DETAILED ACTION
Non-Final Rejection
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 .
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 1-22 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Each of claims1-22 falls within one of the four statutory categories. See MPEP § 2106.03. Each of claims 1-7 and 16-21 fall within category of process; Each of claim 9- 15 fall within category of machine, i.e., a “concrete thing, consisting of parts, or of certain devices and combination of devices.” Digitech, 758 F.3d at 1348–49, 111 USPQ2d at 1719 (quoting Burr v. Duryee, 68 U.S. 531, 570, 17 L. Ed. 650, 657 (1863)); and each of claims 8 and 22 is directed to a “One or more computer-readable media” and therefore falls within category of manufacture.1
Regarding Claims 1-7
Step 2A – Prong 1
Exemplary claim 1 is directed to an abstract idea of generating interval data associated with the billed consumption data.
The abstract idea is set forth or described by the following italicized limitations:
1. A method comprising:
receiving sample interval data for a first period of time from a sample meter associated with a customer class;
determining first weather data associated with the first period of time;
generating a load profile based at least in part on the sample interval data and the first weather data;
receiving billed consumption data associated with a utility meter;
determining that the utility meter is associated with the customer class;
determining that second weather data associated with the utility meter corresponds to the first weather data;
applying the load profile to the billed consumption data based at least in part on the utility meter being associated with the customer class and the second weather data associated with the utility meter corresponding to the first weather data;
generating interval data associated with the billed consumption data based at least in part on applying the load profile to the billed consumption data; and
storing the interval data.
The italicized limitations above represent a mental step (i.e., fundamental economic practice, a sales activity, managing interactions between people, and/or a process that can be performed by can be performed mentally and/or with pen and paper). Therefore, the italicized limitations fall within the subject matter groupings of abstract ideas enumerated in Section I of the 2019 Revised Patent Subject Matter Eligibility Guidance.
For example, the limitations “determining first weather data [..]; generating a load profile [..]; determining that the utility meter is associated with the customer class; determining that second weather data associated with the utility meter [..]; applying the load profile to the billed consumption data [..]; generating interval data associated with the billed consumption data [..]” are mental steps (i.e., fundamental economic practice, a sales activity, managing interactions between people, and/or a process that can be performed by can be performed mentally and/or with pen and paper), see 2106.04(a)(2).
Step 2A – Prong 2
Claims 1 does not include additional elements (when considered individually, as an ordered combination, and/or within the claim as a whole) that are sufficient to integrate the abstract idea into a practical application.
For example, first additional first element is “ receiving sample interval data for a first period of time from a sample meter associated with a customer class; receiving billed consumption data associated with a utility meter; storing the interval data” to be performed, at least in-part, these additional elements appear to only add insignificant extra-solution activity (e.g., data gathering) and only generally link the abstract idea to a particular field. Therefore, this element individually or as a whole does not provide a practical application. See MPEP 2106.05(g).
For Examples, 2nd additional first element is “a sample meter associated with a customer class; a utility meter”: This element amounts to mere use of a generic sensor device , which is well understood routine and conventional (see background of current discloser and IDS and PTO 892) and this element individually does not provide a practical application. In view of the above, the “additional element” individually or combine does not provide a practical application of the abstract idea. see MPEP 2106.05(d).
In view of the above, the three “additional elements” individually do not provide a practical application of the abstract idea.
Step 2B
Claims1 does not include additional elements, when considered individually and as an ordered combination, that are sufficient to amount to significantly more than the abstract idea. For example, the limitation of Claim 1 contains additional elements that are, i.e. a sample meter associated with a customer class; a utility meter”, generic devices, which are well understood, routine and conventional (see background of current discloser and IDS and PTO 892) and MPEP 2106.05(d))The reasons for reaching this conclusion are substantially the same as the reasons given above in § Step 2A – Prong 2. For brevity only, those reasons are not repeated in this section. See MPEP §§ 2106.05(g) and MPEP §§2106.05(II).
