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 the Application
2. Claim 16-35 have been examined in this application. This communication is the first action on the merits.
Drawings
3. The drawings filed on 11/24/23 are acceptable for examination proceedings.
Specification
4. The abstract of the disclosure is objected to because it contains more than 150 words. A corrected abstract of the disclosure is required and must be presented on a separate sheet, apart from any other text. See MPEP § 608.01(b).
Claim Objections
Claim 18 and 34 are objected as “□topen” need to replace by “Δtopen” (at Ln. 5).
Claim 19 is objected as “□tclose” need to replace by “Δtclsoe” (at Ln. 5).
Claim Rejections - 35 USC § 101
5. 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.
6. Claim 35 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claim 35 includes “A computer-readable storage medium …”, however, the specification does not clearly define what the computer-readable storage medium is or how it is differentiated from the storage mediums which are disclosed in the specification, therefore, the broadest reasonable interpretation of the claim is that the memory could include transitory signals, which are non-statutory subject matter.
The Examiner further notes that Paragraphs [0117] of PG Pub: 2024/0288191 discusses a different type or example of storage medium, however, this paragraph also fails to define the storage medium as a statutory medium as it provides only examples.
The Examiner suggests amending the claim to read “A non-transitory computer readable storage medium….” to overcome this rejection.
Allowable Subject Matter
Claim 18-24, 26-29 and 34 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim Rejections - 35 USC § 103
7. 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.
8. Claim 16-17, 25, 30-33, and 35 are rejected under 35 U.S.C. 103 as being unpatentable over Taguchi (Pub: 2021/0254851) in view of Kring (Pub: 2019/0107307).
9. Regarding claim 16, Taguchi teaches a method for controlling an air conditioner and implemented by a controller (e.g., The air conditioning controller 3 is a controller that performs centralized control on the plurality of outdoor units 5 and the plurality of indoor units 6) (Para. [0032], Fig. 1),
comprising: obtaining temperature data and humidity data of the air conditioner, the temperature data including an indoor temperature and an outdoor temperature (e.g., Each indoor unit 6 outputs the acquired environmental information, the received setting information, and operation information indicating an operating state of the corresponding air conditioner 4, as air conditioning data, to the air conditioning controller 3 via the corresponding outdoor unit 5. Note that examples of the environmental information include hourly indoor temperature and indoor humidity) (Para. [0031]), and the humidity data including an indoor humidity and an outdoor humidity (e.g., Each outdoor unit 5 includes a sensor that acquires environmental information on the outdoors where the corresponding outdoor unit 5 is installed. Each outdoor unit 5 outputs the acquired environmental information, as air conditioning data, to the air conditioning controller 3. Note that examples of the environmental information include hourly outdoor temperature and outdoor humidity) (Para. [0030]) (Cited Para. 31 is for indoor temperature and humidity, and Para. 30 is for outdoor temperature and humidity);
inputting a mode of the air conditioner (e.g., and operation modes of the air conditioner 4 including a cooling mode, a heating mode, and a dehumidification mode) (Para. [0031]), a prediction type of the air conditioner (e.g., Examples of the operation information include information related to starting and stopping of the air conditioner 4) (Para. [0031]), the temperature data, and the humidity data into a pre-trained prediction model of the air conditioner (e.g., by inputting the air conditioning data into a machine learning model) (Para. [0008]), the mode of the air conditioner including at least one of a cooling mode or a heating mode (e.g., Examples of the operation information include information related to starting and stopping of the air conditioner 4, and operation modes of the air conditioner 4 including a cooling mode, a heating mode, and a dehumidification mode) (Para. [0031]), the prediction type of the air conditioner including at least one of a startup-time prediction or a shutdown-time prediction (e.g., Examples of the operation information include information related to starting and stopping of the air conditioner 4) (Para. [0031]),
and parameters of the prediction model including an indoor set temperature, [an indoor set temperature threshold value], an indoor set humidity (e.g., The setting information includes at least a target time at which an environmental value of the room equipped with the indoor unit 6 reaches a target value, and other examples of the setting information include a target temperature and a target humidity set by a user) (Para. [0031]), [and an indoor set humidity threshold value];
and controlling a startup or a shutdown of the air conditioner based on a predicted time output by the prediction model, the predicted time including at least one of a predicted startup time or a predicted shutdown time (e.g., The prediction unit 13 outputs the predicted required time to the air conditioning controller 3 via the transceiver unit 11. The air conditioning controller 3 determines a start time of the air conditioner 4 required for the environmental value of the room to reach the target value, from the required time and the target time as above, and controls the air conditioner 4 to start at the start time) (Para. [0035]).
