CN116266052A - Intelligent home control method, storage medium and equipment based on Internet of things - Google Patents

Intelligent home control method, storage medium and equipment based on Internet of things Download PDF

Info

Publication number
CN116266052A
CN116266052A CN202310128468.8A CN202310128468A CN116266052A CN 116266052 A CN116266052 A CN 116266052A CN 202310128468 A CN202310128468 A CN 202310128468A CN 116266052 A CN116266052 A CN 116266052A
Authority
CN
China
Prior art keywords
temperature
scene mode
indoor
automatically
user
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202310128468.8A
Other languages
Chinese (zh)
Inventor
王养浩
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Dafa Technology Shanghai Co ltd
Original Assignee
Dafa Technology Shanghai Co ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Dafa Technology Shanghai Co ltd filed Critical Dafa Technology Shanghai Co ltd
Priority to CN202310128468.8A priority Critical patent/CN116266052A/en
Publication of CN116266052A publication Critical patent/CN116266052A/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00—Systems controlled by a computer
    • G05B15/02—Systems controlled by a computer electric
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00—Programme-control systems
    • G05B19/02—Programme-control systems electric
    • G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00—Program-control systems
    • G05B2219/20—Pc systems
    • G05B2219/26—Pc applications
    • G05B2219/2642—Domotique, domestic, home control, automation, smart house
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]

Abstract

The utility model provides an intelligent home control method, a storage medium and equipment based on the Internet of things, comprising the following steps: acquiring home address positioning of a user; automatically acquiring local historical daily high Wen Junzhi and historical daily low-temperature average values according to home address positioning of a user and drawing an annual historical temperature curve; setting four scene modes; automatically determining an annual actual scene mode of the user according to the annual historical temperature curve and the set four scene modes; and automatically controlling the centralized controller and the temperature controller according to the annual actual scene mode to intelligently adjust the indoor temperature. The method can automatically determine the annual actual scene modes of different users, and the electric air heat pump and the air conditioner are matched according to the annual actual scene modes to realize intelligent control of indoor environment temperature, so that the effects of saving energy and reducing energy consumption cost are achieved.