Dependent Claims 2-7
Dependent claims 2-7 fail to cure this deficiency of independent claim 1 (set forth above) and are rejected accordingly. Particularly, claims 2-7 recite limitations that represent (in addition to the limitations already noted above) either the abstract idea or an additional element that is merely extra-solution activity, mere use of instructions and/or generic computer component(s) as a tool to implement the abstract idea, and/or merely limits the abstract idea to a particular technological environment.
For Examples, claim 2-7: imitations a combination of mental steps (i.e., fundamental economic practice, a sales activity, managing interactions between people, and/or a process that can be performed by can be performed mentally and/or with pen and paper) a, see 2106.04(a)(2).
Regarding Claims 8-20
Claims 8-20 contains language similar to claims 1-7 as discussed in the preceding paragraphs, and for reasons similar to those discussed above, claims 8-20 are also rejected under 35 U.S.C. § 101(abstract idea). Furthermore, claim 8, 9 and 22 contain the additional elements “a sample meter associated with a customer class; a utility meter ”. This element amounts to mere use of a generic device with computer components, which is well understood routine and conventional (see background of current discloser and IDS and PTO 892) and this element individually does not provide a practical application. In view of the above, the “additional element” individually or combine does not provide a practical application of the abstract idea. see MPEP 2106.05(d).
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claim(s) 1 and 3-22 is/are rejected under 35 U.S.C. 102(a)(1)as being anticipated by Shilts et al.( US 20160042049).
Regarding Claims 1 and 8. Shilts teaches a method comprising(abstract):
receiving sample interval data for a first period of time from a sample meter (631: fig.6; 101a: fig. 1)associated with a customer class(630: fig. 6; The smart meter device may broadcast usage data on a periodic or scheduled basis: [0060]-[0061]; first time period: [0055] );
determining first weather data associated with the first period of time(peak users that consume more resources during a first time period : [0055]; receive corresponding outdoor temperatures from the third party weather service via the network: [0064]);
generating a load profile based at least in part on the sample interval data and the first weather data(generating a respective load curve based at least in part on the percentage of the total amount of energy usage at each of the specified intervals over the specified time period:[0054]; identifying the subset of the plurality of users that are peak users further comprises: determining one or more load curve archetypes, each load curve archetype including a respective load curve that represents a type of user based on energy consumption tracked during a period of time: [0055]; receive corresponding outdoor temperatures from the third party weather service via the network: [0064]);
receiving billed consumption data associated with a utility meter(632: fig. 6; usage-information may include past usage information of the commodity during at least one of completed billing period and a current usage of the at least one of the one or more commodities during a completed portion of a current billing period. The usage data for a utility customer may be obtained from a corresponding monitoring device on a scheduled basis, periodic basis or a non-scheduled basis. The monitoring devices (e.g., monitoring devices 102 a, 102 b . . . 102 n) may relate to an advanced metering infrastructure (AMI), 632: [0025], [0064]);
determining that the utility meter (632: fig. 6) is associated with the customer class(630: fig. 1; [0060]);
determining that second weather data associated with the utility meter corresponds to the first weather data(Each of the utility customer regions 610, 620 and 630 may correspond to a separate geographical location with a respective rate schedule. In some aspects, an energy usage alert notification for a corresponding utility customer in one region may be generated using usage data of similar users in the same region to provide the corresponding utility customer with a comparative analysis of its energy consumption (e.g., current energy usage compared to similar customers in the same zip code or within a certain radius):[0063]; forecasted weather conditions: [0064]);
applying the load profile to the billed consumption data based at least in part on the utility meter being associated with the customer class and the second weather data associated with the utility meter corresponding to the first weather data(the usage alert system 660 may use data from the third party weather service to determine a projected use for a current billing period. For example, forecasted weather conditions (e.g., the temperature, the humidity, the barometric pressure, precipitation, etc.) may indicate that the utility customer's HVAC system is likely to be in greater use. The usage alert system 660 may estimate the projected use for the remaining amount of time of the current billing period, and thereby determine if the utility customer is on pace to exceed the projected bill based on the estimated projected us: [0064]);
generating interval data associated with the billed consumption data based at least in part on applying the load profile to the billed consumption data(estimate the projected use for the remaining amount of time of the current billing period, and thereby determine if the utility customer is on pace to exceed the projected bill based on the estimated projected us: [0064]: [0064]); and
storing the interval data(stored as information in the load curve data 107. The load curve may represent the user's energy consumption over a specified time period. Storing usage data 712 and user information 716, which can be used to generate the energy usage alert notification. The data plane 710 is also shown to include a mechanism for storing similar user data 714, which can be used for purposes such as reporting a comparative analysis of the usage data for the corresponding utility customer. The data plane 710 is operable, through logic associated therewith, to receive instructions from the application server 708 and to obtain, update, or otherwise process data:[0029], [0076]).
