CN112161322A - Heating equipment and control method thereof - Google Patents
Heating equipment and control method thereof Download PDFInfo
- Publication number
- CN112161322A CN112161322A CN202011015059.XA CN202011015059A CN112161322A CN 112161322 A CN112161322 A CN 112161322A CN 202011015059 A CN202011015059 A CN 202011015059A CN 112161322 A CN112161322 A CN 112161322A
- Authority
- CN
- China
- Prior art keywords
- current
- heating
- heating equipment
- historical
- data
- 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.)
- Granted
Links
Images
Classifications
-
- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24D—DOMESTIC- OR SPACE-HEATING SYSTEMS, e.g. CENTRAL HEATING SYSTEMS; DOMESTIC HOT-WATER SUPPLY SYSTEMS; ELEMENTS OR COMPONENTS THEREFOR
- F24D19/00—Details
- F24D19/10—Arrangement or mounting of control or safety devices
- F24D19/1006—Arrangement or mounting of control or safety devices for water heating systems
-
- 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
- G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
- G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
- G05B13/04—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators
- G05B13/042—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric involving the use of models or simulators in which a parameter or coefficient is automatically adjusted to optimise the performance
Abstract
The invention provides heating equipment and a control method thereof. The method comprises the following steps: acquiring current energy consumption data of heating equipment, current use habits of users on the heating equipment and current environment data of places where the heating equipment is located, and uploading the data to a cloud server communicated with the heating equipment, wherein the cloud server is provided with a self-adaptive learning model; controlling a self-adaptive learning model to mine and analyze current energy consumption data, current use habits and current environment data to obtain a current use suggestion for heating equipment; and controlling the cloud server to push the current use suggestion to the user terminal. According to the method, the current energy consumption data, the current use habit and the current environment data are taken as the basis, when the current use suggestion of the heating equipment is analyzed, the current use suggestion is sent to the user terminal, a more comfortable and energy-saving setting reference is provided for a user, the user is helped to use the heating equipment more appropriately under the current use environment, and the operation of the heating equipment is made to be adaptive to the current use environment.
Description
Technical Field
The invention relates to the technical field of household appliances, in particular to heating equipment and a control method thereof.
Background
With the improvement of living standard of people, compared with the water boiling by adopting a traditional pot, most families adopt heating equipment such as a wall-hanging stove or a water heater with high automation degree to realize the supply of hot water for heating and hot water for bathroom.
Although the conventional heating equipment such as a wall-mounted boiler or a water heater can display data such as a current water temperature and a target water temperature set by a user, the user generally sets the target temperature directly and simply when using the heating equipment, and it is unclear how the heating equipment should be used more appropriately under the current use environment, so that the target temperature set by the user is difficult to be matched with an optimal comfortable temperature under the current use environment, and the comfort of the user is affected.
Moreover, after the heating apparatus is operated for a certain period of time, even if the water temperature or the room temperature has been adjusted to the optimal comfortable temperature, the user does not know at what time the operation of the heating apparatus should be adjusted to adapt to the changing use environment at any time, resulting in waste of energy.
Disclosure of Invention
The embodiment of the invention provides heating equipment and a control method thereof, and aims to solve the technical problem that when a user uses the existing heating equipment, the user comfort level is influenced or energy waste is caused because how to use the heating equipment more appropriately under different using environments is unclear.
The embodiment of the invention is realized by providing a control method of heating equipment, which comprises the following steps:
acquiring current energy consumption data of the heating equipment, current use habits of users on the heating equipment and current environmental data of a place where the heating equipment is located;
uploading the current energy consumption data, the current usage habits and the current environment data to a cloud server which is communicated with the heating equipment, wherein the cloud server is provided with a self-adaptive learning model;
controlling the self-adaptive learning model to carry out mining analysis on the current energy consumption data, the current use habit and the current environment data to obtain a current use suggestion for the heating equipment;
and controlling the cloud server to push the current use suggestion to a user terminal.
Further, before the obtaining of the current energy consumption data of the heating device, the current usage habit of the user on the heating device, and the current environmental data of the location where the heating device is located, the method further includes:
acquiring historical energy consumption data of the heating equipment in a historical time period, historical use habits of users on the heating equipment and historical environmental data of a place where the heating equipment is located;
uploading the historical energy consumption data, the historical use habits and the historical environment data to the cloud server and storing the historical energy consumption data, the historical use habits and the historical environment data;
mining and learning the historical energy consumption data, the historical use habits and the historical environment data to obtain a self-adaptive learning rule;
and establishing a self-adaptive learning model in the cloud server based on the self-adaptive learning rule.
