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
The office action is being examined in response to the application filed by the applicant on June 26th, 2026.
Claims 1, 3, 5 and 7 – 10 have been amended and are hereby entered.
Claims 2, 4, and 6 have been cancelled.
Claims 1, 3, 5, and 7 - 10 are pending and have been examined.
This action is made NON-FINAL.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on June 26th, 2026 has been entered.
Response to Arguments
Applicant’s arguments filed on July 26th, 2026 have been fully considered but they are not persuasive.
Regarding Applicant’s arguments against the 101 rejections of claims on p. 5 – 8: Applicant’s arguments have been fully considered but are not persuasive because they rely on an unduly narrow interpretation of the claim language. During examination, the claims are given their broadest reasonable interpretation (BRI) consistent with the specification.
Claim 1 broadly recites a moving behavior database, a traffic jam database, and processing circuitry configured to perform calculations using information stored in those databases. The claim does not require any particular database architecture, data format, algorithm, or specific technique for deriving the coefficient, determining the moving means, or calculating the baseline emissions, actual emissions, reduced emissions, or evaluation value. Likewise, the claim broadly recites deriving a coefficient “based on” a traffic jam situation and calculating an evaluation value using that coefficient without imposing any particular mathematical relationship or calculation methodology.
Accordingly, the rejection under 35 U.S.C. § 101 is maintained.
Regarding Applicant’s arguments against the 102/103 rejections of claims on p. 8 – 11: Accordingly, Applicant’s arguments focus on features that are not required by the claims. Under the BRI, the cited portions of Jin, Chapman, and Blackhurst disclose or reasonably correspond to the broadly recited data sources, movement information, environmental impact calculations, and evaluation processing recited in the claims. The claims do not require the more specific implementation advanced by Applicant.
With respect to dependent claims 5, 8, 9, and 10, the additional limitations likewise broadly recite deriving coefficients based on user attributes, units of movement, communication plan information, or purchased products. The claims do not require any specific derivation technique or specialized algorithm for producing such coefficients. Therefore, Applicant’s arguments are not commensurate with the scope of the claims and do not persuasively distinguish the claimed subject matter from the applied references.
Accordingly, the rejection under 35 U.S.C. § 103 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, 3, 5, and 7 – 10 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more, and therefore does not recite patent-eligible subject matter.
Step 2A Prong 1: the claim recites a judicial exception. In particular, claim 1 recites operations that amount to mathematical calculation and mental processes for evaluating user behavior based on environmental impact. The claim recites converting moving-behavior-related information into an evaluation data format, calculating an amount of environmental impact associated with user behavior, deriving a coefficient based on a traffic jam situation, calculating an evaluation value based on the calculated environmental impact and the coefficient, determining a moving means of the user, calculating a baseline amount of CO2 emissions assuming travel by a gasoline vehicle, calculating an actual amount of CO2 emissions corresponding to the determined moving means, subtracting the actual amount of CO2 emissions from the baseline amount to determine a reduced amount of emissions, and calculating an evaluation value based on the reduced amount of emissions and the coefficient.
These limitations collectively describe mathematical relationships and calculations performed on collected data to evaluate the environmental impact of a user’s behavior. Likewise, determining a moving means from stored information, evaluating user behavior, and deriving a coefficient based upon a traffic jam situation are observations, evaluations, and judgments that can practically be performed in the human mind or with the aid of pen and paper when provided with the relevant information. Accordingly, the claim recites both mathematical concepts and mental processes, which are abstract ideas identified in the 2019 Revised Patent Subject Matter Eligibility Guidance.
Step 2A Prong 2: the claim does not integrate the judicial exception into a practical application. The additional elements recited in the claim include a moving behavior information database, attribute information database, traffic jam database, and processing circuitry configured to perform the recited calculations. These components are described in purely functional terms and represent generic computer components used for their typical purposes of storing information and executing calculations. The databases merely store data relating to user movement behavior, user attributes, and traffic conditions, and the processing circuitry retrieves and processes that data in order to perform the recited mathematical calculations. The claim does not recite any specific improvement to database technology, any specialized data acquisition mechanism for detecting movement or traffic conditions, or any particular technological improvement to computer functionality. Instead, the claimed device uses the stored data as inputs to the mathematical calculations that determine the environmental impact and sustainable score. The use of generic computer components to collect, store, and analyze information does not integrate the abstract idea into a practical application.
