DETAILED ACTION
This Office Action is in reply to Applicants response after Non-Final rejection received on December 11, 2025. Claim(s) 1-18 and 20-21 is/are currently pending in the instant application. The application claims priority to U.S. Provisional application 63/464,107 filed on May 4, 2023.
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 .
Response to Amendment
The Examiner acknowledges the Applicants amendments to claims 1-14 and 20 in the response filed on December 11, 2025. Claim 19 has been canceled at this time and new claim 21 is added.
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 1-18 and 20-21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claims 1-18 and 20-21 are directed to one of the four statutory classes of invention (e.g. process, machine, manufacture, or composition of matter). The claims include a system or “apparatus”, method or “process”, or product or “article of manufacture” and is a system and method of energy resource optimization which is a process (Step 1: YES).
The Examiner has identified independent method Claim 14 as the claim that represents the claimed invention for analysis and is similar to independent system Claim 1 and product Claim 20. Claim 14 recites the limitations of (abstract ideas highlighted in italics and additional elements highlighted in bold)
accessing, by one or more processors, preference data that identifies a target value for a condition of a device and an acceptable variation from the target value;
generating a power cost signal based on power cost data and incentive data;
generating, based on the preference data and the power cost signal, a schedule for power consumption by the device by minimizing a function comprising a first term representing a weighted cost and a second term representing a weighted amount of time that a value of the condition of the device differs from the target value by more than the acceptable variation; and
sending commands from a server to the device via a network, thereby causing the device to consume power according to the schedule.
These limitations, under their broadest reasonable interpretation, cover performance of the limitation as “Certain Methods of Organizing Human Activity”. Evaluating preference data for a condition and variation from target, generating a signal based on cost and incentive data, and generating a schedule for consumption with acceptable variation and following the schedule recites a fundamental economic practice and/or commercial interactions. Accordingly, the claim recites an abstract idea. The memory storing instructions and one or more processors in Claim 1 is just applying generic computer components to the recited abstract limitations. The non-transitory computer-readable medium that stores instructions executed by a processor in Claim 20 appears to be just software. Claims 1 and 20 are also abstract for similar reasons. (Step 2A-Prong 1: YES. The claims are abstract)
This judicial exception is not integrated into a practical application. In particular, the claims only recite a memory and one or more processors, and a device (Claim 1) a processor, a server and a network (claim 14) and/or non-transitory computer-readable medium storing instructions and executed by one or more processors (Claim 20). The computer hardware is recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Therefore claims 1, 14, and 20 are directed to an abstract idea without a practical application. (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 because, when considered separately and as an ordered combination, they do not add significantly more (also known as an “inventive concept”) to the exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer hardware 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. See Applicant’s specification para. [0029-0030] about implantation using general purpose or special purpose computing devices [the device 130A may be a desktop computer, a vehicle computer, a tablet computer, a navigational device, a portable media device, or a smart phone belonging to the user 150…Any of the machines, databases, or devices shown in FIG. 1 may be implemented in a general-purpose computer modified (e.g., configured or programmed) by software to be a special-purpose computer to perform the functions described herein for that machine, database, or device.] and MPEP 2106.05(f) where applying a computer as a tool is not indicative of significantly more.<< Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus claims 1, 14, and 20 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more)
Dependent claims 2-13, and 15-18 and 21 further define the abstract idea that is present in their respective independent claims 1 and 14 and thus correspond to Certain Methods of Organizing Human Activity and hence are abstract for the reasons presented above. The dependent claims do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. The dependent claims include steps or processes which are similar to that disclosed in MPEP 2106.05(d), (f), (g), and/or (h) which include activities and functions the courts have determined to be well-understood, routine, and conventional when claimed in a generic manner, or as insignificant extra solution activity, or as merely indicating a field of use or technological environment in which to apply the judicial exception. Therefore, the claims 2-13, and 15-19 are directed to an abstract idea. Thus, the claims 1-20 are not patent-eligible.