Further, the step of controlling the adaptive learning model to perform mining analysis on the current energy consumption data, the current usage habit and the current environmental data to obtain a current usage suggestion for the heating equipment includes:
comparing and analyzing the historical energy consumption data, the historical use habits and the historical environment data with the current energy consumption data, the current use habits and the current environment data to obtain a data difference value;
and mining and analyzing the data difference values according to the self-adaptive learning rule to obtain a current use suggestion for the heating equipment.
Furthermore, the heating device is further connected to the user terminal in a communication manner, and after the controlling the cloud server to send the current usage suggestion to the user terminal, the method further includes:
receiving an operation instruction sent by the user terminal according to the current use suggestion;
and controlling the heating equipment to operate in a first operation mode contained in the current use suggestion according to the operation instruction.
Furthermore, after the controlling the heating device to operate in the first operation mode included in the current usage suggestion according to the operation instruction, the method includes:
receiving a control instruction input from the outside;
and controlling the heating equipment to operate in a second operation mode contained in the control command according to the control command.
Furthermore, an embodiment of the present invention further provides a heating apparatus, where the heating apparatus includes:
the first acquisition module is used for acquiring current energy consumption data of the heating equipment, current use habits of users on the heating equipment and current environment data of places where the heating equipment is located;
the first uploading module is used for uploading the current energy consumption data, the current use habit and the current environment data to a cloud server communicated with the heating equipment, and the cloud server is provided with a self-adaptive learning model;
the first analysis module is used for controlling the self-adaptive learning model to mine and analyze the current energy consumption data, the current use habit and the current environment data to obtain a current use suggestion for the heating equipment;
and the first pushing module is used for controlling the cloud server to push the current use suggestion to the user terminal.
Further, the heating apparatus further includes:
the second acquisition module is used for acquiring historical energy consumption data of the heating equipment in a historical time period, historical use habits of users on the heating equipment and historical environmental data of a place where the heating equipment is located;
the second uploading module is used for uploading the historical energy consumption data, the historical using habits and the historical environment data to the cloud server and storing the historical energy consumption data, the historical using habits and the historical environment data;
the first learning module is used for mining and learning the historical energy consumption data, the historical use habits and the historical environment data to obtain a self-adaptive learning rule;
the first establishing module is used for establishing an adaptive learning model in the cloud server on the basis of the adaptive learning rule.
Further, the heating apparatus further includes:
the second analysis module is used for comparing and analyzing the historical energy consumption data, the historical use habits and the historical environment data with the current energy consumption data, the current use habits and the current environment data to obtain a data difference value;
and the third analysis module is used for mining and analyzing the data difference values according to the self-adaptive learning rule to obtain the current use suggestion of the heating equipment.
Further, the heating device is also connected to the user terminal in communication, and the heating device further includes:
a first receiving module, configured to receive an operation instruction sent by the user terminal according to the current usage suggestion;
and the first control module is used for controlling the heating equipment to operate in a first operation mode contained in the current use suggestion according to the operation instruction.
Further, the heating apparatus further includes:
the second receiving module is used for receiving a control instruction input from the outside;
and the second control module is used for controlling the heating equipment to operate in a second operation mode contained in the control instruction according to the control instruction.
Compared with the prior art, the method has the advantages that the current energy consumption data of the heating equipment, the current use habit of a user on the heating equipment and the current environment data of the place where the heating equipment is located are obtained, and the current energy consumption data, the current use habit and the current environment data are uploaded to the cloud server which is pre-established with the self-adaptive learning model. And the cloud server performs data analysis on the current energy consumption data, the current use habits of the user and the current environment data by adopting a self-adaptive learning model to obtain a use suggestion suitable for the current heating equipment and the environment where the current heating equipment is located. And the cloud server can be in communication connection with the user terminal, and on the basis of current energy consumption data, current use habits and current environment data, after the current use suggestion of the heating equipment is analyzed, the current use suggestion is sent to the user terminal, so that more comfortable and energy-saving setting reference is provided for a user, the user is helped to use the heating equipment more suitably under the current use environment, and the operation of the heating equipment is adapted to the current use environment.