Furthermore, the claim does not recite any technological improvement to the determination of environmental data or movement information. The determination of a moving means based on stored behavior information and the reference to attribute and traffic databases merely provide additional information used in the calculations. These elements serve as sources of input data for the mathematical analysis rather than providing a technological improvement to any computing system or external technology. The claim therefore remains directed to the abstract idea of evaluating environmental impact and scoring user behavior based on calculated emissions reductions and contextual information.
Step 2B: the claim does not include any additional elements that amount to significantly more than the abstract idea itself. The moving behavior information database, attribute information database, traffic jam database, and processing circuitry represent well-understood and routine computer components that perform their generic functions of storing data and executing information. When considered individually and as an ordered combination, these elements merely implement the abstract idea of mathematically evaluating environmental impact and user behavior using generic computer technology. The claim does not recite any unconventional arrangement of computer components, any specialized hardware configuration, or any improvement to computer technology itself. Instead, the computer components operate in their ordinary capacity to perform calculations on collected data.
For dependent claims 3, 5 and 7 – 10, depend from claim 1 and therefore incorporate the abstract idea recited in claim 1. The additional limitations recited in these claims merely specify different categories of information that may be used in the evaluation of the user’s behavior. For example, claim 3 specifies that the user may include communication activity, electricity usage, or purchasing behavior. Claim 5 specifies particular user attributes such as gender, age, place of residence, household type, or occupation that may be used when deriving the scoring coefficient. Claim 7 recites that the movement may correspond to a specific state of the user, and claim 8 specifies that the environmental impact and scoring coefficient may be calculated in units of movement. Claim 9 specifies deriving a scoring coefficient corresponding to an amount of communication when a predetermined communication plan is used, and claim 10 specifies deriving a coefficient corresponding to a number of purchased products of a predetermined category. These limitations merely apply the same mathematical evaluation of environmental impact to additional types of user behavior or contextual data and do not introduce any technological improvement.
Accordingly, claims 1, 3, 5, 7 – 10 are directed to an abstract idea and do not include additional elements sufficient to amount to significantly more than the abstract idea itself. Therefore, claims 1, 3, 5, and 7 – 10 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.
Claims 1, 3, and 7 - 8 and 10 are rejected under 35 U.S.C. § 102(a)(1) as being unpatentable over Jin (U.S. Pub No. 20190213097 A1) in view of Chapman (U.S. Pub No. US20120150425 A1).
Regarding claim 1:
Jin teaches:
a moving behavior database configured to store information relating to moving behavior of a user; [¶0027]: User behavior data is generated, analyzed and then may be stored locally or remotely.
a processing circuitry configured to convert moving-behavior-related information acquired from the moving behavior database into an evaluation data format used for calculating CO2 emissions [¶0021, ¶0029]: Behavior data, which includes user movement behavior, associated with a user is collected. Then, a carbon-saving quantity value is determined by using a quantization algorithm;
calculate an amount of environmental impact generated in association with user behavior based on the information converted into the evaluation data format; [¶0018 - 0019]: A carbon emissions calculator is provided to calculate and control carbon footprints and carbon-saving quantities, for both individuals as well as enterprises.
refer to the traffic jam database and derive a coefficient based on a traffic jam situation in which the user is placed; [¶0019 - 0021]: A user’s behavior data is automatically collected and then can be broken down into “fragmented behavior data.” Additionally, [¶0040]: utilizes specific user data to then calculate carbon-saving quantities and then further convert those quantities to point values.
calculate an evaluation value for the user behavior based on the generated amount and the coefficient; [¶0040]: “The newly converted points can be added to total points associated with the user to obtain an updated total points value. As the value of the total points increase, the carbon-saving quantity associated with the user increases.”
