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 1-20 have been examined and are pending in this Final Rejection. Claims 1-20 are currently rejected.
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 a Zero Knowledge (ZK) attestation if a sum of the one or more normalized CFMs is less than a carbon footprint threshold;
generate a verifiable ZK proof based on the ZK attestation; and
transmit the verifiable ZK proof […] to prove compliance with the carbon footprint threshold without disclosing the one or more normalized CFMs, as drafted, are processes that, under the broadest reasonable interpretation, 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. 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 2-9, 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. Claim(s) 9 merely describe(s) the sustainability logic further configured to determine an actual energy usage of the device based on the normalized CFM, 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 threshold.. Therefore claims 2, 3, 6, 7, 9, 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 2-9, 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, 2, 3, 7 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar (US 20220327538 A1), in view of Beveridge (US 20250028761 A1).
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 a Zero Knowledge (ZK) attestation if a sum of the one or more normalized CFMs is less than a 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).
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 to prove compliance with the carbon footprint threshold . "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).
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 proving compliance without disclosing data. Beveridge, however, discloses publishing metadata to a blockchain network. The metadata can contain properties of data generated by a system. The metadata can allow for other entities to validate or trust the data generated by the system. Beveridge teaches:
to prove compliance with the " The configuration smart contract 156 can be used to store and maintain data on the blockchain related to the operation of the management service 113 and the management agent 139. For example, the configuration smart contract 156 could maintain one or more state records 157, which could be stored on the blockchain 153. Each state record 157 could represent the current configuration state 136 for a client device 106. However, because the blockchain 153 may be publicly accessible, it could be undesirable to store the current configuration state 136 itself on the blockchain 153. Accordingly, a state record 157 could include a device identifier 133 for a specific client device 106 and a state zero-knowledge proof (ZKP) 159 that represents the current state of the client device 106. The management agent 139 could generate the state ZKP 163 and submit it to the configuration smart contract 156 to store on the blockchain 153 to prove that the current state of the client device 106 complies with the current configuration state 136 assigned by the management service 113 without explicitly disclosing the current configuration of the client device 106. The management service 113 or other applications (e.g., such as those run by auditors) could evaluate the state ZKP 163 to confirm that state the client device 106 matches the configuration state 136 specified for the client device 106. Examples of ZKPs that could be used for the state ZKP 163 can include non-interactive zero knowledge (NIZK) proofs, zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK) proofs, and zero-knowledge scalable transparent argument of knowledge (zk-STARK) proofs." (Beveridge Par. 0108).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the monitoring and assessing method of carbon footprint of Kumar with proving compliance without disclosing data of Beveridge to trust that the data stored on the device has not been tampered with (Beveridge Par. 0003).
Regarding Claim 2,
The combination of Kumar and Beveridge 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 and Beveridge 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 7,
The combination of Kumar and Beveridge 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).
Claim(s) 4, 5 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar (US 20220327538 A1), in view of Beveridge (US 20250028761 A1), in view of Miura (JP2023168121A), and in further view of Chen (TW I872336 B).
Regarding Claim 4, and Claim 11
The combination of Kumar and Beveridge disclose the device of claim 3, and claim 10 as shown above. The combination of Kumar and Beveridge fail to disclose a key value and offset value based on the one or more CFMs and carbon footprint threshold such that the sum of the one or more normalized CFMs and offset value is greater than the carbon footprint threshold and applying a hash on the key value. Alternatively, Miura discloses greenhouse gas emissions. Miura teaches, The device of claim 3, wherein the sustainability logic is further configured to: determine 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; 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 at the time of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar and Beveridge 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, Beveridge and Miura disclose monitoring carbon footprints and determining a key value and offset value based on a threshold. The combination of Kumar, Beveridge and Miura fail to disclose applying a hash on the key value based on at least the carbon footprint threshold, the offset value, or sum of the one or more normalized CFMs to generate the ZK attestation. Alternatively, Chen discloses a blockchain system for managing carbon footprints. Chen teaches, apply 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. “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 at the time 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, Beveridge and Miura 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 5,
The combination of Kumar, 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).