Drawings
Fig. 1 is a schematic flow chart of a control method of a heating facility according to an embodiment of the present invention;
fig. 2 is a schematic flowchart of a control method of a heating facility according to a second embodiment of the present invention;
fig. 3 is a schematic flow chart of a control method of a heating facility according to a third embodiment of the present invention;
fig. 4 is a schematic flowchart of a control method of a heating facility according to a fourth embodiment of the present invention;
FIG. 5 is a schematic block diagram of a heating system according to a fifth embodiment of the present invention;
FIG. 6 is a schematic block diagram of a heating system according to a sixth embodiment of the present invention;
fig. 7 is a schematic block diagram of a heating apparatus according to a seventh embodiment of the present invention;
fig. 8 is a block schematic diagram of a heating facility according to an eighth embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Example one
Referring to fig. 1, a flow chart of a method for controlling a heating device according to an embodiment of the present invention is shown, where the method includes the following steps:
and step S10, acquiring current energy consumption data of the heating equipment, current use habits of users on the heating equipment and current environmental data of the place where the heating equipment is located.
Specifically, the heating equipment includes, but is not limited to, equipment with a temperature adjusting function, such as a wall-mounted furnace, a gas water heater, an electric water heater, and an air conditioner, and heating may be understood as heating and heating water. The energy consumption data of the heating device includes, but is not limited to, the electricity or gas consumption of the heating device, and the heating power and the accumulated heating time of the heating device, and other data related to the energy consumption of the heating device. Therefore, the current energy consumption data includes, but is not limited to, the amount of electricity or gas currently consumed by the heating facility, the current heating power and the accumulated heating time of the heating facility, and the like.
In one embodiment, a wall-mounted boiler is taken as a heating device, and specifically, data such as a target heating water temperature, a target bathroom water temperature, a water consumption amount and the like can be collected or calculated by a sensor (such as a temperature sensor) on the wall-mounted boiler, so as to analyze and calculate energy consumption data such as a power consumption amount, a gas consumption amount and the like. Therefore, the user can know the energy consumption data of the heating equipment every year, every month, every day, every hour and even every minute, and grasp the detailed energy consumption condition of the heating equipment through the energy consumption data so as to control and use the heating equipment more reasonably.
The usage habits of the user for the heating device include, but are not limited to, the user's setting of the heating device parameters actively for target temperature, heating duration, operation mode (e.g., energy saving, comfort, rapid heating, regular heating, etc.) and the like when using the heating device. Thus, current usage habits include, but are not limited to, the target temperature, heating duration, and operating mode for the heating appliance as it is currently being used by the user, which involve actively setting specific parameters of the heating appliance.
In this embodiment, the environmental data of the workplace where the heating device is located includes, but is not limited to, values of environmental parameters such as an ambient temperature, an ambient humidity, an outdoor temperature, and an outdoor humidity in the workplace where the heating device is located. Therefore, the current environmental data includes, but is not limited to, values of environmental parameters such as a current environmental temperature, a current environmental humidity, a current outdoor temperature, and a current outdoor humidity in the location where the heating device is located.
And step S20, uploading the current energy consumption data, the current usage habit and the current environment data to a cloud server communicated with the heating equipment, wherein the cloud server is established with a self-adaptive learning model.
And step S30, controlling the self-adaptive learning model to carry out mining analysis on the current energy consumption data, the current use habit and the current environment data to obtain a current use suggestion for the heating equipment.
In this embodiment, heating equipment accessible Internet of Things (The Internet of Things, IOT) module (like The wireless communication module, WIFI, 4G/5G, ZigBee etc.) realizes The communication with The high in The clouds server, also can realize through Internet of Things module (WIFI module) with other equipment between communication and be connected, The user still can be through terminals such as cell-phones, through modes such as app or webpage, carries out remote operation and control to heating equipment, improve The intellectuality and The user experience of equipment. And a self-adaptive learning model is pre-established in a cloud server in communication connection with the heating equipment. The heating equipment uploads the acquired current energy consumption data, the current use habits of the user and the current environment data of the heating equipment to the cloud server, and the cloud server performs data analysis on the current energy consumption data, the current use habits of the user and the current environment data by adopting a self-adaptive learning model to obtain a use suggestion applicable to the current heating equipment and the environment where the current heating equipment is located.