transmit the evaluation value to a service server; [¶0040]: Points are handled across different service providers to provide a plethora of services corresponding to the amount of points a user may have.
determine a moving means of the user based on information database acquired from the moving behavior database; [¶0029]: In order for the carbon saving quantity quantization algorithm to properly monitor carbon emission, it monitors how many trips use a vehicle versus walking by foot.
calculate a baseline amount of CO2 emissions assuming that a total moving distance of the user was traveled by a gasoline vehicle, and calculate an amount of CO2 emissions when the user traveled using the determined moving means; [¶0029]: In order for the carbon saving quantity quantization algorithm to properly monitor carbon emission, it monitors how many trips use a vehicle versus walking by foot.
calculate, as the amount of environmental impact, a reduced amount of emissions by subtracting the actual amount of CO2 emission from the baseline amount of CO2 emissions; and [¶0029 - 0030]: In order for the carbon saving quantity quantization algorithm to properly monitor carbon emission, it monitors how many trips use a vehicle versus walking by foot. [¶0030]: Shows the second present algorithm determining carbon savings related to walking vs driving.
calculate, as the evaluation value, a score based on the reduced amount of emissions and the coefficient, [¶0040]: User data is processed to produce an x number of points, which may then be converted to a total points value.
wherein the user behavior includes movement by the moving means of the user, wherein the service server is configured to be accessed by a terminal of a target user to be evaluated so as to allow the target user to view the evaluation value, and to prompt the target user to take an action corresponding to the evaluation value; [¶0033]: The second preset algorithm relating to user behavior includes carbon-saving quantities based on trips—whether that by via vehicle or walking trips.
Jin does not disclose the following limitations below. Thus, Chapman teaches:
a traffic jam database configured to store attribute information of the user. [¶0109]: A traffic information provider system is paired either directly or indirectly to a database or a storage device in order to store future traffic conditions as well as condition predictions.
It would have been obvious to one of ordinary skill in the art before the earliest effective filing date of the invention to combine Jin’s disclosure for calculating individual carbon footprints as well as reduced carbon emissions with a traffic jam database, as taught by Chapman, in order to efficiently and effectively monitor and store traffic conditions as well as future predictions/assessments of traffic.
Regarding claim 3:
Jin teaches:
wherein the behavior of the user further includes at least one of communication of a communication means used by the user, use of electricity by the user, and purchase behavior of the user. [¶0021]: The disclosure may be associated with a health service mobile application to monitor movement behavior. [¶0075]: The implementation may also associate and track utility usage (i.e., water usage, electricity usage, natural gas usage, etc.) [¶0044]: Furthermore, user data may also include a user purchase data.
Regarding claim 7:
Jin teaches:
wherein the movement by the moving means of the user is a specific state of the user. [¶0021]: The disclosure may be associated with a health service mobile application to monitor movement behavior. Furthermore, [¶0029, 0035]: Preset algorithms are put in place to accurately determine how much carbon emission can be saved by different modes of transportation. [¶0087]: “Walking data can be produced by a health service application (for example, a walking application) having a walking data collection function. The walking data can be used as behavior data for walking. “
Regarding claim 8:
Jin teaches:
wherein processing circuitry calculates the amount of environmental impact generated in a unit of movement, Figs. 1, 2E, 3; [¶0089]: An example method is used to acquire and calculate how much carbon-saving quantity a user produces just by walking.
derives the coefficient in the unit of movement, and [¶0087]: Carbon-saving quantity is directly associated with a user’s walking behavior, which entails number of steps, location information, walking distance, etc.
evaluates the behavior of the user in the unit of movement. Fig. 2E; [¶0089 - 0091]: An acquisition request is sent, including all applicable walking data, in order to compute a carbon-saving quantity unit through an algorithm.
Regarding claim 10:
Jin teaches:
wherein the processing circuitry derives the coefficient corresponding to a number of purchased products of a predetermined category as the behavior of the user. Figs 2A-2E, 3; [¶0042]: User behavior data is tracked and collected throughout different scenarios (i.e., [¶0043] being an online ticketing service, [¶0054] being an online payment service, [¶0064]: being an online reservation service, etc.)