Beveridge further discloses, wherein the verifiable ZK proof is verified by the auditing device by applying the hash "A third blockchain, referred to herein as a data attribute blockchain, can be utilized to store metadata relating to data generated by applications running on a computing device. The metadata can be trusted because the configuration of the computing device can be trusted due to the configuration blockchain that is utilized to specify the configuration of the device. The metadata can be tightly coupled to the data generated by the computing device so that other parties can trust the validity or accuracy of the data that is generated by the computing device. In some examples, the metadata can comprise a hash of the data, a rollup of the data, or other representations of the data. In some cases, the metadata or components within the metadata can be signed. In certain examples, an encrypted wrapper or shield that is stored on the data attribute blockchain can comprise the metadata and/or a hash for the metadata. The data attribute blockchain enables entities or parties to prove that they are observant of data policies, regulations, laws, or other requirements or recommendations with respect to handling of data that is generated on a computing device. (Beveridge Par. 0017).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Beveridge Miura, and Chen with the verifiable proof being verified by a device by applying a hash of Beveridge to prove that they are observant of data policies, regulations, laws, or other requirements or recommendations with respect to handling of data that is generated on a computing device (Beveridge Par. 0017).
Claim(s) 6 is rejected under 35 U.S.C. 103 as being unpatentable over Kumar (US 20220327538 A1), in view of Beveridge (US 20250028761 A1)), in view of Miura (JP2023168121A), in view of Chen (TW I872336 B), and in further view of Quigley (US 20240201662 A1) .
Regarding Claim 6,
The combination of Kumar, Beveridge, Miura, Chen, disclose the device of claim 5, 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).
The combination of Kumar, Beveridge, Miura, Chen, fail to disclose 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. Alternatively, Quigley discloses reducing flows when a greenhouse gas exceeds a measurement. Quigley, teaches:
compare the sum of the one or more normalized CFMs with the carbon footprint threshold dynamically; "At act 604, the measure of mass flow rate obtained at act 602 is compared to a first threshold to determine whether the measure of mass flow rate is greater than the first threshold. As described herein, the inventors have appreciated that it may be desirable to limit the mass flow rate of greenhouse gasses being emitted from a landfill. Thus, the process 600 may include determining whether a mass flow rate of a particular greenhouse gas exceeds a threshold" (Quigley Par. 0172). "r. The one or more sensors disposed in the chamber may obtain a static measurement of gas concentration of the gas sample that has been drawn into the chamber by the pump. In some embodiments, the one or more sensors disposed in the chamber may obtain a dynamic measurement of gas concentration of the gas sample that has been drawn into the chamber by the pump. For example, the one or more sensors may be operated to obtain a measurement of gas concentration while the gas sample is flowing (e.g., flowing through a tube via activation of the pump)" (Quigley Par. 0255).
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. "For example, if the estimate of gas emissions is greater than or equal to a threshold for gas emissions, one or more corrective actions may be performed, such as adjusting a flow rate of gas extraction from one or more wells in and/or outside of the region of the landfill for which emissions are estimated (e.g., by adjusting positions of one or more valves controlling flow rate of respective one or more wells and/or adjusting a system vacuum applied to a plurality (e.g., all) wells in the region of the landfill), removing liquid from gas collection wells in and/or outside of the region of the landfill, adjusting a cover of the landfill surface for one or more wells (e.g., by applying less permeable cover material to the landfill surface), and/or adjusting the number of gas collection wells in the region of the landfill (e.g., increasing gas collection well density to improve methane capture)" (Quigley Par. 0039).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Beveridge, 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 Quigley for a more efficient reduction greenhouse gas emissions. (Quigley Par. 0167).
Claim(s) 8 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar (US 20220327538 A1), in view of Beveridge (US 20250028761 A1), in view of Singh (US 20250029034 A1) .
Regarding Claim 8, and Claim 14
The combination of Kumar and Beveridge disclose the device of claim 1, and method of claim 10 as shown above. The combination of Kumar and Beveridge fail to disclose collecting telemetry data indicative of sustainability data. Alternatively, Singh discloses determining optimal power consumption using telemetry data. Singh teaches: The device of claim 1, wherein the sustainability logic is further configured to: collect a real-time telemetry data indicative of a diverse sustainability data; and "Referring to FIG. 10, a flow diagram is presented of method 1200 for intelligent validation of digital assets via power consumption telemetry data tracking, in accordance with embodiments of the present invention. At Event 1210, telemetry data is extracted from a digital asset or distributed trust computing network used to mint/mine and/or store the digital asset. The telemetry data is related to power consumption (i.e., the carbon footprint of the digital asset) of the digital asset occurred in minting/mining of the digital asset, storage of the asset and, in some embodiments, where applicable transfer of the digital asset amongst different distributed trust computing networks " (Singh Par. 0082).