Regarding Claims 3, 11 and 18. Shilts teaches validating the billed consumption data prior to applying the load profile to the billed consumption data, wherein the validating includes a maximum threshold value and a minimum threshold value(peak uses , off-peak uses: [0022]; 406, 407: fig. 4A; [0044]).
Regarding Claims 4, 12 and 19. Shilts teaches determining a first register value associated with the billed consumption data(i.e. projected: [0027], [0064], [0070]);
determining a second register value associated with the billed consumption data(target: [0027], [0064], [0070]);
and generating a register read value associated with the billed consumption data based at least in part on a difference between the first register value and the second register value(projected bill exceeding target budget: [0027], [0064], [0070]),
wherein applying the load profile to the billed consumption data comprises applying the load profile to the register read value(provide one or more recommendations to one or more of utility customers 101 a, 101 b to 101 n for reducing energy usage: [0027], [0070]-[0073]: fig.7).
Regarding Claims 5, 13 and 20. Shilts teaches generating an interval container having a number of intervals (. The report module 113 may be configured to generate a usage alert notification, and cause the usage alert notification to be sent to one or more of the utility customers 101 a-101 n based on one or more reporting conditions (e.g., projected bill exceeding target budget, current billing period ended, utility customer inquiry, etc.: [0027]); and
storing the register read value in the interval container such that the register read value is distributed amongst the number of intervals(one or more reporting conditions (e.g., projected bill exceeding target budget, current billing period ended, utility customer inquiry, etc.: [0027]; The data stores of the data plane 710 can include several separate data tables, databases, or other data storage mechanisms and media for storing data relating to a particular aspect, reporting a comparative analysis:[0075]-[0076]).
Regarding Claims 6 and 14. Shilts teaches the customer class comprises at least one of a residential customer, a commercial customer, or an industrial customer(630: fig. 6).
Regarding Claims 7 and 15. Shilts teaches generating the load profile comprises utilizing one or more statistical models(406: fig. 4A; the load curve 406 includes a graphical representation of the average energy usage or consumption: [0044]).
Regarding Claim 9. Shilts teaches a system comprising(660: fig. 6; fig.8):
one or more processors(802:fig. 8);
a memory(804); and
instructions stored in the memory that, when executed by the one or more processors, cause the one or more processors to perform operations comprising(fig.8):
receiving sample interval data for a first period of time(630: fig. 6; The smart meter device may broadcast usage data on a periodic or scheduled basis: [0060]-[0061]; first time period: [0055] ) from a sample meter(631: fig.6; 101a: fig. 1);
determining a first customer class associated with the sample meter(peak users that consume more resources during a first time period : [0055]; receive corresponding outdoor temperatures from the third party weather service via the network: [0064]);
generating a load profile based at least in part on the sample interval data(generating a respective load curve based at least in part on the percentage of the total amount of energy usage at each of the specified intervals over the specified time period:[0054]; identifying the subset of the plurality of users that are peak users further comprises: determining one or more load curve archetypes, each load curve archetype including a respective load curve that represents a type of user based on energy consumption tracked during a period of time: [0055]; receive corresponding outdoor temperatures from the third party weather service via the network: [0064]);
receiving billed consumption data associated with a utility meter(632: fig. 6; usage-information may include past usage information of the commodity during at least one of completed billing period and a current usage of the at least one of the one or more commodities during a completed portion of a current billing period. The usage data for a utility customer may be obtained from a corresponding monitoring device on a scheduled basis, periodic basis or a non-scheduled basis. The monitoring devices (e.g., monitoring devices 102 a, 102 b . . . 102 n) may relate to an advanced metering infrastructure (AMI), 632: [0025], [0064]);
determining that the utility meter (632: fig. 6)is associated with a second customer class(630: fig. 1; [0060]);
determining that the second customer class is of a same type as the first customer class([0060]);
applying the load profile to the billed consumption data based at least in part on the second customer class being of the same type as the first customer class(the usage alert system 660 may use data from the third party weather service to determine a projected use for a current billing period. For example, forecasted weather conditions (e.g., the temperature, the humidity, the barometric pressure, precipitation, etc.) may indicate that the utility customer's HVAC system is likely to be in greater use. The usage alert system 660 may estimate the projected use for the remaining amount of time of the current billing period, and thereby determine if the utility customer is on pace to exceed the projected bill based on the estimated projected us: [0064]);
generating interval data associated with the billed consumption data based at least in part on applying the load profile to the billed consumption data(estimate the projected use for the remaining amount of time of the current billing period, and thereby determine if the utility customer is on pace to exceed the projected bill based on the estimated projected us: [0064]: [0064]); and
storing the interval data(stored as information in the load curve data 107. The load curve may represent the user's energy consumption over a specified time period. Storing usage data 712 and user information 716, which can be used to generate the energy usage alert notification. The data plane 710 is also shown to include a mechanism for storing similar user data 714, which can be used for purposes such as reporting a comparative analysis of the usage data for the corresponding utility customer. The data plane 710 is operable, through logic associated therewith, to receive instructions from the application server 708 and to obtain, update, or otherwise process data:[0029], [0076]).
Regarding Claims 10 and 17. Shilts teaches applying the load profile to the billed consumption data is based at least in part on determining that first weather data associated with the utility meter corresponds to second weather data associated with the sample meter([0063]-[0064]).
Regarding Claims16 and 22. Shilts teaches a method comprising(abstract):
receiving sample interval data for a first period of time (630: fig. 6; The smart meter device may broadcast usage data on a periodic or scheduled basis: [0060]-[0061]; first time period: [0055] ) from a sample meter(631: fig.6; 101a: fig. 1);
generating a load profile based at least in part on the sample interval data;
receiving billed consumption data associated with a site(generating a respective load curve based at least in part on the percentage of the total amount of energy usage at each of the specified intervals over the specified time period:[0054]; identifying the subset of the plurality of users that are peak users further comprises: determining one or more load curve archetypes, each load curve archetype including a respective load curve that represents a type of user based on energy consumption tracked during a period of time: [0055]; receive corresponding outdoor temperatures from the third party weather service via the network: [0064]);
applying the load profile to the billed consumption data(the usage alert system 660 may use data from the third party weather service to determine a projected use for a current billing period. For example, forecasted weather conditions (e.g., the temperature, the humidity, the barometric pressure, precipitation, etc.) may indicate that the utility customer's HVAC system is likely to be in greater use. The usage alert system 660 may estimate the projected use for the remaining amount of time of the current billing period, and thereby determine if the utility customer is on pace to exceed the projected bill based on the estimated projected us: [0064]);
generating interval data associated with the billed consumption data based at least in part on applying the load profile to the billed consumption data(estimate the projected use for the remaining amount of time of the current billing period, and thereby determine if the utility customer is on pace to exceed the projected bill based on the estimated projected us: [0064]: [0064]); and
storing the interval data(stored as information in the load curve data 107. The load curve may represent the user's energy consumption over a specified time period. Storing usage data 712 and user information 716, which can be used to generate the energy usage alert notification. The data plane 710 is also shown to include a mechanism for storing similar user data 714, which can be used for purposes such as reporting a comparative analysis of the usage data for the corresponding utility customer. The data plane 710 is operable, through logic associated therewith, to receive instructions from the application server 708 and to obtain, update, or otherwise process data:[0029], [0076]).
Regarding Claim 21. Shilts teaches applying the load profile to the billed consumption data is based at least in part on a customer class associated with the site (generating a respective load curve based at least in part on the percentage of the total amount of energy usage at each of the specified intervals over the specified time period:[0054]; identifying the subset of the plurality of users that are peak users further comprises: determining one or more load curve archetypes, each load curve archetype including a respective load curve that represents a type of user based on energy consumption tracked during a period of time: [0055]; 630: fig. 6).