Description

Intelligent home control method, storage medium and equipment based on Internet of things
Technical Field
The invention relates to the technical field of intelligent home, in particular to an intelligent home control method, storage medium and equipment based on the Internet of things.
Background
With the world energy crisis, especially in europe, the heating modes of original natural gas and boilers are subject to cost constraints and challenges, and new heating modes and energy saving schemes are urgently needed. At present, an air conditioner, a temperature controller, a heating system and a centralized controller used in home are controlled independently or manually, so that the cost of household energy sources is high.
Therefore, it is necessary to research a smart home control method, a storage medium and a device based on the internet of things to solve one or more of the above technical problems.
Disclosure of Invention
In order to solve at least one technical problem, according to an aspect of the present invention, there is provided an intelligent home control method based on the internet of things, which is characterized by comprising the following steps:
acquiring home address positioning of a user;
automatically acquiring local historical daily high Wen Junzhi and historical daily low-temperature average values according to home address positioning of a user and drawing an annual historical temperature curve;
setting four scene modes, wherein a first temperature range of a spring scene mode, a second temperature range of a summer scene mode, a third temperature range of an autumn scene mode and a fourth temperature range of a winter scene mode are set;
automatically determining an annual actual scene mode of the user according to the annual historical temperature curve and the set four scene modes;
automatically controlling a centralized controller and a temperature controller according to an annual actual scene mode to intelligently adjust indoor temperature, wherein the centralized controller is used for controlling an electric air heat pump and a ground heating pipeline valve, and the temperature controller is arranged in each room and used for controlling an air conditioner in the corresponding room;
under the spring scene mode and the autumn scene mode, the refrigerating and heating functions of the electric air heat pump and the air conditioner are automatically closed, and the fresh air function of the air conditioner is kept available;
in a summer scene mode, automatically closing the heating functions of the electric air heat pump and the air conditioner, and starting the air conditioner to refrigerate when the indoor temperature is greater than or equal to a first threshold value;
in the winter scene mode, the refrigerating function of the air conditioner is automatically turned off, when the indoor temperature is smaller than or equal to a second threshold value, the electric air heat pump and the air conditioner are started to heat, and when the indoor temperature is increased from the second threshold value to a third threshold value, the air conditioner is turned off to heat.
According to still another aspect of the invention, the current date and time, the indoor and outdoor temperature values and the current day temperature time change curve are automatically obtained, the scene mode in which the current scene is located and the indoor and outdoor temperature difference are automatically determined, and the change trend of the indoor and outdoor temperature difference is predicted, so that the intelligent indoor temperature control system is used for controlling the centralized controller, the temperature controller and the intelligent indoor temperature regulation.
According to still another aspect of the present invention, local sunrise and sunset time, user's work holiday time, local building type and corresponding heat preservation coefficient, room area and room use parameters are automatically obtained for controlling the centralized controller and temperature controller and intelligently adjusting indoor temperature.
According to yet another aspect of the invention, the home address location is entered and confirmed by the user via a client on the mobile terminal.
According to still another aspect of the present invention, the annual actual scene mode of the user is formed by combining any one or any two or more of the group consisting of a spring scene mode, a summer scene mode, an autumn scene mode, and a winter scene mode.
According to still another aspect of the present invention, a user can set a target indoor temperature in different scene modes through a mobile terminal.
According to still another aspect of the present invention, the electric air heat pump and/or the air conditioner is controlled according to a time when a user will arrive home, a current indoor and outdoor temperature difference, and a predicted trend of variation of the indoor and outdoor temperature difference.
According to yet another aspect of the present invention, the first threshold, the second threshold, and the third threshold are automatically adjusted after AI learning.
According to a further aspect of the present invention, there is also provided a computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program adapted to be loaded and executed by a processor to cause a computer device having the processor to perform the aforementioned method.
According to still another aspect of the present invention, there is also provided a computer apparatus characterized by comprising: a processor and a memory;
the processor is connected with a memory, wherein the memory is used for storing a computer program, and the processor is used for calling the computer program to enable the computer device to execute the method.
The invention can obtain one or more of the following technical effects:
1. the annual actual scene mode of users in different areas can be automatically determined, and the electric air heat pump and the air conditioner are matched according to the annual actual scene mode to realize intelligent control of indoor environment temperature, so that the effects of saving energy and reducing energy consumption cost are achieved, and compared with the existing mode, the energy consumption can be reduced by 25%.
2. The electric air heat pump is adopted to replace a natural gas boiler and assist the use of an air conditioner, so that the heating energy and the overall energy cost are greatly reduced.
3. The current scene mode and the indoor and outdoor temperature difference can be automatically determined, and the change trend of the indoor and outdoor temperature difference is predicted, so that the indoor temperature of a user can be intelligently realized while energy conservation is realized.
4. The intelligent control system can automatically acquire the local building type and the corresponding heat preservation coefficient, and assist in controlling the electric air heat pump and the air conditioner, so as to realize intelligent control.
Drawings
The invention will be described in further detail with reference to the drawings and the detailed description.
Fig. 1 is a flowchart of an intelligent home control method based on the internet of things according to a preferred embodiment of the present invention.
Fig. 2 is a schematic structural diagram of an intelligent home control system based on the internet of things according to a preferred embodiment of the present invention.
Fig. 3 is a graphical representation of historical daily high Wen Junzhi and historical daily low temperature mean values of years 2014-2022 located near the carthamus tinctorius airport of the netherlands in europe, according to a preferred embodiment of the present invention.