Claims 5 and 9 are rejected under 35 U.S.C. § 103 as being unpatentable over Jin (U.S. Pub No. 20190213097 A1) in view of Chapman (U.S. Pub No. US20120150425 A1) in further view of Blackhurst (U.S. 20150032586 A1).
Regarding claim 5:
Although Jin teaches a user inputting information into their account and having user activity stored [¶0022], Jin does not teach wherein the attributes includes at least one of a gender, age, place of residence, household type, and occupation of the user. Thus, Blackhurst teaches:
wherein the coefficient is further derived based on attributes of the user include at least one of a gender, age, place of residence, household type, and occupation of the user. [¶0047]: Customer attributes (i.e., customer demographics, customer input, transaction data, ages of each household member, model and number of cars associated with the household, etc.) are used to determine when alternative carbon emission data.
It would have been obvious to one of ordinary skill in the art before the earliest effective filing date to modify Jin’s disclosure for calculating individual carbon footprints as well as reduced carbon emissions with having attributes include at least one of a gender, age, place of residence, household type, and occupation of the user, as taught by Blackhurst, in order to effectively and efficiently identify user behavior and use the data collected to calculate more precise measurements.
Regarding claim 9:
Jin does not teach the coefficient derivation portion deriving a coefficient corresponding to an amount of communication of the user when a contract for a predetermined plan, which is a communication plan, is made as the behavior of the user. Thus, Blackhurst teaches:
wherein the processing circuitry derives the coefficient corresponding to an amount of communication of the user when a contract for a predetermined plan, which is a communication plan, is made as the behavior of the user. Fig. 3; [¶0056]: The disclosure teaches retrieval of electronic communications relating to customer purchase transactions, with the inclusion of data being tracking consumer consumption.
It would have been obvious to one of ordinary skill in the art before the earliest effective filing date to combine Jin’s disclosure for calculating individual carbon footprints as well as reduced carbon emissions with the coefficient derivation portion derives a coefficient corresponding to an amount of communication of the user when a contract for a predetermined plan, which is a communication plan, is made as the behavior of the user, as taught by Blackhurst, in order to effectively and efficiently identify user behavior and use the data collected to calculate more precise measurements.
Pertinent Art
The prior art made of record and not relied upon is considered pertinent to applicant’s disclosure.
Silby (US20060089851 A1) is pertinent because it is related to “methods and apparatus for using billing statements to provide consumers with their individual carbon usage in the matter of global warming, thereby allowing the opportunity for the consumer to take responsibility for their carbon emissions.”
Silverstein (US20210224819 A1) is pertinent because it is related to “the field of reduction of greenhouse gas emissions, and more particularly to carbon footprint tracking.”
Yoder (US20060286518 A1) is pertinent because it is related to “a system and method for managing personalized information regarding a product. In particular, the invention relates to a computer-implemented system and method for calculating and communicating personalized product environmental information to a user, for accounting for pollution resulting from raw material production, manufacture, use disposal and packaging of the purchased product and for accounting for price surcharges paid by the purchaser.”
Kaminsky (US20100030608 A1) is pertinent because it is related to “a system and method for a carbon calculator and, more particularly, to a system and method for a carbon calculator including offset costs.”
Zhu (US20230089850 A1) is pertinent because it is related to a “system, method, and computer program product embodiments for utilizing non-RAM memory to implement environmental impact scoring.”
Ellingham (US20100328314 A1) is pertinent because it is related to “the field of energy conservation and, more particularly, to aiding individuals in the conservation of energy.”
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Bill Chen whose telephone number is (571)270-0660. The examiner can normally be reached Monday - Friday 8:30am - 5:00pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Nathan Uber can be reached on (571) 270-3923. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BILL CHEN/Examiner, Art Unit 3626
/NATHAN C UBER/Supervisory Patent Examiner, Art Unit 3626
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