The use suggestion can be understood as an operation strategy that the heating equipment provides comfortable temperature or bathing temperature for a workplace, and the like, and specifically can include set heating power, indoor temperature for stopping heating, set heating time length, heating power at each stage in the heating time length, and the like. For example, one proposed use may be to control the heating equipment to heat the room with 300W power for 5 minutes, then reduce the power from 300W to 100W, and stop heating when the room temperature is 26 ℃ to achieve "strategic regulation" of the temperature in the work site; in one embodiment, the heating device may also be controlled to heat the bath water to a set and comfortable bath temperature, for example, after the heating device is controlled to heat the water at 300W for 5 minutes, the power is reduced from 300W to 100W, and the heating is stopped when the water is heated to 40 ℃.
And step S40, controlling the cloud server to push the current use suggestion to a user terminal.
It can be understood that the cloud server is in communication connection with a user terminal, and the user terminal includes but is not limited to a mobile terminal such as a mobile phone, a tablet computer, a smart wearable device, a computer, and the like. After the current use suggestion of the heating equipment is analyzed by the cloud server through the self-adaptive learning model according to the current energy consumption data, the current use habit and the current environment data, the current use suggestion is sent to the user terminal, and more comfortable and energy-saving setting reference is provided for a user.
Further, after the cloud server obtains the current use suggestion through analysis, the current use suggestion can be fed back to the heating equipment, and the heating equipment displays the current use suggestion on a connected display device so that a user can know and select the use suggestion as an operation strategy of the heating equipment, the operation state of the heating equipment is completely mastered, and the purposes of comfort and energy conservation are achieved.
In an embodiment, the cloud server may also send the usage advice back to the heating device after obtaining the usage advice, and the heating device may push the current usage advice to the user through a display screen, a speaker and other devices provided in the heating device, for example, the current usage advice is displayed through the display screen, or a sound of the current usage advice is sent through the speaker, and when receiving the current usage advice, the user may actively operate an entity key or a virtual key on the heating device, thereby implementing subsequent "strategic adjustment" on the temperature in the work place or the bath temperature.
In this embodiment, current energy consumption data of the heating equipment, current usage habits of the user on the heating equipment, and current environmental data of a place where the heating equipment is located are obtained, and the current energy consumption data, the current usage habits, and the current environmental data are uploaded to a cloud server in which a self-adaptive learning model is pre-established. And the cloud server performs data analysis on the current energy consumption data, the current use habits of the user and the current environment data by adopting a self-adaptive learning model to obtain a use suggestion suitable for the current heating equipment and the environment where the current heating equipment is located.
And the cloud server is in communication connection with the user terminal, on the basis of the current energy consumption data, the current use habit and the current environment data, after the current use suggestion of the heating equipment is analyzed, the current use suggestion is sent to the user terminal, a more comfortable and energy-saving setting reference is provided for a user, the user is helped to use the heating equipment more suitably under the current use environment, the operation of the heating equipment is made to be adaptive to the current use environment, the problem that the heating equipment is not suitable for operation only according to self experience or no operation experience of the user is avoided, further, the problem that the heating parameters set by the user are not appropriate, the heating time is too short or too long, the comfort of the user is influenced, the energy consumption of the equipment is larger, the energy consumption cost is high and the like.
Example two
Referring to fig. 2, a flowchart of a method for controlling a heating device according to a second embodiment of the present invention is shown, where the second embodiment is different from the first embodiment in that before step S10 in the first embodiment, the method further includes:
and step S50, acquiring historical energy consumption data of the heating equipment in a historical time period, historical use habits of users on the heating equipment and historical environmental data of the place where the heating equipment is located.
And step S60, uploading the historical energy consumption data, the historical use habits and the historical environment data to the cloud server and storing the historical energy consumption data, the historical use habits and the historical environment data.
And step S70, mining and learning the historical energy consumption data, the historical use habits and the historical environmental data to obtain an adaptive learning rule.
And step S80, establishing an adaptive learning model in the cloud server based on the adaptive learning rule.
In this embodiment, the heating device acquires energy consumption data of the heating device, a usage habit of a user on the heating device, environmental data of a place where the heating device is located, and the like in real time, and sends the acquired data to the cloud server. The cloud server obtains and stores the service condition of the heating equipment in the past period of time for big data analysis, obtains the self-adaptive learning rule, and establishes the self-adaptive learning model according to the self-adaptive learning rule so as to provide a comfortable and energy-saving heating environment for the user by calculating the working strategy of the current heating equipment according to the current actual condition of the heating equipment when the heating equipment is subsequently used. The usage condition includes, but is not limited to, energy consumption data, usage habits of users on the heating equipment, environmental data of a place where the heating equipment is located corresponding to a usage time point, and the like.