Taguchi does not specifically teach an indoor set temperature threshold value, an and an indoor set humidity threshold value.
Kring teaches an indoor set temperature threshold value, an and an indoor set humidity threshold value (e.g., Further, different thresholds may be programmed and/or learned for different times of the day, days of the week, or days of the year (e.g., desired cooler temperature thresholds at night, more airflow on weekends when occupants are home, desired lower humidity thresholds for summer, etc.). Moreover, thresholds may be dynamic depending on the location of a vent register 110 or sensor module 112. For example, a vent register 110 or sensor module 112 in a low-traffic room or corridor of a building may have a larger acceptable temperature threshold than a high-traffic room or corridor. In another example, a vent register 110 or sensor module 112 proximal to a door, window, or other opening may have a greater acceptable threshold differential since the opening may introduce temperature fluctuations that can be absorbed by the remainder of the rooms/corridors. Moreover, a sensor module 112 and/or control processor 106 may have multiple thresholds for various environmental conditions. For example, a sensor module 112 may have a temperature threshold of two degrees Fahrenheit differential and a humidity threshold of a 10% humidity differential. It will be appreciated that many configurations are possible) (Para. [0061]).
Because Kring is also directed to manage and operate an HVAC system in response to detected environmental conditions and user input, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, having teachings of Taguchi and Kring before him/her, to modify the teachings of Taguchi to include the teaching of Kring in order to efficiently manage the operations of an HVAC system (Kring: Para. [0005]).
10. Regarding claim 17, the combination of Taguchi and Kring teaches the method according to claim 16, wherein Taguchi further teaches obtaining the temperature data and the humidity data of the air conditioner includes: obtaining a current time; and obtaining the temperature data and the humidity data in response to the current time reaching a preset determination time (e.g., Each indoor unit 6 includes a sensor that acquires environmental information on the inside of a room where the corresponding indoor unit 6 is installed. Each indoor unit 6 further includes a reception unit that receives setting information from a user. Each indoor unit 6 outputs the acquired environmental information, the received setting information, and operation information indicating an operating state of the corresponding air conditioner 4, as air conditioning data, to the air conditioning controller 3 via the corresponding outdoor unit 5. Note that examples of the environmental information include hourly indoor temperature and indoor humidity) (hourly is a specific time to obtain the data) (Para. [0031], also refer to Para. [0053] which includes “monitoring the monitoring the indoor temperature and the outdoor temperature at a regular time interval”).
11. Regarding claim 25, the combination of Taguchi and Kring teaches the method according to claim 16, wherein Taguchi further comprising, after controlling the startup or the shutdown of the air conditioner based on the predicted time: determining a temperature-reaching time of the air conditioner; and adjusting the parameters of the prediction model based on the temperature-reaching time (e.g., Next, the update unit 15 reads the machine learning model stored in advance in the storage unit 12, and updates the machine learning model by referring to the air conditioning data and the start time acquired by the acquisition unit 16 as well as the augmented data generated by the augmentation unit 14 (step ST12). For example, in step ST12, the update unit 15 updates the machine learning model, by referring to the indoor temperature, the outdoor temperature, and the start time acquired by the acquisition unit 16 as well as the augmented data thereof) (Para. [0049]).
12. Regarding claim 30, the combination of Taguchi and Kring teaches the method according to claim 16, wherein Taguchi further teaches adjusting the parameters of the prediction model based on the temperature-reaching time includes: obtaining historical temperature data and historical humidity data of the air conditioner within a preset time range; and adjusting the parameters of the prediction model further based on the historical temperature data and the historical humidity data (e.g., generate augmented data by referring to the acquired air conditioning data and the start time; and update the machine learning model, by referring to the acquired air conditioning data and the start time as well as the generated augmented data, wherein the processing circuitry acquires, as the air conditioning data, an indoor environmental value of a room in which an indoor unit of the air conditioner is installed and an outdoor environmental value of the outdoors where an outdoor unit of the air conditioner is installed, and the processing circuitry refers to the indoor environmental value and the outdoor environmental value for a period from the start time to a time when the indoor environmental value reaches a target value, calculates a difference between the indoor environmental value and the outdoor environmental value and a slope of an indoor environmental value change graph at a certain time within the period, and generates a linear model with the slope associated with the difference, as augmented data of the indoor environmental value change graph) (Refer to claim 2).