Fig. 4 is a cost comparison of a natural gas boiler using an electric air heat pump in accordance with a preferred embodiment of the present invention.
Detailed Description
The present invention is described in its best mode by the following preferred embodiments with reference to the accompanying drawings, and the detailed description herein is to be construed as limiting the invention, since various changes and modifications can be made without departing from the spirit and scope of the invention.
Example 1
According to a preferred embodiment of the present invention, referring to fig. 1, there is provided an intelligent home control method based on the internet of things, which is characterized by comprising the following steps:
acquiring home address positioning of a user;
automatically acquiring local historical daily high Wen Junzhi and historical daily low-temperature average values according to home address positioning of a user and drawing an annual historical temperature curve;
setting four scene modes, wherein a first temperature range of a spring scene mode, a second temperature range of a summer scene mode, a third temperature range of an autumn scene mode and a fourth temperature range of a winter scene mode are set;
automatically determining an annual actual scene mode of the user according to the annual historical temperature curve and the set four scene modes;
automatically controlling a centralized controller and a temperature controller according to an annual actual scene mode to intelligently adjust indoor temperature, wherein the centralized controller is used for controlling an electric air heat pump and a ground heating pipeline valve, and the temperature controller is arranged in each room and used for controlling an air conditioner in the corresponding room;
under the spring scene mode and the autumn scene mode, the refrigerating and heating functions of the electric air heat pump and the air conditioner are automatically closed, and the fresh air function of the air conditioner is kept available;
in a summer scene mode, automatically closing the heating functions of the electric air heat pump and the air conditioner, and starting the air conditioner to refrigerate when the indoor temperature is greater than or equal to a first threshold value;
in the winter scene mode, the refrigerating function of the air conditioner is automatically turned off, when the indoor temperature is smaller than or equal to a second threshold value, the electric air heat pump and the air conditioner are started to heat, and when the indoor temperature is increased from the second threshold value to a third threshold value, the air conditioner is turned off to heat.
Referring to fig. 3, there is shown a historical daily high Wen Junzhi and historical daily low temperature mean, and an annual historical temperature profile for years 2014-2022 located near the carthamus seafloor of the netherlands of europe. For example, the first temperature range may be preset to be specifically Wen Junzhi to 28 degrees per day, the second temperature range may be Wen Junzhi to more than 28 degrees per day, the third temperature range may be specifically Wen Junzhi to 28 degrees per day, and the fourth temperature range may be specifically Wen Junzhi to less than 10 degrees per day. From this annual history temperature profile, a time zone having a daily height Wen Junzhi of less than 10 degrees (11 months 15 days per year to 2 months 15 days per year) can be determined as a winter mode, similarly, 2 months 16 days to 8 months 15 days per year (the daily height Wen Junzhi of 8 months 15 days reaches a maximum value of 22 degrees) can be determined as a spring mode, and 8 months 15 days to 11 months 14 days per year can be determined as a fall mode (no summer mode because the daily heights Wen Junzhi in this region are all higher than 28 degrees). That is, the annual actual scene mode of the user is composed of a winter mode, a spring mode, and an autumn mode. Similarly, if located in a region near the equator, there may be no winter mode, and if located in a region of high cold, there may be no summer mode.
Preferably, for the spring mode and the fall mode, it can be further determined by an ascending trend of temperature (spring mode) or a descending trend of temperature (fall mode).
Advantageously, by means of the user's annual actual scene mode, the current actual scene mode may be automatically determined according to the current date and time, for example, when the temperature sensor senses that the indoor temperature is 20 degrees celsius, if the summer mode and the winter mode are not distinguished, whether to select cooling or heating cannot be determined. Or if the mode is not discriminated from the spring mode and the winter mode, whether the fresh air mode or the heating mode is selected cannot be determined. Obviously, through the differentiation of four different season modes, the intelligent control of the electric air heat pump and the air conditioner can be realized.
Referring to fig. 4, an example is given in which a user's house is equipped with a gas central heating boiler having an efficiency of 95% (maximum heating value). A total of 1600 cubic meters of gas (average value of a house in the netherlands) is consumed annually by the user, 40 cubic meters of gas being needed annually to cook a meal. Therefore, the heating and hot water gas consumption of the user is: 1600 cubic meters/-40 cubic meters = 1560 cubic meters of gas, the cost is 1.60 euros per cubic meter, the heating and hot water gas cost of the user is: 1560x1, 60 euro=2496 euro/year. The energy cost of the electric air heat pump is 1390.48 Euro, so that the energy cost can be greatly reduced.
According to another preferred embodiment of the invention, the current date and time, the indoor and outdoor temperature values and the current time-of-day temperature change curve are automatically acquired, the current scene mode and the indoor and outdoor temperature difference are automatically determined, and the change trend of the indoor and outdoor temperature difference is predicted, so that the centralized controller, the temperature controller and the intelligent indoor temperature regulation are used for controlling.
For example, the time-of-day temperature change curve may be obtained from a historical data average, or may be obtained from the weather forecast data. For example, in winter mode, if the indoor-outdoor temperature difference is expected to be larger and larger, the electric air heat pump is controlled to increase the power, even the air heat pump is controlled to increase the air heat, so as to ensure that the indoor temperature reaches the target temperature, otherwise, the power can be reduced appropriately.
According to a further preferred embodiment of the invention, local sunrise and sunset time, working holiday time of the user, local building type and corresponding heat preservation coefficient, room area and room use parameters are automatically acquired for controlling the centralized controller and the temperature controller and intelligently adjusting indoor temperature.
For example, local sunrise and sunset times may be used to divide the daytime and evening, for example, in summer mode, the indoor target temperature for daytime may be set to 26 degrees and the indoor target temperature for evening may be set to 28 degrees. The user's work holiday time may be used to determine a period of time when the user is not at home, where energy saving modes (e.g., turning off air conditioning and electric heat pump) may be employed. In addition, whether a person is at home or in a room may also be sensed by an infrared sensor.