Further, after the adaptive learning model is established by the cloud server, mining and analyzing are performed according to the current energy consumption data, the current usage habit and the current environment data uploaded by the heating equipment, and a specific method for obtaining a current usage suggestion of the heating equipment comprises the following steps:
comparing and analyzing the historical energy consumption data, the historical use habits and the historical environment data with current energy consumption data, the current use habits and the current environment data respectively to obtain data difference values;
and mining and analyzing the obtained data difference value by adopting the self-adaptive learning rule to obtain a current use suggestion for the heating equipment.
In this embodiment, the cloud server performs big data analysis by acquiring and storing the use condition of the heating equipment in a past period of time, acquires the adaptive learning rule, and establishes the adaptive learning model according to the adaptive learning rule, so that when the heating equipment is subsequently used, the working strategy of the current heating equipment is calculated according to the current actual condition of the heating equipment, and a comfortable and energy-saving heating environment is provided for a user.
EXAMPLE III
Referring to fig. 3, a flow chart of a method for controlling a heating device according to a third embodiment of the present invention is shown, where the third embodiment is different from the first and second embodiments in that after step S40, the method further includes:
and step S90, receiving an operation instruction sent by the user terminal according to the current use suggestion.
And S100, controlling the heating equipment to operate in a first operation mode contained in the current use suggestion according to the operation instruction.
Specifically, in this embodiment, the cloud server sends the current usage suggestion obtained by the adaptive learning model analysis to the user terminal. Similarly, the user terminal is connected with the heating equipment in a communication mode, and after the current use suggestion is received, the user sends a corresponding operation instruction to the heating equipment through the user terminal according to the current use suggestion. And after receiving an operation instruction sent by the user terminal, the heating equipment is controlled to operate in a first operation mode contained in the current use suggestion. The first operation mode can be understood as a mode that each parameter in the heating equipment adopts a numerical value matched with the current use suggestion, and under the first operation mode, the heating equipment can achieve the purposes of adjusting the temperature in a workplace or the temperature of bath water to a relatively comfortable temperature and consuming relatively lower energy.
In this embodiment, after receiving the current usage suggestion analyzed by the cloud server, the user sends an operation instruction corresponding to the current usage suggestion to the heating device through the user terminal. And after receiving the operation instruction sent by the user terminal, the heating equipment operates in a first operation mode contained in the current use suggestion. Through the final confirmation operation of the user, the heating equipment can run according to the current use suggestion obtained by the self-adaptive learning model, the working state of saving energy and ensuring environmental comfort is achieved, and the control of the user on the heating equipment is also improved.
Example four
Referring to fig. 4, a flowchart of a method for controlling a heating device according to a fourth embodiment of the present invention is shown, where the fourth embodiment is different from the third embodiment in that after step S100, the method further includes:
step S110, receiving a control command input from the outside.
And step S120, controlling the heating equipment to operate in a second operation mode contained in the control command according to the control command.
It can be understood that different populations have different requirements for the environmental temperature, and the same population may have individual differences, so that even the optimal working strategy obtained through big data analysis may have a situation that cannot meet the current user requirements. Therefore, when the heating equipment operates in the first operation mode corresponding to the current use suggestion, if a control instruction input from the outside is received, the heating equipment can respond to the control instruction and operate in the second operation mode contained in the control instruction, so that the controllability of the heating equipment is maintained, and more personalized requirements of users are met.
In this embodiment, the second operation mode may be understood as a mode in which a user actively operates (i.e., controls) the heating device so that the heating device correspondingly generates a change in the operation state. For example, if the user wants to increase the temperature, and presses the temperature-increasing button through a device such as a remote controller, etc. to actively send a control instruction for increasing the temperature, the second operation mode included in the control instruction may be a corresponding temperature increase, so as to achieve the purpose of increasing the temperature; if the user wants to heat up more quickly in a short time, and presses a fast button or the like through a device such as a remote controller or the like to actively send a control instruction for fast heating up, the second operation mode can correspondingly increase the power to achieve the purpose of fast heating up. The above description of the second mode of operation is exemplary only and should not be construed as limiting the invention.
