objects in a data model, and each data object has attribute data associated therewith. The attribute data is information about the data object. In the current example, the data objects can correspond to sensors, detectors, transportation, manufacturing, and the like, and the attribute data can be an identification of the types of sensor, location of the sensor, readings associated with the sensor, the purpose of the measurement, operational limits, quality, type of fuel, and the like" (Kumar Par. 0112).
and a time data; and "The Party A transactional information is reflected in a data object referenced as Version 1 (V1) in a block 302 of the blockchain 304 (e.g., blockchain transaction log). Block 302 also contains the object key 1234. In addition to the blockchain transaction log 304, the distributed ledger also comprises a world state database 306 that holds the current attributes and attribute values associated with object key 1234 and provided by the SKA. Accordingly, following the Party A transaction, the world state database contains the transactional attributes for Party A (A1, A2, A3) and corresponding attribute values as well as the shared attributes (S1, S2, S3) and corresponding attribute values. In some embodiments the world state database may further include additional metadata, such as a version number of the data object, a timestamp that indicates when the current version was created or updated, an identity of the party and/or user who submitted the current version, etc." (Kumar Par. 0107).
transmit the verifiable ZK proof based on the ZK attestation to an auditing device. "The data stored in the blockchain 20A of the digital trust infrastructure unit 20 can be viewed, retrieved and processed using the post-processing unit 24. For example, the post-processing unit 24 can include one or more software applications that processes and integrates the data stored in the digital trust infrastructure unit 20 so as to generate one or more reports that are configured to provide information to a system user that is related to the data. For example, the post-processing unit 24 can employ data visualization software that analyzes the data and then displays the data in selected visualization formats, such as graph-type visualization formats. The post-processing unit 24 can also be configured to create standardized and configurable reports for clients specific to their jurisdictional compliance requirements, as well as provide business insights and associated analytics from the data. The reports can also be industry specific, domain specific, or can generate or create reports that relate to risk monitoring and controls. The reports can include financial reports and the like. According to one practice, the reports can include, when processing environmental data, an emission history report, water usage report and other enterprise (e.g., building) specific reports, as well as provide a summary dashboard showing selected metrics or parameters, including building efficiency and the like. An example of suitable data visualization software includes the various software applications products from Tableau Software, USA. An example of a suitable data integration and business analytics software includes the various software applications from Qlik. The reports generated by the post-processing unit 24 can be displayed in a display region 50. The display region can include one or more displays or monitors for displaying the reports. The displays can be separate display devices or can form part of any suitable electronic device, such as for example a computer, tablet or smartphone" (Kumar Par. 0063).
Regarding Claim 17,
The combination of Kumar, Roy, Miura, and Chen disclose the device of claim 16, as shown above. Kumar further discloses, wherein the time data includes at least one of: the timeframe, or a timestamp indicative of a time of generation of the verifiable ZK proof. "The Party A transactional information is reflected in a data object referenced as Version 1 (V1) in a block 302 of the blockchain 304 (e.g., blockchain transaction log). Block 302 also contains the object key 1234. In addition to the blockchain transaction log 304, the distributed ledger also comprises a world state database 306 that holds the current attributes and attribute values associated with object key 1234 and provided by the SKA. Accordingly, following the Party A transaction, the world state database contains the transactional attributes for Party A (A1, A2, A3) and corresponding attribute values as well as the shared attributes (S1, S2, S3) and corresponding attribute values. In some embodiments the world state database may further include additional metadata, such as a version number of the data object, a timestamp that indicates when the current version was created or updated, an identity of the party and/or user who submitted the current version, etc." (Kumar Par. 0107).
Regarding Claim 18,
The combination of Kumar, Roy, Miura, and Chen disclose the device of claim 16, as shown above. Chen further discloses, apply the hash on the key value based on at least one of: the carbon footprint threshold, the offset value, or the sum of the one or more normalized CFMs “Specifically, the carbon footprint accounting management certificate module 100 generates a carbon footprint accounting management certificate code, a data block (m), and a hash value of the data block (m). The hash value of the carbon footprint accounting management certificate data 120 of the transaction in this embodiment is calculated based on the carbon footprint accounting management certificate code, the accounting certificate, and the unique information identifiable in the carbon footprint record information content” (Chen Par. 0033-0034). “More specifically, the carbon footprint accounting management certificate module performs field operations (e.g., associative table operations) based on the data in the accounting certificate data and carbon footprint data read to the nth transaction. In addition to merging the two data columns and presenting them together, it also adds fields for the total carbon footprint of each item and the subtotal carbon footprint of each stage of the item life cycle. The field content includes: (1) The total carbon emissions generated by a certain item in the nth transaction subject, which is calculated as the sum of the "unit carbon footprint value" of each item in the transaction subject multiplied by the "transaction quantity" (Chen Par. 0052). "As a preferred solution of the present invention, step S22 specifically includes: the carbon emission related data is stored in the block in the form of a binary tree Merkle tree, each carbon emission related data has a hash value, and the hash values corresponding to the two carbon emission related data are combined and then hashed to form a unique Merkle root of the block, which is stored in the block header; if any data is tampered with, the hash value corresponding to the tampered data will also be changed, and the tampered data can be found by tracing back from the Merkle root to the leaf node according to the Merkle tree." (Chen Par. 0040). "The Merkle tree, also known as the hash tree, is an algorithm for data storage in blockchain technology. In a Merkle tree, each node is labeled with a cryptographic hash value of a data block. The Merkle tree is a tree data structure that can be a binary tree or a multi-branch tree and has all the characteristics of a tree structure. The value on the leaf node of the Merkle tree is the data to be stored, and the value of the non-leaf node is the hash value obtained by combining all the child nodes of the node and then performing a hash calculation on the combined result" (Chen Par. 0099).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise with an offset and key value of Kumar, Roy, Miura, and Chen with applying a hash on the key value based on at least one of the carbon footprint threshold, the offset value, or the sum of the one or more normalized CFMs to generate the ZK attestation of Chen to obtain accurate carbon footprints for each activity (Chen Par. 0006).