generate the one or more normalized CFMs based on the real-time telemetry data. "At Event 1220, the extracted telemetry data is applied to ML algorithms, in specific embodiments, DL algorithms to determine a power consumption indicator for the digital asset. The power consumption indicator, which may be a numeric score or the like indicates the level of power consumed by the digital asset when minting/mining, storing, and transferring the digital asset” (Singh Par. 0083).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar and Beveridge with collecting a real-time telemetry data indicative of a diverse sustainability data, and generating the one or more normalized CFMs based on the real-time telemetry data of Singh to serve to limit the amount of power consumed (Singh Par. 0004).
Claim(s) 12 is rejected under 35 U.S.C. 103 as being unpatentable over Kumar (US 20220327538 A1), in view of Beveridge (US 20250028761 A1), in view of Miura (JP2023168121A), in view of Chen (TW I872336 B), and in further view of Quigley (US 20240201662 A1) .
Regarding Claim 12,
The combination of Kumar, Beveridge, Miura, and Chen disclose the device of claim 11, as shown above. Kumar further discloses, The method of claim 11, further comprising: generating 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).
The combination of Kumar, Beveridge, Miura, and Chen, fail to disclose 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. Alternatively, Quigley disclose reducing flows when a greenhouse gas exceeds a measurement. Quigley, teaches:
comparing the sum of the one or more normalized CFMs with the carbon footprint threshold dynamically; "At act 604, the measure of mass flow rate obtained at act 602 is compared to a first threshold to determine whether the measure of mass flow rate is greater than the first threshold. As described herein, the inventors have appreciated that it may be desirable to limit the mass flow rate of greenhouse gasses being emitted from a landfill. Thus, the process 600 may include determining whether a mass flow rate of a particular greenhouse gas exceeds a threshold" (Quigley Par. 0172). "r. The one or more sensors disposed in the chamber may obtain a static measurement of gas concentration of the gas sample that has been drawn into the chamber by the pump. In some embodiments, the one or more sensors disposed in the chamber may obtain a dynamic measurement of gas concentration of the gas sample that has been drawn into the chamber by the pump. For example, the one or more sensors may be operated to obtain a measurement of gas concentration while the gas sample is flowing (e.g., flowing through a tube via activation of the pump)" (Quigley Par. 0255).
adjusting an energy consumption of a device dynamically if the sum of the one or more normalized CFMs is not less than the carbon footprint threshold. "For example, if the estimate of gas emissions is greater than or equal to a threshold for gas emissions, one or more corrective actions may be performed, such as adjusting a flow rate of gas extraction from one or more wells in and/or outside of the region of the landfill for which emissions are estimated (e.g., by adjusting positions of one or more valves controlling flow rate of respective one or more wells and/or adjusting a system vacuum applied to a plurality (e.g., all) wells in the region of the landfill), removing liquid from gas collection wells in and/or outside of the region of the landfill, adjusting a cover of the landfill surface for one or more wells (e.g., by applying less permeable cover material to the landfill surface), and/or adjusting the number of gas collection wells in the region of the landfill (e.g., increasing gas collection well density to improve methane capture)" (Quigley Par. 0039).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Beveridge, 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 Quigley for a more efficient reduction greenhouse gas emissions. (Quigley Par. 0167).
Regarding Claim 13,
The combination of Kumar, Beveridge, Miura, Chen and Quigley disclose the method of claim 12, as shown above. Kumar further discloses, The method of claim 12, 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).
Beveridge discloses, further comprising verifying the verifiable ZK proof by applying the hash "A third blockchain, referred to herein as a data attribute blockchain, can be utilized to store metadata relating to data generated by applications running on a computing device. The metadata can be trusted because the configuration of the computing device can be trusted due to the configuration blockchain that is utilized to specify the configuration of the device. The metadata can be tightly coupled to the data generated by the computing device so that other parties can trust the validity or accuracy of the data that is generated by the computing device. In some examples, the metadata can comprise a hash of the data, a rollup of the data, or other representations of the data. In some cases, the metadata or components within the metadata can be signed. In certain examples, an encrypted wrapper or shield that is stored on the data attribute blockchain can comprise the metadata and/or a hash for the metadata. The data attribute blockchain enables entities or parties to prove that they are observant of data policies, regulations, laws, or other requirements or recommendations with respect to handling of data that is generated on a computing device. (Beveridge Par. 0017).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Beveridge, Miura, Chen and Quigley with the verifiable proof being verified by a device by applying a hash of Beveridge to prove that they are observant of data policies, regulations, laws, or other requirements or recommendations with respect to handling of data that is generated on a computing device (Beveridge Par. 0017).