Claim Rejections - 35 USC § 102
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 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) 1-2, 5, 8-15, 18, 20-21 is/are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Reeder U.S. Publication 2022/0253078 A1 (hereafter Reader).
Regarding claim 1, a memory that stores instructions (see at least [0176] Storage devices suitable for tangibly embodying computer program instructions and data include all forms of non-volatile memory,); and
one or more processors configured by the instructions to perform operations (see at least [0176] a processor will receive instructions and data from a read-only memory and/or a random access memory.) comprising:
accessing preference data that identifies a target value for a condition of a device and an acceptable variation from the target value (see at least [0049] An HVAC comfort model can heavily rely upon user specified set temperature points for home, sleep, away, vacation/traveling, and “energy aware” modes. Each of these sets points can include a range of acceptable temperatures (68-72 F) or a desired “ideal” temperature and a requested/required accuracy (70 F with a degree of error of 2 F).);
generating a power cost signal based on power cost data and incentive data (see at least [0133] the control unit may initiate a time of the pre-cooling method before a start time of the on-peak hours. To reduce the overall grid constrain, the control unit may start the pre-cooling method for a particular property well in advance of the on-peak hours, such as one or two hours before, to name a few examples. Alternatively, the control unit may start the pre-cooling method for a particular property such that the property reaches a desired temperature at the start time of the on-peak hours. For example, if the control unit can determine an amount of time for the monitored property to move between temperatures, then the control unit can initiate the pre-cooling method the determined amount of time from the start time of the on-peak hours.);
generating, based on the preference data and the power cost signal, a schedule for power consumption by the device by minimizing a function comprising a first term representing a weighted cost and a second term representing a weighted amount of time that a value of the condition of the device differs from the target value by more than the acceptable variation (see at least [0134] the control unit may initiate a time of the pre-cooling method before a start time of the on-peak hours. To reduce the overall grid constrain, the control unit may start the pre-cooling method for a particular property well in advance of the on-peak hours, such as one or two hours before, to name a few examples. Alternatively, the control unit may start the pre-cooling method for a particular property such that the property reaches a desired temperature at the start time of the on-peak hours. For example, if the control unit can determine an amount of time for the monitored property to move between temperatures, then the control unit can initiate the pre-cooling method the determined amount of time from the start time of the on-peak hours. [0135] The control unit can instruct the HVAC system of the monitored property to cycle off and on based on the generated duty-cycle during the on-peak hours (410). For example, in response to a time during a start of the on-peak hours, the control unit can instruct the HVAC system to operate at a 50% duty-cycle per hour to reach a desired temperature during the on-peak hours. [0070] Customers can also input what temperature sensor they desire to use with each of the settings above (for example, comparing the master bedroom temperature to the set point temperature when in “sleep” mode). Based on the differences between the different set point values, the control unit 104 can extract their preference for comfort (which is particularly based on the difference between their home and away set points). This is used to inform how aggressive the control unit 104 is in pursuing savings for the customer. [0131] For example, the control unit can determine that the monitored property can adjust from 71 degrees Fahrenheit to 75 degrees Fahrenheit in 30 minutes from 8:00 AM to 10:00 AM and 15 minutes from 5:00 PM to 7:00 PM in the southwestern part of the United States. Outside of the threshold value, .e.g., 5 degrees Fahrenheit different, the adjustment between the two temperatures can take longer than 30 minutes and 15 minutes, at the respective timeframes. Continuing with this example, the control unit can determine that the on-peak hours starts at 5:30 PM and lasts until 8:30 PM and a desired temperature of 75 degrees Fahrenheit is to be reached. Because the control unit has determined that the monitored property can adjust between two different temperatures in 15 minutes between 5:00 PM and 7:00 PM and