The local building type and the corresponding heat preservation coefficient are mainly reflected in that, for example, a building wall body in the south is thinner, the heat preservation coefficient is lower, a building wall body in the north is provided with a heat preservation structure, the heat preservation coefficient is higher, and the power of related equipment can be regulated in an auxiliary mode by acquiring the heat preservation coefficient of a building so as to accurately and intelligently determine a preset time period to achieve indoor target temperature in the preset time period. For example, the user's off-duty time is 17:00 a day, 18 points to home a day, and when no one is in the daytime in winter mode, the air-conditioning and electric heat pump is turned off (or the electric heat pump is operated intermittently with minimum power), and the air-conditioning and electric heat pump is started half an hour (a predetermined period of time) before the user arrives at home, so that the user arrives at the target indoor temperature at home. The preset time period needs to be comprehensively determined by combining the heat preservation coefficient of a building, the maximum power of an electric heat pump, the maximum power of air conditioner heating, the current indoor temperature, the target indoor temperature, the indoor and outdoor temperature difference, the outdoor temperature change trend and the room area.
The room use parameters mainly comprise adult bedrooms, study rooms, living rooms, children rooms and the like, and the rooms with different uses have different requirements on temperature and are used for controlling corresponding air conditioners and electric air heat pumps.
Preferably, the heat preservation coefficient is automatically adjusted according to the time required for reaching the indoor target temperature under the first predetermined condition. For example, under the same condition parameters, the smaller the time required to reach the indoor target temperature, the higher the heat preservation coefficient. The same condition parameters include, for example, the time period in which the electric heat pump is located, the current outdoor temperature, the current indoor temperature, the target indoor temperature, the power of the electric heat pump, and the like.
According to a further preferred embodiment of the invention, the processing unit is further adapted to obtain house data, environment data and user data for controlling the power required for heat pump heating, the rate of heating up of the room, the target temperature of the heat pump heating, and the target temperature of the respective room. House data includes geographic location, overall area, room type and area, house height, and house warmth retention rating. The heat preservation grade of the house is determined by the thickness of the wall body, the thickness of the roof and the area of the window. The environmental data includes outdoor temperature, indoor temperature, and historical data. User data includes family population, time and period of residence, activity paradigm, preference temperature, etc.
According to a further preferred embodiment of the invention, the home address location is entered and confirmed by the user via a client on the mobile terminal.
According to still another preferred embodiment of the present invention, the annual actual scene mode of the user is composed of any one or a combination of two or more of the group consisting of a spring scene mode, a summer scene mode, an autumn scene mode, and a winter scene mode.
According to still another preferred embodiment of the present invention, a user can set a target indoor temperature in different scene modes through the mobile terminal.
According to a further preferred embodiment of the present invention, the electric air heat pump and/or the air conditioner is controlled according to the time the user will be home, the current indoor and outdoor temperature difference, and the predicted trend of the indoor and outdoor temperature difference.
According to a further preferred embodiment of the invention, the first threshold value, the second threshold value and the third threshold value are automatically adjusted after AI learning.
According to a further preferred embodiment of the present invention there is also provided a computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program adapted to be loaded and executed by a processor to cause a computer device having the processor to perform the aforementioned method.
There is further provided in accordance with still another preferred embodiment of the present invention a computer apparatus including: a processor and a memory;
the processor is connected with a memory, wherein the memory is used for storing a computer program, and the processor is used for calling the computer program to enable the computer device to execute the method.
According to still another preferred embodiment of the present invention, referring to fig. 2, the present invention further provides an intelligent home control system based on the internet of things, which is characterized by comprising: a central controller 2 for controlling an electric air heat pump 1 and a floor heating pipeline valve, wherein the electric air heat pump 1 is connected with the floor heating pipelines 4 in each room, and the floor heating pipeline valve is arranged at a preset position in the floor heating pipeline 4;
a temperature controller 5 provided in each room and controlling an air conditioner 6 in the corresponding room;
the intelligent gateway 7 is used for being in communication connection with the centralized controller 2 and the temperature controller 5 and comprises a processing unit and a storage unit;
a WIFI router 8 communicatively connected between the intelligent gateway 7 and the IOT cloud platform 9, and
the mobile terminal 10 is in communication connection with the IOT cloud platform 9.
Preferably, the floor heating pipe valve is provided on the distribution manifold 3.
According to a further preferred embodiment of the present invention, the intelligent gateway is further used for controlling a door magnetic sensor, a window magnetic sensor, an intelligent curtain, an intelligent lamp, an intelligent camera and an intelligent door lock.
The invention can obtain one or more of the following technical effects:
1. the annual actual scene mode of users in different areas can be automatically determined, and the electric air heat pump and the air conditioner are matched according to the annual actual scene mode to realize intelligent control of indoor environment temperature, so that the effects of saving energy and reducing energy consumption cost are achieved, and compared with the existing mode, the energy consumption can be reduced by 25%.
2. The electric air heat pump is adopted to replace a natural gas boiler and assist the use of an air conditioner, so that the heating energy and the overall energy cost are greatly reduced.
3. The current scene mode and the indoor and outdoor temperature difference can be automatically determined, and the change trend of the indoor and outdoor temperature difference is predicted, so that the indoor temperature of a user can be intelligently realized while energy conservation is realized.
4. The intelligent control system can automatically acquire the local building type and the corresponding heat preservation coefficient, and assist in controlling the electric air heat pump and the air conditioner, so as to realize intelligent control.
It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (10)

