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 .
This is the initial Office Action based on the application filed 12/27/2023. Claims 1-16 are presented for examination and have been considered below.
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 1-16 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (an abstract idea) without reciting significantly more.
Independent claim 1 recites:
obtaining message data comprising energy-related data from household collectors,
analyzing the message data,
correcting the message data based on analysis,
generating an energy blockchain transaction based on corrected data,
transmitting the transaction to a blockchain system.
These limitations describe collecting information, analyzing information, correcting or organizing information, and recording the information in a ledger. These activities constitute mental processes because analyzing data, identifying errors, correcting data, and deciding what to record can be performed by a human using pen and paper. Besides, the claims amount to collecting, processing, and storing information, which courts have repeatedly found abstract. See: Alice Corp. v. CLS Bank, Electric Power Group v. Alstom, CyberSource v. Retail Decisions.
The additional elements recited in the claims include:
collectors installed in households
a blockchain system
a message classifier
a message corrector
a transaction generator
generic computing components
These elements are described at a high level of generality that perform routine data collection and processing functions. Thus, they do not improve computer technology or blockchain technology and do not provide a technical solution to a technical problem. The use of a blockchain merely serves as a ledger for recording processed data. Using a distributed ledger to store transaction data is an abstract concept implemented on generic computing infrastructure. Therefore, the claims do not improve blockchain structure, distributed ledger security, smart meter hardware or data transmission protocols. Instead, the claims use blockchain as a generic storage mechanism for energy transaction records. Thus, the abstract idea is not integrated into a practical application.
The additional elements do not amount to significantly more than the abstract idea. The components recited are generic collectors, generic processors, generic message classifiers, and generic blockchain systems. The functions performed (collecting, analyzing, correcting, generating, transmitting) are well-understood, routine, and conventional computer functions. Blockchain itself was well-known at the time of filing as a distributed ledger for recording transactions. And nothing in the claims alters the functioning of a computer, improves blockchain architecture, introduces unconventional technical mechanisms, and provides a technical improvement in smart grid systems. Instead, the claims apply routine data-cleaning techniques (e.g., replacing missing data, removing duplicates, correcting error data) before logging into a ledger, which is conventional data processing. Therefore, the claims do not contain an inventive concept sufficient to transform the abstract idea into patent-eligible subject matter.
Accordingly, claim 1 recites an abstract idea.
Dependent claims 2–7 merely add refinements of:
organizing messages by time period,
substituting missing data,
removing duplicate data,
identifying error data,
classifying by household ID.
These are further data organization and correction steps which are abstract. System claims 8–10 and device claims 11–16 merely recite generic components configured to perform the same abstract process. Accordingly, claims 1–16 are rejected under 35 U.S.C. §101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-16 are rejected under 35 U.S.C. 103 as being unpatentable over Guan et al ("Privacy-preserving and Efficient Aggregation based on Blockchain for Power Grid Communications in Smart Communities" ) and further in view of Chen et al “Data quality of electricity consumption data in a smart grid environment”.
Claim 1: Guan et al teach an energy blockchain transaction management method, comprising:
obtaining message data generated by collecting messages comprising energy-related data of respective households from collectors installed respectively in the households (e.g., The system uses "Smart Meters (SM)" installed in "users' homes" (households) to "collect the near real-time electricity consumption data" ([Page 1], [Page 3], Fig. 2). These SMs act as the "collectors." The data collected constitutes the "message data."); and
generating an energy blockchain transaction based on the corrected message data and transmitting the generated energy blockchain transaction to a blockchain system (e.g., The core of the scheme involves a "mining node" aggregating the data and recording it into a "private blockchain" ([Page 3], [Page 6]). The "creation of new block" ([Page 6], Fig. 4) is the generation of the blockchain transaction/record. This block is then "published to the other users" (transmitted to the blockchain system) for verification ([Page 6])).
Not explicitly taught by Guan et al is analyzing the message data and correcting the message data based on an analysis result obtained by the analyzing. However, Chen et al. teach the necessity of analyzing the data to detect these quality issues, such as using "outlier detection" methods ([Section 5]). Chen et al. further teach that after analysis, the data must be processed. It states that the goal is "removing the noise, identifying the outlier and processing the incomplete" ([Section 2.1]). This is the definition of correcting the data.
Therefore, it would be obvious to a POSITA, before the effective filing date of the claimed invention, to combine the privacy-preserving blockchain framework of Guan et al. with the data cleansing teachings of Chen et al. in order to ensure the data being immutably recorded on the blockchain is accurate and reliable, preventing "garbage-in, garbage-out" scenarios that could affect billing, grid balancing, and other critical functions.
As per claim 8, the claimed features are rejected similarly to claim 1 above.
As per claim 11, the claimed features are rejected similarly to claim 1 above. Guan’s system inherently classifies data by household (each smart meter corresponds to a specific household). The mining node receives data "from all users in the group" (e.g., page 5).
Claim 2: Guan et al and Chen et al teach the energy blockchain transaction management method of claim 1, wherein the message data comprises messages received from the collectors during a block generation period and is stored in a unit of the block generation period (e.g., This is an inherent feature of blockchain systems, where data is batched into blocks over specific time periods. The system divides time into discrete slots (e.g., "each time slot, such as 15 min") for data collection and aggregation. See Page 4. The mining node aggregates data received during that specific time slot and records it into a block. See pages 3-4 ).