the current temperature of the property is 85 degrees Fahrenheit, the control unit can decide to implement the pre-cooling method before the on-peak hours to reach a temperature of 80 degrees before the on-peak hours start, which is within the threshold difference value of 5 degrees Fahrenheit. Then, during the on-peak hours, the control unit only needs to move the temperature 5 degrees, e.g., between 80 degrees to 75 degrees, which ultimately reduces the overall energy consumption, energy cost, and load on the electric grid. Further, the control unit can instruct the HVAC system with a duty cycle during the on-peak period, which reduces the energy consumption even further, by splitting up the HVAC energy consumption of a 5-degree temperature difference across multiple time periods during the on-peak period. The control unit can execute a pre-cooling method that instructs the HVAC system to reach a set temperature in the monitored property before the on-peak hours to help reduce the overall consumption of energy during the on-peak period. The system can use the difference between two setpoint values to control the unit based on cost savings by cooling partially when it’s more cost effective and only having to run a shirt time when it’s more high demand) ; and
sending commands to the device, thereby causing the device to consume power according to the schedule (see at least [0120] a customer with two A/C units and a solar install may run an HVAC runtime algorithm that alternates their two A/C units so they are never on at the same time, and that has a higher run-time from 3-4 pm than from 7-8 pm. So on a 105° F. day, the HVAC runtime schedule might look like this (APS): 3:00 PM-4:00 PM: 50% duty-cycle; 4:00 PM-5:00 PM: 40% duty-cycle; 5:00 PM-6:00 PM: 30% duty-cycle; 6:00 PM-7:00 PM: 20% duty-cycle; and, 7:00 PM-8:00 PM: 15% duty-cycle. [0153] A module 537 is connected to one or more components of an HVAC system associated with a property, and is configured to control operation of the one or more components of the HVAC system. In some implementations, the module 537 is also configured to monitor energy consumption of the HVAC system components, for example, by directly measuring the energy consumption of the HVAC system components or by estimating the energy usage of the one or more HVAC system components based on detecting usage of components of the HVAC system. The module 537 can communicate energy monitoring information and the state of the HVAC system components to the thermostat 534 and can control the one or more components of the HVAC system based on commands received from the thermostat 534.)
Regarding claim 2, wherein: the device is a heating unit, an air-conditioning unit, or a hot-water heater (see at least [0002] This specification generally relates to monitoring technology and, for example, Heating Ventilation and Air Conditioning (HVAC) systems.);
the condition of the device is a temperature of the device;
the target value is a target temperature for heating or cooling (see at least [0003] HVAC systems may perform cooling functions by circulating air over evaporator coils to remove heat from the air, and heating functions by using a furnace to heat air from a source vent and blowing the heated air through return vents.); and
the acceptable variation from the target value defines an acceptable temperature range (see at least [0099] The peak protect module can receive feedback from a certain duty-cycle when target temperature is not precisely hit. For example, the peak protect module may select a minimum and maximum temperature and try to hit the minimum temperature during pre-cool during the on-peak period.).
Regarding claim 5, wherein the power cost signal has an hourly, quarter-hourly, or minute-level granularity (see at least [0131] the control unit can determine that the monitored property can adjust from 71 degrees Fahrenheit to 75 degrees Fahrenheit in 30 minutes from 8:00 AM to 10:00 AM and 15 minutes from 5:00 PM to 7:00 PM in the southwestern part of the United States. Outside of the threshold value, .e.g., 5 degrees Fahrenheit different, the adjustment between the two temperatures can take longer than 30 minutes and 15 minutes, at the respective timeframes. Continuing with this example, the control unit can determine that the on-peak hours starts at 5:30 PM and lasts until 8:30 PM and a desired temperature of 75 degrees Fahrenheit is to be reached. Because the control unit has determined that the monitored property can adjust between two different temperatures in 15 minutes between 5:00 PM and 7:00 PM and the current temperature of the property is 85 degrees Fahrenheit, the control unit can decide to implement the pre-cooling method before the on-peak hours to reach a temperature of 80 degrees before the on-peak hours start, which is within the threshold difference value of 5 degrees Fahrenheit.).