1. An intelligent home control method based on the Internet of things is characterized by comprising the following steps:
acquiring home address positioning of a user;
automatically acquiring local historical daily high Wen Junzhi and historical daily low-temperature average values according to home address positioning of a user and drawing an annual historical temperature curve;
setting four scene modes, wherein a first temperature range of a spring scene mode, a second temperature range of a summer scene mode, a third temperature range of an autumn scene mode and a fourth temperature range of a winter scene mode are set;
automatically determining an annual actual scene mode of the user according to the annual historical temperature curve and the set four scene modes;
automatically controlling a centralized controller and a temperature controller according to an annual actual scene mode to intelligently adjust indoor temperature, wherein the centralized controller is used for controlling an electric air heat pump and a ground heating pipeline valve, and the temperature controller is arranged in each room and used for controlling an air conditioner in the corresponding room;
under the spring scene mode and the autumn scene mode, the refrigerating and heating functions of the electric air heat pump and the air conditioner are automatically closed, and the fresh air function of the air conditioner is kept available;
in a summer scene mode, automatically closing the heating functions of the electric air heat pump and the air conditioner, and starting the air conditioner to refrigerate when the indoor temperature is greater than or equal to a first threshold value;
in the winter scene mode, the refrigerating function of the air conditioner is automatically turned off, when the indoor temperature is smaller than or equal to a second threshold value, the electric air heat pump and the air conditioner are started to heat, and when the indoor temperature is increased from the second threshold value to a third threshold value, the air conditioner is turned off to heat.
2. The intelligent home control method based on the internet of things according to claim 1, wherein a current date and time, an indoor and outdoor temperature value and a current day temperature time change curve are automatically acquired, a current scene mode and an indoor and outdoor temperature difference are automatically determined, and a change trend of the indoor and outdoor temperature difference is predicted, so that the intelligent home control method is used for controlling the centralized controller, the temperature controller and the intelligent indoor temperature adjustment.
3. The intelligent home control method based on the internet of things according to claim 2, wherein local sunrise and sunset time, working holiday time of a user, local building type and corresponding heat preservation coefficient, room area and room use parameters are automatically obtained for controlling the centralized controller and the temperature controller and intelligently adjusting indoor temperature.
4. A smart home control method based on internet of things according to any of claims 1-3, characterized in that the home address location is entered and confirmed by a user via a client on a mobile terminal.
5. The intelligent home control method based on the internet of things according to claim 4, wherein the annual actual scene mode of the user is formed by combining any one or more than two of a group consisting of a spring scene mode, a summer scene mode, a autumn scene mode and a winter scene mode.
6. The intelligent home control method based on the internet of things according to claim 5, wherein a user can set target indoor temperatures in different scene modes through the mobile terminal.
7. The intelligent home control method based on the internet of things according to claim 3, wherein the electric air heat pump and/or the air conditioner is controlled according to the time the user is going to home, the current indoor and outdoor temperature difference and the predicted trend of the indoor and outdoor temperature difference.
8. The intelligent home control method based on the internet of things according to claim 4, wherein the first threshold, the second threshold and the third threshold are automatically adjusted after AI learning.
9. A computer readable storage medium, characterized in that the computer readable storage medium has stored therein a computer program adapted to be loaded and executed by a processor to cause a computer device having the processor to perform the method of any of claims 1-8.
10. A computer device, comprising: a processor and a memory;
the processor is connected to a memory, wherein the memory is configured to store a computer program, and the processor is configured to invoke the computer program to cause the computer device to perform the method of any of claims 1-8.
CN202310128468.8A 2023-02-17 2023-02-17 Intelligent home control method, storage medium and equipment based on Internet of things Pending CN116266052A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310128468.8A CN116266052A (en) 2023-02-17 2023-02-17 Intelligent home control method, storage medium and equipment based on Internet of things