Claim(s) 15, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Kumar (US 20220327538 A1), in view of Beveridge (US 20250028761 A1), and in further view of Quigley (US 20240201662 A1) .
Regarding Claim 15,
Kumar discloses, 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).
generate a Zero Knowledge (ZK) attestation if the sum of the one or more normalized CFMs is less than 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).
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 proving compliance without disclosing data, comparing a sum of the one or more normalized CFMs with a 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. Beveridge, however, discloses publishing metadata to a blockchain network. The metadata can contain properties of data generated by a system. The metadata can allow for other entities to validate or trust the data generated by the system. Beveridge teaches:
to prove compliance with the " The configuration smart contract 156 can be used to store and maintain data on the blockchain related to the operation of the management service 113 and the management agent 139. For example, the configuration smart contract 156 could maintain one or more state records 157, which could be stored on the blockchain 153. Each state record 157 could represent the current configuration state 136 for a client device 106. However, because the blockchain 153 may be publicly accessible, it could be undesirable to store the current configuration state 136 itself on the blockchain 153. Accordingly, a state record 157 could include a device identifier 133 for a specific client device 106 and a state zero-knowledge proof (ZKP) 159 that represents the current state of the client device 106. The management agent 139 could generate the state ZKP 163 and submit it to the configuration smart contract 156 to store on the blockchain 153 to prove that the current state of the client device 106 complies with the current configuration state 136 assigned by the management service 113 without explicitly disclosing the current configuration of the client device 106. The management service 113 or other applications (e.g., such as those run by auditors) could evaluate the state ZKP 163 to confirm that state the client device 106 matches the configuration state 136 specified for the client device 106. Examples of ZKPs that could be used for the state ZKP 163 can include non-interactive zero knowledge (NIZK) proofs, zero-knowledge succinct non-interactive argument of knowledge (zk-SNARK) proofs, and zero-knowledge scalable transparent argument of knowledge (zk-STARK) proofs." (Beveridge Par. 0108).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the monitoring and assessing method of carbon footprint of Kumar with proving compliance without disclosing data of Beveridge to trust that the data stored on the device has not been tampered with (Beveridge Par. 0003).
The combination of Kumar and Beveridge disclose monitoring carbon footprints using zero knowledge methods, but fails to disclose comparing a sum of the one or more normalized CFMs with a 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. Alternatively, Quigley discloses reducing flows when a greenhouse gas exceeds a measurement. Quigley, teaches:
compare a sum of the one or more normalized CFMs with a carbon footprint threshold dynamically; "At act 604, the measure of mass flow rate obtained at act 602 is compared to a first threshold to determine whether the measure of mass flow rate is greater than the first threshold. As described herein, the inventors have appreciated that it may be desirable to limit the mass flow rate of greenhouse gasses being emitted from a landfill. Thus, the process 600 may include determining whether a mass flow rate of a particular greenhouse gas exceeds a threshold" (Quigley Par. 0172). "r. The one or more sensors disposed in the chamber may obtain a static measurement of gas concentration of the gas sample that has been drawn into the chamber by the pump. In some embodiments, the one or more sensors disposed in the chamber may obtain a dynamic measurement of gas concentration of the gas sample that has been drawn into the chamber by the pump. For example, the one or more sensors may be operated to obtain a measurement of gas concentration while the gas sample is flowing (e.g., flowing through a tube via activation of the pump)" (Quigley Par. 0255).
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; and "For example, if the estimate of gas emissions is greater than or equal to a threshold for gas emissions, one or more corrective actions may be performed, such as adjusting a flow rate of gas extraction from one or more wells in and/or outside of the region of the landfill for which emissions are estimated (e.g., by adjusting positions of one or more valves controlling flow rate of respective one or more wells and/or adjusting a system vacuum applied to a plurality (e.g., all) wells in the region of the landfill), removing liquid from gas collection wells in and/or outside of the region of the landfill, adjusting a cover of the landfill surface for one or more wells (e.g., by applying less permeable cover material to the landfill surface), and/or adjusting the number of gas collection wells in the region of the landfill (e.g., increasing gas collection well density to improve methane capture)" (Quigley Par. 0039).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar and Beveridge 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 Quigley for a more efficient reduction greenhouse gas emissions. (Quigley Par. 0167).