Regarding claim 8. The system of claim 1, wherein the power cost signal is further based on solar power production at a location of the device (see at least [0046] The HVAC model can, in some cases, predict a run time needed for the temperature in a monitored property to move from point A to point B over a period. For example, the HVAC model can indicate in an Arizona summer the minimum AC run time required to only allow the monitored property to move back from 75 F to 85 F (without going over) over the on-peak electric price period from 3:00 PM-8:00 PM. The prediction can rely on, for example, previous observed run time, temperatures (internal and external), and other data, such as, solar data, appliance usage, energy usage of each appliance, door/window openings, and other energy usage in the monitored property.).
Regarding claim 9, wherein the preference data further indicates a maximum price for power to be paid to avoid variation beyond the acceptable variation (see at least [0049] Each of these sets points can include a range of acceptable temperatures (68-72 F) or a desired “ideal” temperature and a requested/required accuracy (70 F with a degree of error of 2 F). Additionally, each set point can optionally be tied to a specific temperature sensor, such as, in a bedroom, in the kitchen, and in the basement, to name a few examples. Additionally, the HVAC comfort model can also heavily rely upon global presence detection to determine if residents of the monitored property 102 are at home and awake, at home and asleep, or are away from the property. [0138] the control unit can take additional processes in case the monitored property will not reach the target temperature during a time period identified by the on-peak period with the designated duty-cycle. For example, the control unit can adjust the duty-cycle on the fly, such as by, increasing the duty cycle to a new value. If the control unit adjusts the duty-cycle on the fly, the control unit can use the data identified above to retrain the train machine-learning model, e.g., the (i) incorrect duty cycle, (ii) the newly adjusted duty cycle, and (iii) temperature data of the property. [0127] Additionally, by instructing the HVAC system to turn off and on based on the generated duty-cycle, the control unit can reduce a maximum power consumption used for a particular monitored property across smaller time periods over an overall larger time period, e.g., on-peak period. In other words, the control unit still enables the same amount of power consumption across the entire on-peak period, but the amount of power consumption is spaced out across smaller or shorter periods of the entire on-peak period in order to reduce the maximum amount of power consumption or reduce a rate of power consumption.).
Regarding claim 10, wherein the operations further comprise: accessing historical usage data of the device (see at least [0044] This can also include for example, Wi-Fi devices, detected, Bluetooth devices detected, calendars of residents, historical data corresponding to each of the aforementioned data, and electrical rate information. The electrical rate information can include base rates, TOU periods and charges, peak charges, real time price variability inputs, and data associated with utility bill extracted via user input and/or image recognition.);
determining an expected cost savings by implementing the schedule (see at least Fig. 3. Show less energy usage correlates to monetary savings based on the optimized usage and recovery); and
causing display of the expected cost savings in a user interface (see at least [0102] the peak protect module can run in an energy saver or money saver mode during a demand response event. This may be used to discourage changes during those periods. The results can be displayed on an alarm panel or the thermostat.).
Regarding claim 11, wherein the operations further comprise: dynamically aggregating real-time data from multiple sources including energy prices, grid demands, and environmental conditions to generate the power cost data (see at least [0028-0029]).
Regarding claim 12, wherein the dynamically aggregating of the real-time data includes updating the real-time data at intervals determined by the volatility and temporal relevance of each of the multiple sources (see at least [0023] electricity usage continues to rise in a hot afternoon in the southwestern part of the United States as people arrive home from work at the end of the day. Consequently, utility companies have created rate plans called time of use (hereinafter, TOU), time of day, and TOU plus demand rate plans, that incentivize their customers to use less energy during the peak times of the day. Under these schemes, customers may pay different prices for a kilowatt-hour (kWh) at certain times of the day—higher prices during periods that have lower generation and higher demand,).