13. Regarding claim 31, the combination of Taguchi and Kring teaches method according to claim 16, wherein Taguchi further teaches the controller is arranged in the air conditioner or in a server in communication connection with the air conditioner (e.g., FIG. 18B is a block diagram illustrating a configuration of hardware that executes software for implementing the functions of the air conditioning control device 2 or the air conditioning control device 20. A storage device 101 illustrated in FIGS. 18A and 18B functions as the storage unit 12. Note that the storage device 101 may be a component included in the air conditioning control device 2 or the air conditioning control device 20, or may be included in a device separate from the air conditioning control device. For example, the storage device 101 may be a device on a communication network to which the air conditioning control device 2 or the air conditioning control device 20 can have communication access) (Para. [0142]).
14. Regarding claim 32, Claim 32 recites an electronic device that implement the method of claim 16, with substantially the same limitations, respectively. Therefore the rejection applied to claim 16, also applies to claim 32 respectively.
Wherein Taguchi further teaches an electronic device comprising: a processor; and a memory storing a computer-executable instruction that, when executed by the processor (e.g., The processor 102 reads and executes the programs stored in the memory 103, thereby implementing the function of each of the prediction unit 13, the augmentation unit 14, the update unit 15, and the acquisition unit 16 in the air conditioning control device 2. That is, the air conditioning control device 2 includes the memory 103 for storing the programs that, when executed by the processor 102, result in the execution of the processing from step ST1 to step ST4 illustrated in FIG. 3, the processing from step ST10 to step ST13 illustrated in FIG. 4, the processing from step ST30 to step ST34 illustrated in FIG. 13, the processing from step ST40 to step ST43 illustrated in FIG. 14, the processing from step ST50 to step ST56 illustrated in FIG. 16, or the processing from step ST60 to step ST63 illustrated in FIG. 17) (Para. [0147], Fig. 18A- 18B).
15. Regarding claim 33, as to claim 32, applicant is directed to citation of claim 17 above.
16. Regarding claim 35, Claim 35 recites a computer-readable storage medium storing a computer-executable instruction that implement the method of claim 16, with substantially the same limitations, respectively. Therefore the rejection applied to claim 16, also applies to claim 32 respectively.
Wherein Taguchi further teaches a computer-readable storage medium storing a computer-executable instruction that, when invoked and executed by a processor, causes the processor to (e.g., The processor 102 reads and executes the programs stored in the memory 103, thereby implementing the function of each of the prediction unit 13, the augmentation unit 14, the update unit 15, and the acquisition unit 16 in the air conditioning control device 2. That is, the air conditioning control device 2 includes the memory 103 for storing the programs that, when executed by the processor 102, result in the execution of the processing from step ST1 to step ST4 illustrated in FIG. 3, the processing from step ST10 to step ST13 illustrated in FIG. 4, the processing from step ST30 to step ST34 illustrated in FIG. 13, the processing from step ST40 to step ST43 illustrated in FIG. 14, the processing from step ST50 to step ST56 illustrated in FIG. 16, or the processing from step ST60 to step ST63 illustrated in FIG. 17) (Para. [0147], Fig. 18A- 18B).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Mady (Pub: 2018/0142915) disclose a control system for an HVAC system having at
least one HVAC component, the control system comprising: a controller having a processor and a memory, the controller in signal communication with the at least one HVAC component, the controller configured to: determine a startup/shut-down setpoint and the time associated with a beginning or an end of a building occupancy period; determine a predicted weather condition for outside air at a location of the HVAC system; predict a set of indoor air conditions over the period from the current time until the building being occupied/unoccupied based on the determined setpoint and time and the predicted weather condition; and start/stop the at least one HVAC component when an actual room air condition approaches the predicted indoor air condition (Abstract).
Hokari (Pub: 2022/0154960) disclose an air-conditioning control device, an air
conditioning system, an air-conditioning control method, and a non-transitory computer readable recording medium for estimating a startup time of an air conditioner using a machine learning model (Para. [0002]).
Lee (Pub: 2019/0264940) disclose “The server determines the schedule duration by
detecting a time point when occupancy starts and a time point when the occupancy ends of the compound control zone based on a CO.sub.2 concentration change. In this case, the schedule duration denotes a time duration to which a cooling/heating schedule and a ventilating schedule of the compound control zone are applied.” (Para. [0210]).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JIGNESHKUMAR C PATEL whose telephone number is (571)270-0698. The examiner can normally be reached Monday - Friday, 7:00 AM - 5:00 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kenneth M. Lo can be reached at (571)272-9774. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JIGNESHKUMAR C PATEL/Primary Examiner, Art Unit 2116