Regarding Claim 16,
The combination of Kumar, Beveridge and Quigley disclose the device of claim 15, as shown above. Kumar further discloses, The device of claim 15, 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, Beveridge, and Quigley disclose the device of claim 16, as shown above. Kumar further discloses, The device of claim 16, 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).
Claim(s) 18 is rejected under 35 U.S.C. 103 as being unpatentable over Kumar (US 20220327538 A1), in view of Beveridge (US 20250028761 A1), in view of Quigley (US 20240201662 A1), in view of Miura (JP2023168121A), and in further view of Chen (TW I872336 B) .
Regarding Claim 18,
The combination of Kumar, Beveridge and Quigley disclose the device of claim 17, as shown above. The combination of Kumar and Quigley fails to disclose a key value and offset value based on the one or more CFMs and carbon footprint threshold such that the sum of the one or more normalized CFMs and offset value is greater than the carbon footprint threshold and applying a hash on the key value. Alternatively, Miura discloses greenhouse gas emissions. Miura teaches, The device of claim 17, wherein the sustainability logic is further configured to: determine 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; 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 at the time of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Beveridge and Quigley 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, Beveridge, Quigley and Miura disclose monitoring carbon footprints and determining a key value and offset value based on a threshold. The combination of Kumar, Beveridge, Quigley, and Miura fail to disclose applying a hash on the key value based on at least the carbon footprint threshold, the offset value, or sum of the one or more normalized CFMs to generate the ZK attestation. Alternatively, Chen discloses a blockchain system for managing carbon footprints. Chen teaches, apply 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. “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 at the time 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, Quigley and Miura 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, Beveridge, Quigley, 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).
Beveridge further discloses, the verifiable ZK proof is verified by applying the hash on "A third blockchain, referred to herein as a data attribute blockchain, can be utilized to store metadata relating to data generated by applications running on a computing device. The metadata can be trusted because the configuration of the computing device can be trusted due to the configuration blockchain that is utilized to specify the configuration of the device. The metadata can be tightly coupled to the data generated by the computing device so that other parties can trust the validity or accuracy of the data that is generated by the computing device. In some examples, the metadata can comprise a hash of the data, a rollup of the data, or other representations of the data. In some cases, the metadata or components within the metadata can be signed. In certain examples, an encrypted wrapper or shield that is stored on the data attribute blockchain can comprise the metadata and/or a hash for the metadata. The data attribute blockchain enables entities or parties to prove that they are observant of data policies, regulations, laws, or other requirements or recommendations with respect to handling of data that is generated on a computing device. (Beveridge Par. 0017).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Beveridge, Quigley, Miura, and Chen with the verifiable proof being verified by a device by applying a hash of Beveridge to prove that they are observant of data policies, regulations, laws, or other requirements or recommendations with respect to handling of data that is generated on a computing device (Beveridge Par. 0017).
Claim(s) 20 is rejected under 35 U.S.C. 103 as being unpatentable over Kumar (US 20220327538 A1), in view of Beveridge (US 20250028761 A1), in view of Quigley (US 20240201662 A1), and in further view of Singh (US 20250029034 A1).
Regarding Claim 20,
The combination of Kumar, Beveridge, and Quigley disclose the device of claim 15, as shown above. The combination of Kumar, Beveridge, and Quigley fail to disclose collecting telemetry data indicative of sustainability data. Alternatively, Singh discloses determining optimal power consumption using telemetry data. Singh teaches: The device of claim 15, wherein the sustainability logic is further configured to: collect a real-time telemetry data indicative of a diverse sustainability data; and "Referring to FIG. 10, a flow diagram is presented of method 1200 for intelligent validation of digital assets via power consumption telemetry data tracking, in accordance with embodiments of the present invention. At Event 1210, telemetry data is extracted from a digital asset or distributed trust computing network used to mint/mine and/or store the digital asset. The telemetry data is related to power consumption (i.e., the carbon footprint of the digital asset) of the digital asset occurred in minting/mining of the digital asset, storage of the asset and, in some embodiments, where applicable transfer of the digital asset amongst different distributed trust computing networks " (Singh Par. 0082).
generate the one or more normalized CFMs based on the real-time telemetry data. "At Event 1220, the extracted telemetry data is applied to ML algorithms, in specific embodiments, DL algorithms to determine a power consumption indicator for the digital asset. The power consumption indicator, which may be a numeric score or the like indicates the level of power consumed by the digital asset when minting/mining, storing, and transferring the digital asset” (Singh Par. 0083).
It would have been obvious to one of ordinary skill in the art at the time of the claimed invention to have combined the method of assessing and monitoring carbon footprints of an enterprise of Kumar, Beveridge, and Quigley with collecting a real-time telemetry data indicative of a diverse sustainability data, and generating the one or more normalized CFMs based on the real-time telemetry data of Singh to serve to limit the amount of power consumed (Singh Par. 0004).
Subject Matter Distinguishable from Prior Art
After conducting different searches in PE2E Search, Similarity Search, Google, and IP.com, it appears that the cited prior art of record fails to expressly teach or suggest, either alone or in combination, the features 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.
Therefore, in combination with the other limitations clearly claimed render claim 9 allowable over the prior art. A Non-Patent Literature search was conducted and no relevant art was found.
Response to Arguments
Applicant's arguments filed 11/24/2025 with respect to 35 U.S.C. § 101, have been fully considered but they are not persuasive. Applicant argues that the claim provides a specific technical solution to this data-privacy and security problem by implementing a Zero Knowledge (ZK) protocol for verifying compliance and that the step of generating a proof that verifies a fact (compliance) while mathematically hiding the source data is not an abstract rule or a method of organizing human activity, and that a human cannot verify a sum against a threshold without knowing the sum, and the direct manipulation of data transmission to enforce privacy is a specific improvement in computer networking and data-security technology, not an abstract idea. The Examiner respectfully disagrees. The current category of “certain methods of organizing human activity” that the claims have been rejected under, is “managing personal behavior including following rules or instructions” which falls under certain methods of organizing human activity. Applicant argues that a direct manipulation of data transmission to enforce privacy is a specific technical improvement. The Examiner respectfully disagrees. Hiding source data is protecting confidentiality, and an attestation of that data is not a technical improvement, but a business improvement. The claims recite the desired result without specifying a technical improvement in how the computer accomplishes the direct manipulation of data.
Applicant further argues that the additional elements amount to “significantly more”, providing an inventive concept since the specific cryptographic implantation improves the security of the network device by eliminating the need to transmit sensitive payload data across the network, provides a technical solution to the problem of “greenwashing” and data leakage by reciting a specific data-processing pipeline, and solves a technical problem of verifying sustainability metrics in a “trustless” environment by transforming the internal operation data into a cryptographic proof. The Examiner respectfully disagrees because the claim language itself does not recite a method that improves security of the network device. The claims merely recite generating Zero Knowledge attestation, generating verifiable ZK proof, and transmitting verifiable ZK poof without specifying a precise method of generating the attestation and proof that would be considered an improvement. In response to applicant's argument that the claims provide a technical improvement, it is noted that the features upon which applicant relies (i.e., features described in [0040] of the specification) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993). Furthermore, even in view of the specification, the applicant’s arguments are still not persuasive because it is not apparent to one of ordinary skill in the art that the current scope of the claim language lends the alleged improvement to the field of cryptography. As stated in MPEP 2106.05(a), “If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide 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.” While there may be an improvement in the abstract idea of verifying data to prove compliance while maintaining privacy, there is no improvement to a particular technological field because the claims do not actually improve the way that the Zero Knowledge/cryptography is being generated and transmitted from a network device. Furthermore, the alleged improvements of “improving the functioning of secure network communication systems” is not persuasive as a technical improvement, because there is no indication that the generic computing component is made to run faster, more efficiently, or utilize less power. The steps as stated in the claims do not provide an actual improvement because it is merely reciting rule-based triggers to perform certain tasks on an interface, thus using devices in their ordinary capacity to validate and prove compliance. Therefore, based on the updated rejection above and the response presented here, the applicant’s arguments are not persuasive, and the 101 rejection holds.
Applicant's arguments filed 11/24/2025 with respect to 35 U.S.C. § 102, have been fully considered and are persuasive. The 102 Rejection is withdrawn in light of the amendments.
Applicant's arguments filed 11/24/2025 with respect to 35 U.S.C. § 103, have been fully considered but they are not persuasive. The amendments necessitated a new grounds of rejection as shown above.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/E.M.K./Examiner, Art Unit 3626
/JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626