Regarding claim 13, further comprising optimizing energy usage across a network of interconnected devices to enhance overall energy efficiency and achieve cost-effectiveness at a system-wide level (see at least [0054] Through the combination of the relevant monitored property energy model and comfort/need model for various devices, the control unit 104 can optimize energy usage to maximize the homeowner comfort.).
Claim 14 is substantially similar to claim 1 and therefore rejected under the same rationale.
Claim 15 is substantially similar to claim 2 and therefore rejected under the same rationale.
Claim 18 is substantially similar to claim 5 and therefore rejected under the same rationale.
Claim 20 is substantially similar to claims 1 or 14 and therefore rejected under the same rationale.
Regarding claim 21, wherein the generating of the schedule is further based on an initial state of the device as reported by a sensor (see at least [0067] The smart scheduler of the control unit 104 can use the following inputs to meet the above goals for the customer. For example, the smart scheduler can take as input, security system arming state, motion sensor data, door and window contact data, granular and non-granular humidity data, detected Wi-Fi devices at the monitored property 102, detected Bluetooth devices at the monitored property 102, and state of the shade and shutters. [0037] The one or more sensors 114 may include a motion sensor located at the exterior of the monitored property 102, a front door sensor that is a contact sensor positioned at the front door 118, a pressure sensor that receives button presses at a light device, an air flow sensor included in the air duct 130 or the air-handling unit 142, and a lock sensor that is positioned at the front door 118 and each window.) [0043] the control unit 104 can create various models for other monitoring and predicting of device usage in the monitored property 102. For example, the control unit 104 may generate an HVAC specific model that is trained and implemented based on outdoor temperature, thermostat temperature, remote temperature sensor readings, humidity (indoor and outdoor readings), detected wiring data and installer input to determine the HVAC type. The HVAC type can indicate, for example, a heat pump, boiler-based radiant heating systems, a furnace, and how many heating stages, to name a few examples. Additionally, the HVAC specific model can also be trained and implemented based on thermostat run times and resulting temperature changes.).
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.
Claim(s) 3-4, 6-7, and 16-17is/are rejected under 35 U.S.C. 103 as being unpatentable over Reeder U.S. Publication 2022/0253078 A1 (hereafter Reeder) in view of Singh et al. U.S. Patent 11,411.402 B1 (hereafter Singh).
Regarding claim 3, Reeder discloses that of claim 1 but fails to disclose carbon production data.
Singh discloses, in the same field of invention, methods of energy and power management and the use of incentive/disincentive measures (incentive energy pricing/rewards) where power devices are controlled and coordinated through a schedule and power management controllers to balance demand load where a user can opt for carbon minimization (see at least Col. 8, lines 28-44) or display of inventive pricing or rewards include consideration of carbon credits (see at least Col. 9, lines 32-52), therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to use the energy management and optimization disclosed by Reeder with the consideration of carbon production and credits as taught by Singh for incentivizing and gaming energy and power management for optimizing demand and availability as applying known techniques to know devices for improvement would yield predictable results (KSR D).
Regarding claim 4, the combination discloses wherein the preference data further identifies a carbon cost value (see at least Col. 9, lines 41-47; “How many carbon credits will I minimize by charging from x1 to x2 time?”; and the like. In another example, power end-user 104 may input onto a screen auxiliary data 128 (e.g., preferred source of energy, personal environmental benchmarks, geostrategic/buy-local considerations, etc.), thereby generating a display of revised computations of incentive energy pricing/rewards. Attaches cost savings to each credit).
Regarding claim 6, the combination discloses wherein the incentive data comprises carbon credit incentive data (see at least Col. 9, line 32 and Col. 8, lines 34-37).
Regarding claim 7, the combination discloses wherein the incentive data comprises utility demand response incentive data (see at least Col. 1, lines 53-56).
Claim 16 is substantially similar to claim 3 and therefore rejected under the same rationale.