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) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over
Shilts et al.( US 20160042049) in view of Zoldi et al. (US 2009/0045976).
Regarding Claim 2. Shilts silent about determining that second weather data associated with the utility meter corresponds to the first weather data is based on the utility meter being in a service territory associated with the sample meter.
However, Zoldi teaches determining that second weather data associated with the utility meter corresponds to the first weather data is based on the utility meter being in a service territory associated with the sample meter([0025],[0034]-[0035], [0041]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to the invention of Shilts, determining that second weather data associated with the utility meter corresponds to the first weather data is based on the utility meter being in a service territory associated with the sample meter, as taught by Zoldi, so as to predict areas of revenue leakage and network failure in real-time, thus the method allows timely investigation and resolution of revenue assurance and network issues to protect revenue and quality of service delivered to the end consumer effectively.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
a) Patricia et al. (US 20210125129) disclose receiving at least one utility consumption information from at least one utility consumption information source, wherein the at least one utility consumption information is associated with consumption of at least one utility corresponding to the at least one premises; receiving at least one premises information from at least one premises information source, wherein the at least one premises information is associated with the at least one premises; receiving at least one lifestyle information from at least one lifestyle information source, wherein the at least one lifestyle information is associated with at least one occupant of the at least one premises; and transmitting at least one utility fingerprint associated with the at least one premises to at least one electronic device;.
b) Singh et al. (US 20200118223) disclose Using artificial intelligence to automatically and intelligently extract critical data from utility bills, enrich the extracted data with other data, categorize the data, validate and detect anomalies in the data, draw insights from the data, and pro actively present usage recommendations based on the insights and respond to user inquiries regarding the data through a user-friendly interface.
c) Dan. et al. (US 20140188565) disclose describes techniques for detecting changes in demographic data of a customer based on energy consumption data of the customer. For example, a customer data management system receives energy consumption data of a customer and detects, based at least in part on the received energy consumption data of the customer, a change in demographic data associated with the customer. The customer data management system then outputs, based at least in part on the detecting, at least one demographic change report associated with the demographic data.
d) Jar. (US 20060106741) disclose A utility monitoring system and method for relaying to a consumer personalized utility consumption information in order to induce the consumer to conserve the utility. The system includes a data source, a processor coupled to the data source, and a display unit coupled to the processor. The processor receives utility consumption information from the data source. The processor then generates enhanced utility consumption information, as well as a display of the data. The processor may also provide Demand-Side Management for utility conservation based on the utility consumption information and the consumer's settings. The display is then transmitted to the display unit to be displayed. The display unit resides in the consumer's home or business. A broadband server may also be used to provide customized broadband information.
e) Joseph (US 20180293674) disclose A system of collecting retail consumer electricity kilowatt hour consumption interval data from the electric distribution company meter, on a real-time basis, at a multiple of locations, for the purpose of procuring and billing interval consumption through a wholesale electricity market managed by an independent system operator and billing those costs to specific customers based on their actual electricity consumption intervals. All customer electricity consumption is collected on a universal time interval and transmitted using cellular or wireless communications to a central data center and energy trading desk. When purchases of interval loads are completed for the day, the data server software allocates aggregate electricity costs back to individual customer accounts based on actual interval loads. Customers have access to real-time consumption and corresponding wholesale prices for purposes of curtailing consumption to reduce electricity interval costs. The system includes a billing mechanism for single rate billing on the electric distribution company utility bill.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMAD K ISLAM whose telephone number is (571)270-0328. The examiner can normally be reached M-F 9:00 a.m. - 5:00 p.m..
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shelby A Turner can be reached at 571-272-6334. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MOHAMMAD K ISLAM/ Primary Examiner, Art Unit 2857
1 Applicant’s specification defines “One or more computer-readable media” as “computer-readable media and may take the form of volatile memory, such as random-access memory (RAM) and/or non-volatile memory, such as read only memory (ROM) or flash RAM. Computer-readable media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storage of information such as computer-readable instructions” ([0023]).