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310128468.8A CN116266052A (en) 2023-02-17 2023-02-17 Intelligent home control method, storage medium and equipment based on Internet of things

Publications (1)

Publication Number Publication Date
CN116266052A true CN116266052A (en) 2023-06-20

Family

ID=86744478

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310128468.8A Pending CN116266052A (en) 2023-02-17 2023-02-17 Intelligent home control method, storage medium and equipment based on Internet of things

Country Status (1)

Country Link
CN (1) CN116266052A (en)

Similar Documents

Publication Publication Date Title
Clauß et al. Predictive rule-based control to activate the energy flexibility of Norwegian residential buildings: Case of an air-source heat pump and direct electric heating
Badescu et al. Warm season cooling requirements for passive buildings in Southeastern Europe (Romania)
WO2018032241A1 (en) Controller for hvac unit
US10083408B2 (en) Energy conservation unit and system of a building by way of interactive learning
US20160085248A1 (en) Conditioning an indoor environment
CN109690200A (en) Digital intelligent energy conserving system, methods and procedures
AU2011305053A1 (en) Improved heat pump
Thornton et al. Technical support document: 50% energy savings design technology packages for medium office buildings
Elhelw Analysis of energy management for heating, ventilating and air-conditioning systems
CN116266053A (en) Intelligent home management system based on Internet of things
WO2023273379A1 (en) Method and apparatus for controlling curtains, and server
Yasue et al. Modeling the occupant behavior relating to window and air conditioner operation based on survey results
CN110488897A (en) A kind of misclosure space environment regulator control system and its regulation method
CN116266052A (en) Intelligent home control method, storage medium and equipment based on Internet of things
Zhuang et al. Cascade control for supply air temperature in a variable air volume system
CN114353280B (en) Air conditioner and control method thereof
CN108253604A (en) The control method and air conditioner of air conditioner
Mikola et al. Problems with using the exhaust air heat pump for renovation of ventilation systems in old apartment buildings
Jiang et al. Study on Fuzzy Control for Air-To-Water Heat Pumps Connected to a Residential Floor Heating System
Strand Recent energy simulation model enhancements for radiant systems
Deshko et al. Modeling of unsteady temperature regimes of autonomous heating systems
Zhang et al. Energy and Energy Cost Savings Analysis of the 2015 IECC for Commercial Buildings
Lamichhane An eQUEST based building energy modeling analysis for energy efficiency of buildings
Jiang et al. Study fuzzy variable supplied water temperature control for air-to-water heat pumps connected to a residential floor heating system
Medyakov et al. Evaluation of the effectiveness of the building heating control system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination