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
This action is in response to remarks received 04/07/2026.
Applicant amends claims 1, 7, 26 and 32, cancels claims 3-6, 13, 28, 31 and 39 and newly adds claim 50.
Claims 2, 7-12, 14-25, 27, 29-30, 32-38 and 40-50 being dependent claims and claims 1 & 26 are independent.
Claims 1, 2, 7-12, 14-27, 29, 30, 32-38 and 40-50 are currently pending and have been examined.
Response to Arguments
Applicant's arguments filed 04/07/2026 have been fully considered but they are not persuasive.
With respect to Applicants’ arguments of the claims under 35 USC § 101, have been fully considered; however, the Examiner respectfully disagrees.
Applicant’s argument that the independent claim is not directed to a business process is not persuasive. While the claim is not limited to a particular industry or expressly labeled as a business method, the claim nonetheless recites a method of organizing human activity, specifically, generating, receiving, storing, enriching, employing, creating, analyzing, processing, measuring, segmenting, normalizing, scoring, ranking, estimating, and applying data according to defined rules. Under the 2019 Revised Patent Subject Matter Eligibility Guidance, such activities fall within the abstract idea grouping of certain methods of organizing human activity.
Further, the claims are also directed to collecting and analyzing information (e.g., environmental data, sensor data, financial data) and generating results (e.g., emissions estimates, rankings & reports), which courts have consistently held to be abstract ideas (see Electric Power Group; SAP v. InvestPic).
The mere recitation of computer components to implement these steps does not alter the fundamental character of the claim.
Applicant’s amendments to include sensors, IoT devices, proximity-based clustering, blockchain infrastructure, and machine learning techniques do not alter this conclusion because these elements are recited at a high-level and are used as tools to collect, analyze, and process data, rather than to improve the functioning of such technologies themselves.
The limitations reciting automated or technical processing of these steps and the generation of a report do not alter this conclusion, as such limitations merely reflect the use of a computer to automate the underlying information processing and the present the results.
The recitation of sensors and IoT devices does not render the claims non-abstract, as the focus of the claims remains on the processing and analysis of the collected data rather than any improvement to sensor technology or data acquisition mechanisms.
Under Step 2A, Prong Two, Applicant’s arguments that the claims are integrated into a practical application are not persuasive. The claims do not meaningfully limit the judicial exception, but instead represent no more than drafting efforts designed to monopolize the abstract idea.
The additional elements merely recite the use of generic computing components to perform the abstract idea and therefore do not integrate the abstract idea into a practical application.
In particular, the recited “partition unit”, “scoring unit”, “ranking unit”, “normalization unit” and “estimation unit” describe functional results of data processing (e.g., grouping, evaluating, comparing, and predicting data) rather than specific technological improvements.
The claimed invention does not improve the functioning of a computer nor does it improve another technology or technical field. Rather, the claims are directed to processing information according to defined rules, with the computer serving only as a tool to automate the abstract idea.
Applicant’s argument that the claims improve environmental monitoring, sensor networks, or data integrity is not supported by the claim language, which does not recite any improvement to sensor hardware, communication protocols, network performance, or blockchain operation, but instead uses such components as data sources and storage mechanisms.
Applicant’s argument that the claims solve a specific technical problem (e.g., data integrity, sensor reliability, or environmental data accuracy) is not persuasive because the claims address these issues through data analysis techniques such as comparison, validation, scoring, and ranking, rather than through improvements to the underlying technology itself. The alleged “technical problems” (e.g., data integrity, sensor reliability, and environment data accuracy) are themselves data-centric issues relating to the quality and analysis of information, rather than technological problems rooted in the functioning of a computer, sensor hardware, or network technology.
Similarly, Applicant’s assertion that the claims recite specific technical limitations beyond generic computer implementation is not persuasive. The recited limitations, including, cross-validation of sensor data, historical accuracy analysis, clustering based on proximity, and machine learning predictions; represent analytical techniques applied to data and do not reflect improvements to computer functionality or another technological field.
Considering the claims as a whole does not change the analysis. The ordered combination of elements results in a data processing workflow that collects, evaluates, and outputs information, but does not improve the operation of any computing component, sensor, or network technology.
Applicant’s argument that the claims integrate the judicial exception into a practical application is not persuasive. The additional elements do not impose a meaningful limit on the abstract idea, but instead merely link the abstract idea to a technological environment (e.g., sensor networks, blockchain systems and machine learning tools).
Applicant’s argument that the claims do not merely automate a business process but instead provide a technological solution is not persuasive. Even if not framed as a traditional business method, the claims are directed to organizing, analyzing, and using information to produce outputs such as emission estimates, predictions, and reports. Such activities fall squarely within abstract data analysis (see Electric Power Group; Sap v. InvestPic; Two-Way Media).
Although the claims recite the use of a blockchain, the blockchain is used in its inherent capacity to store data in an immutable manner, which is a well-known and conventional function.
Applicant’s argument that the blockchain recites a specific structure (e.g., transaction log, world state database and hash chaining) is not persuasive because these elements correspond to known components of conventional distributed ledger architectures and are recited at a high-level without any improvement to their operation. Further, the claims do not alter how blocks are generated, validated, or stored within the blockchain, but merely use known blockchain structures to record results of data processing.
Under Step 2B, the claims do not include additional elements that amount to significantly more than the abstract idea. The additional elements, when considered individually and in combination, merely recite the use of generic computing components to perform well-understood, routine, and conventional functions of receiving, storing, processing, and outputting information.
The use of machine learning techniques, as recited by the “cognitive intelligence unit”, does not add an inventive concept because the claims invoke machine learning at a high-level of generality to analyze data and generate predictions, which is a conventional use of such techniques. The claims do not recite any specific model architecture, training methodology, feature engineering technique, or improvement to model performance, but instead invoke machine learning at a high-level as a generic tool to analyze data.
Similarly, the recited blockchain is employed in its conventional capacity to store and verify data and does not provide an unconventional arrangement or technical improvement.
The recitation of token generation, attestation, financial derivatives, and emissions reporting reflects the use of processed information for financial or reporting purposes and does not add an inventive concept.
Applicant’s argument that the combination of elements amounts to an inventive concept is not persuasive. The claimed elements; data collection, validation, scoring, ranking, machine learning analysis, and blockchain storage; each perform their expected functions, and their combination does not result in an unconventional technical arrangement. The claimed combination does not result in any technical interaction that improves system performance, but instead reflects a sequential data processing pipeline in which each component performs its expected role.
With respect to the dependent claims, the additional limitations further narrow the abstract idea by specifying particular data types, processing rules, or implementation details. However, these limitations do not add an inventive concept.
This includes limitations relating to clustering, normalization, scoring, ranking, blockchain storage, token creation, emissions accounting, and governance reporting, all of which represent variations of data processing and output generation.
Applicant’s reliance on USPTO Subject Matter Eligibility Examples 45-47 is not persuasive.
These examples are distinguishable because they involve using calculated information to control or improve the operation of a physical device or system. In contrast, the present claims do not control any physical process or device, but instead generate information outputs.
Applicant’s reliance on Ex Parte Desjardins, is not persuasive.
In Desjardins, eligibility was based on a specific improvement to machine learning technology itself. In contracts, the present claims merely apply machine learning to analyze environmental data without reciting any improvement to model training, architecture, or performance.
Taken together, the claims describe a data processing pipeline that collects environmental data, analyzes the data using conventional techniques (including validation, ranking and machine learning), and generates outputs such as predictions, reports and financial information. The claims do not improve the underlying technology, but instead use known tools to process information.
Accordingly, the claims do not integrate the abstract idea into a practical application under Step 2A, and do not include and inventive concept under Step 2B.
For the above reasoning the 35 U.S.C. § 101 rejection of the claims is maintained.
35 USC § 112(f) Analysis
The claim limitations including, for example, “enrichment layer”, ”data layer”, ”partition unit”, “ranking unit”, “normalization unit”, “standards module”, “emissions trading unit”, “recommendation engine”, “post-processing unit”, and “digital trust infrastructure unit”, each reciting functionality using “configured to” language, have been considered with respect to 35 USC 112(f). Upon review, the limitations are not interpreted under 35 USC 112(f) because the claim language, when read in light of the specification, recites sufficiently definite structure for performing the claimed functions and therefore does not recite purely functional claiming without corresponding structure.
For the above reasoning the 35 U.S.C. § 101 rejection of the claims is maintained.
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, 2, 7-12, 14-27, 29, 30, 32-38 and 40-50 are directed to statutory categories of invention, including a system (machine) and a computer-implemented method (process). Accordingly, the claims satisfy Step 1 of the Alice/Mayo framework.
Under Step 2A, Prong One: The claims are rejected under 35 U.S.C. § 101 because the claimed invention is directed to the abstract idea of collecting, analyzing, validating, and processing environmental and enterprise data to estimate emissions, assess reliability, and generate reports and financial/decision outputs. This includes, for example:
collecting environmental data from sensors and IoT devices,
segmenting data into clusters and normalizing data,
scoring, ranking and validating sensor data,
estimating emissions and generating reports,
creating tokens or financial derivatives based on the data,
applying machine learning models to generate predictions, and
tracking, managing, and reporting enterprise emissions and risks.
This is a form of a method of organizing human activity and a fundamental economic practice, such as managing business, environment, and financial information according to a set of rules, which falls within the groupings identified in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Under Step 2A, Prong Two: This judicial exception is not integrated into a practical application because the combination of additional elements fail to integrate the judicial exception into a practical application. The generically recited additional elements include:
an enrichment unit,
a digital trust infrastructure unit (including blockchain),
a post-processing unit,
a partition unit, normalization unit, scoring unit, and ranking unit,
an application interface unit,
a cognitive intelligence unit (including machine learning),
token creation, attestation, and analytics unit, and
various reporting, accounting, management trading, and governance units.
These elements, individually and in combination merely perform data collection, storage, analysis, and output functions on a computer system and do not impose a meaningful limit on the abstract idea.
For example:
the blockchain is used as a generic data storage/verification mechanism,
the machine learning models are used to analyze data and generate predictions,
the token creation and attestation units generate financial or informational outputs,
the scoring, ranking, and validation steps evaluate data using rules,
All of the above examples constitute data processing and analysis rather than a technological improvement.
These elements merely apply the abstract idea in a conventional computing environment and do not improve the functioning of a computer or another technology, nor do they effect a transformation of a particular article or provide a particular technical solution to a technical problem.
Under Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
The additional limitations are directed to:
storing, retrieving, and processing data,
analyzing data using rules, scoring, and validation,
applying machine learning techniques,
generating tokens, reports, and financial outputs, and
recording or verifying data using blockchain
These are well-understood, routine, conventional computer functions, as recognized in MPEP § 2106.05(d).
The use of machine learning, blockchain, and tokenization does not add an inventive concept because these technologies are invoked at a high-level of generality to perform their basic functions of analyzing data, storing data, and generating outputs.
The claims merely invoke computers as tools to perform an existing process and do not integrate the exception into a practical application or provide significantly. This is equivalent to “apply it” or “mere instructions” to apply an abstract idea as described in MPEP § 2106.05(f).
The recited computing components perform their well-understood, routine, and conventional functions, and the ordered combination of elements does not add an inventive concept sufficient to transform the abstract idea into patent-eligible subject matter.
The dependent claims 2, 7-12, 14-25, 27, 29-30, 32-38 and 40-50 further limit the abstract idea by specifying particular types of data, processing steps, or outputs, including clustering, normalization, scoring, ranking, validation, machine learning predictions, blockchain storage, token generation, emissions accounting, trading, governance reporting, and climate impact analysis.
However, these limitations merely refine how the abstract idea is performed and do not add any additional elements that integrate the exception into a practical application or amount to significantly more.
Accordingly, claims 1, 2, 7-12, 14-27, 29, 30, 32-38 and 40-50 are not directed to patent-eligible subject matter under 35 U.S.C. § 101.
Conclusion
THIS ACTION IS MADE FINAL. 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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TONY P KANAAN whose telephone number is (571)272-2481. The examiner can normally be reached Monday- Friday 7:30am - 3:30 pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Gart can be reached on 5712723955. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/T.P.K./Examiner, Art Unit 3696
/MATTHEW S GART/Supervisory Patent Examiner, Art Unit 3696
Prosecution Insights