Claim 17 is substantially similar to claim 4 and therefore rejected under the same rationale.
Response to Arguments
The Applicants arguments begin on page 6 of the response filed on December 11, 2025. The remarks start with a summary of the claims and amendments including support paragraphs in the disclosure. Applicant cites new claim 21 and summarizes the interview.
Applicants arguments begin with the rejection under 35 U.S.C § 102 where the Applicant believes the reference fails to anticipate the claims based on the limitation “generating based on the preference data and the power cost signal…. A weighted amount of time that a value of the condition of the device differs from the target value by more than an acceptable variation”.
Similarly, the Applicant argues the amended claim 9, and states that the reference does not indicate a maximum price to avoid.
The Examiner does not agree. First with respect to the independent claims, the reference of Reeder discloses a smart energy scheduling system. The system is not simply for HVAC equipment and hot water heaters but for all household items which are using electricity. The system is designed to optimize power usage with considerations for inside temperature, relative outside temperature, appliance energy usage, lighting, and also things like automatic window shades which can assist in reducing inside temperature. The system has a schedule to run many aspects of the household to optimize for several things such as overall power usage, usage during peak times where there is high demand and potentially higher rates, incentives for power use as well as considerations for when the residents are scheduled to get home. It takes into consideration programmed schedules with the thermostat and also potential solar generation from any power generation such as solar, and also availability of systems such as in home battery. The System definitely considers the time of day, the cost of power during high demand times (e.g. 8-10 am and 5-7 pm) in order to minimize high cost usage while also catering to resident comfort. The system considers how much lead time the system needs for cooling considering the inside temperature, cooling rate, outside temperature, and electricity cost. It has the ability to decide to precool the house during a lower cost window to bring the temperature down part of the way to offset any costs by running the system for extended times or during a higher cost time window. This would account for considering conditions that are different from a target value and the amount of time the value differs from the set or target temperature. See cited paragraphs for claim 1.
Regarding claim 9, the Examiner is not convinced. While the Applicant references paragraph 85 for setting conditions in which the customer is willing to pay a higher price to a degree based on power prices, the system of Reeder seeks to optimize both comfort and price control where the system is avoiding high process through optimization of usage including the operating duty cycles of some appliances such as HVAC systems.
Regarding the rejection under 35 U.S.C § 103 the Applicants point back to the arguments against Reeder. The Examiner refers the Applicant back to the above arguments. The combination discloses that of 3, 4, 6, 7, 16, and 17.
The Applicant concludes with the rejection under 35 U.S.C § 101 and argues that Example 46 is analogous to the instant claims as the example has “automatic sending of control signal to the feed dispense to dispense a therapeutically effective amount of supplemental salt and minerals mixed with the feed when the analysis result for the animal indicates it’s exhibiting aberrant behavior patterns” since it’s a meaning limitation on the exception. The Applicants argue that similar to scheduling operation with “sending commands” is not merely presented, but actually used to operate the device.
The Examiner does not agree. The schedule is generated and is applied to the HVAC or water heater. The use of a server (or computer) to follow the schedule and send commands to turn on/ turn off is not more than use of a computer as a tool to perform the judicial exception. The claim language is not demonstrating next level control as asserted in Diamond v. Diehr, rather it’s creating a schedule which indicates when the device should be on and off based on power cost and incentive data which is looking at the cost variation of power during low and peak hours while considering any usage incentives available. In this situation, the Examiner does not find integration into practical application but mere use of the computer as a tool to perform the judicial exception.
In summary, the claims remain rejected under 35 U.S.C § 101, 102 and 103. The arguments are not persuasive and the claims are not in condition for allowance.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DYLAN C WHITE whose telephone number is (571)272-1406. The examiner can normally be reached M-F 7:30-4:00 EST.
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/DYLAN C WHITE/Primary Examiner, Art Unit 3625 January 9, 2026