Regarding Claim 19,
The combination of Kumar, Roy, Miura, and Chen disclose the device of claim 18, as shown above. Kumar further discloses, The device of claim 18, wherein the verifiable ZK proof based on the carbon footprint threshold. "As shown in FIG. 11, the estimate of the total emissions of the enterprise 183 and the estimate of the net impact of the climate actions of the enterprise 207 can be utilized by the system to estimate the net emissions of the enterprise (e.g., enterprise A), step 208. The system 10 can compare the net emission amounts to a threshold level, such as a cap level, established for the individual clusters within the operational boundaries of an enterprise in accordance with one or more sustainability development target initiatives (SBTi) or enterprise determined climate or decarbonization goals, step 210. If the net emission total or amounts are less than a cap level, then the difference between the threshold and the net amounts can be tokenized, such as by the token creation unit 60, to create a carbon credit, step 212. The tokens can be published, if desired, to a carbon credit marketplace for sale by the enterprise. The tokenized carbon credit can be sold to another enterprise through the marketplace or directly thereto, step 214. The transaction details associated with the sale of the carbon credit can be recorded, such as to the blockchain 20A, step 216" (Kumar Par. 01117).
Chen further discloses, the verifiable ZK proof is verified by applying the hash on "stores the carbon footprint accounting management certificate data 120 in the data block (m) in the blockchain 200 . Specifically, the carbon footprint accounting management voucher module 100 will generate the carbon footprint accounting management voucher code, the data block (m) and the hash value (Hash Value) of the data block (m)”. (Chen Par. 0033). “The carbon footprint accounting management voucher module 100 can also confirm whether it is necessary to request a third-party agency (third-party verification module 110) to verify the carbon footprint accounting management voucher data of the nth transaction subject according to the preset response conditions. If necessary, it can be uploaded After carbon footprint accounting manages the voucher data (generates the data block and its hash value), it requests the third-party verification module 110 to confirm whether the content of the data block is correct. At this time, the hash value can be calculated in addition to accounting documents and carbon footprint record information” (Chen Par. 0035).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Roy, Miura, and Chen with the verifiable ZK proof by applying the hash of Chen to obtain accurate carbon footprints for each activity (Chen Par. 0006).
Response to Arguments
Applicant's arguments filed 04/0 with respect to 35 U.S.C. § 101, have been fully considered but they are not persuasive. Applicant argues that the independent claims now recite the allowable feature of controlling an energy consumption of the device dynamically such that the actual energy usage of the device is less than a maximum energy usage indicated by the carbon footprint threshold, and that the dynamic control of physical energy consumption constitutes a practical application that integrates any alleged abstract idea into the tangible functioning of the device, and because the claims are anchored to this specific, physical, and allowable technological improvement, they provide significantly more than any judicial exception. The Examiner respectfully disagrees. MPEP 2106.04(d)(1) states "the word 'improvements' in the context of this consideration is limited to improvements to the functioning of a computer or any other technology/technical field, whether in Step 2A Prong Two or in Step 2B." Here, there is no improvement to the technological environment to which the claims are confined (a general purpose computer); put another way, the computer is implementing what it was programmed to implement. The computer did not cause the problem of the energy usage to be outside of a threshold. Further, the claims do not recite any particular technique for improving how the energy consumption is controlled. Rather, the limitation merely recites the desired result of controlling energy consumption and does not recite any particular technological technique, control algorithm, hardware architecture or other technical implementation for accomplishing that result. The claim is silent as to how the energy consumption is dynamically controlled. For example, the claim does not distinguish between sophisticated power-management techniques and routine actions that simply reduce or discontinue operation of the device. Merely performing an abstract idea process more efficiently using generic computer components does not render the claims patent-eligible. Further, allowable subject matter over prior art is not persuasive because the requirements for eligibility, patentability under U.S.C. 102 and 103 with respect to prior art is neither required for, nor a guarantee of patent eligibility under 35 U.S.C. 101. The distinction between eligibility (under 35 U.S.C. 101) and patentability over the art (under 35 U.S.C. 102 and/or 103) is further discussed in MPEP 2106.05(d).
Applicant's arguments filed 04/0 with respect to 35 U.S.C. § 103, have been fully considered but they are not persuasive. The Applicant amended claim 1 to include allowable subject matter previously disclosed in the Final Rejection on 01/07/2026, however, the allowable subject matter was based off on dependent claims. The dependent claim(s) were not incorporated into the independent claim(s). In light of the amendments, a new grounds of rejection has been made, and the remaining arguments are moot.
Conclusion
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/E.M.K./Examiner, Art Unit 3626
/JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626
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