As per claim 9, the claimed features are rejected similarly to claim 2 above.
Claim 3: Guan et al and Chen et al teach the energy blockchain transaction management method of claim 1, but fail to teach that the correcting comprises: identifying, from the message data, a household that has not transmitted a message during a block generation period; extracting a message corresponding to the identified household from message data of a previous block generation period; and setting the extracted message as a message received from the identified household during the block generation period and adding the set message to the message data However, Chen et al Identify "incomplete data" as a core data quality issue (e.g., Section 3.3). Chen et al further discuss "data filling method" where incomplete data is filled through appropriate algorithms (e.g., Section 3.3). And using data from a previous period (e.g., last observation carried forward) is a standard imputation technique. Furthermore, Guan et al provide the context of time-slotted data collection ("block generation period") where this incompatibility would be detected (e.g., Page 4). Therefore, A PHOSITA, aware of Chen's teachings on incomplete data, would apply a standard imputation method (using previous period data) to fill gaps identified in Guan's time-slotted collection framework.
As per claim 12, the claimed features are rejected similarly to claim 3 above.
Claim 4: Guan et al and Chen et al teach the energy blockchain transaction management method of claim 1, but fail to teach t the correcting comprises: identifying, from the message data, a household from which duplicate messages have been received; identifying a first received message among the messages corresponding to the identified household; and moving at least one remaining message, excluding the identified message, among the messages corresponding to the identified household, to message data of a subsequent block generation period. However, Chen et al identifies "redundant data" as a data quality issue (e.g., Section 1). Chen et al further discuss handling of duplicate records (e.g., Section 2.2). Furthermore, Guan et al provide the structure of discrete block generation periods to which duplicate messages can be reallocated (e.g., Page 4). Detecting and handling duplicates is a basic data preprocessing step. Therefore, reallocating a duplicate to a subsequent period (rather than deleting) is an obvious design choice to preserve data while maintaining chronological order.
As per claim 13, the claimed features are rejected similarly to claim 4 above.
Claim 5: Guan et al and Chen et al teach the energy blockchain transaction management method of claim 1, wherein the correcting comprises: identifying whether each of the messages comprised in the message data comprises error data; and when a message comprising the error data is identified, correcting the identified message (e.g., This is the core of Chen et al., which focuses on detecting and correcting "noise data" and "outlier data" (e.g., Sections 3.2, 3.4 & 5).
As per claim 14, the claimed features are rejected similarly to claim 5 above.
Claim 6: Guan et al and Chen et al teach the energy blockchain transaction management method of claim 1, but fail to teach that each of the messages comprises at least one of: an energy consumption data storing application programming interface (API) that is generated by collecting energy consumption data from each of the households by an energy consumption data collector in each of the collectors; an energy production data storing API that is generated by collecting operational status data of solar power or fuel cell power generation equipment installed in each of the households by a power generation and status data collector in each of the collectors; or an energy storage data storing API that is generated by collecting charging and discharging status data of an energy storage device installed in each of the households by a charging and discharging status data collector in each of the collectors. However, Guan et al. teach the "energy consumption data storing API" is inherent in the smart meter data collection process. The smart meter collects consumption data and makes it available to the system (e.g., Page 1). Chen et al provide the broader context of smart grid data collection, which would encompass data from generation and storage devices as part of comprehensive energy management (e.g., Section 3.1). Therefore, as with Claim 10, extending API data collection to include generation and storage is an obvious adaptation in a modern smart grid environment where such devices are common. The APIs are simply the interface mechanism for the collectors already taught.
As per claim 15, the claimed features are rejected similarly to claim 6 above.
Claim 7: Guan et al and Chen et al teach the energy blockchain transaction management method of claim 1, further comprising: classifying the messages by household based on household identification data, wherein the transmitting to the blockchain system comprises: setting the household identification data as a key value and setting each of the messages as a data value, and generating an energy blockchain transaction corresponding to a household (e.g., Guan et al. use pseudonyms linked to specific households. The data is tied to a specific identity/pseudonym for processing and billing, which is the same as setting a key value).
As per claim 16, the claimed features are rejected similarly to claim 7 above.
Claim 10: Guan et al and Chen et al teach the energy blockchain transaction management system of claim 8, but fail to teach that each of the collectors comprises at least one of: an energy consumption data collector configured to collect energy consumption data about energy consumed by each of the households; a power generation and status data collector configured to collect operational status data of solar power or fuel cell power generation equipment installed in each of the households; or a charging and discharging status data collector configured to collect charging and discharging status data of an energy storage device installed in each of the households. However, Guan et al teach that Smart meters (SMs) are installed to collect "near real-time electricity consumption data" (e.g., page 1). This directly teaches the energy consumption data collector limitation, wherein the system is situated in a "smart grid" environment where distributed energy resources (solar, storage) are standard components. Furthermore, Chen et al discuss electricity consumption data in a "smart grid environment" where data comes from diverse sources, implicitly including generation and storage as part of modern grid infrastructure (e.g., Section 3). Therefore, a PHOSITA implementing a blockchain-based energy system for "smart communities" (as taught by Guan) would recognize that modern households increasingly include solar panels, fuel cells, and battery storage. Extending the data collection to include these sources is an obvious adaptation to provide a comprehensive energy management solution. Chen et al.'s framework for data quality applies equally to consumption, generation, and storage data.
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/GUERRIER MERANT/
Primary Examiner, Art Unit 2111
2/25/2026