In this embodiment, when the heating equipment receives a control instruction input from the outside, the second operation mode included in the control instruction is adopted to operate, so that the requirement of the user on the ambient temperature can be met to the maximum extent in the process of heating the user by the heating equipment, the comfort level of the user is improved, and more personalized requirements of the user are met.
EXAMPLE five
Fig. 5 is a schematic structural diagram of a heating facility according to a fifth embodiment of the present invention, and only the portions related to the embodiment of the present invention are shown for convenience of description. The heating apparatus includes:
the first obtaining module 10 is configured to obtain current energy consumption data of the heating device, current usage habits of a user on the heating device, and current environmental data of a place where the heating device is located.
Specifically, the heating equipment includes, but is not limited to, equipment with a temperature adjusting function, such as a wall-mounted furnace, a gas water heater, an electric water heater, and an air conditioner, and heating may be understood as heating and heating water. The energy consumption data of the heating device includes, but is not limited to, the electricity or gas consumption of the heating device, and the heating power and the accumulated heating time of the heating device, and other data related to the energy consumption of the heating device. Therefore, the current energy consumption data includes, but is not limited to, the amount of electricity or gas currently consumed by the heating facility, the current heating power and the accumulated heating time of the heating facility, and the like.
In one embodiment, a wall-mounted boiler is taken as a heating device, and specifically, data such as a target heating water temperature, a target bathroom water temperature, a water consumption amount and the like can be collected or calculated by a sensor (such as a temperature sensor) on the wall-mounted boiler, so as to analyze and calculate energy consumption data such as a power consumption amount, a gas consumption amount and the like. Therefore, the user can know the energy consumption data of the heating equipment every year, every month, every day, every hour and even every minute, and grasp the detailed energy consumption condition of the heating equipment through the energy consumption data so as to control and use the heating equipment more reasonably.
The usage habits of the user for the heating device include, but are not limited to, the user's setting of the heating device parameters actively for target temperature, heating duration, operation mode (e.g., energy saving, comfort, rapid heating, regular heating, etc.) and the like when using the heating device. Thus, current usage habits include, but are not limited to, the target temperature, heating duration, and operating mode for the heating appliance as it is currently being used by the user, which involve actively setting specific parameters of the heating appliance.
In this embodiment, the environmental data of the workplace where the heating device is located includes, but is not limited to, values of environmental parameters such as an ambient temperature, an ambient humidity, an outdoor temperature, and an outdoor humidity in the workplace where the heating device is located. Therefore, the current environmental data includes, but is not limited to, values of environmental parameters such as a current environmental temperature, a current environmental humidity, a current outdoor temperature, and a current outdoor humidity in the location where the heating device is located.
The first uploading module 20 is configured to upload the current energy consumption data, the current usage habit and the current environment data to a cloud server in communication with the heating device, where the cloud server is established with an adaptive learning model.
And the first analysis module 30 is configured to control the adaptive learning model to perform mining analysis on the current energy consumption data, the current usage habit and the current environment data to obtain a current usage suggestion for the heating equipment.
In this embodiment, heating equipment accessible Internet of Things (The Internet of Things, IOT) module (like The wireless communication module, wifi, 4G/5G, ZigBee etc.) realizes The communication with The cloud server, also can realize through Internet of Things module with other equipment between communication and be connected, The user still can be through terminals such as cell-phones, through modes such as app or webpage, carries out remote operation and control to heating equipment, improve The intellectuality and The user experience of equipment. And a self-adaptive learning model is pre-established in a cloud server in communication connection with the heating equipment. The heating equipment uploads the acquired current energy consumption data, the current use habits of the user and the current environment data of the heating equipment to the cloud server, and the cloud server performs data analysis on the current energy consumption data, the current use habits of the user and the current environment data by adopting a self-adaptive learning model to obtain a use suggestion applicable to the current heating equipment and the environment where the current heating equipment is located.
The use suggestion can be understood as an operation strategy that the heating equipment provides comfortable temperature or bathing temperature for a workplace, and the like, and specifically can include set heating power, indoor temperature for stopping heating, set heating time length, heating power at each stage in the heating time length, and the like. For example, one proposed use may be to control the heating equipment to heat the room with 300W power for 5 minutes, then reduce the power from 300W to 100W, and stop heating when the room temperature is 26 ℃ to achieve "strategic regulation" of the temperature in the work site; in one embodiment, the heating device may also be controlled to heat the bath water to a set and comfortable bath temperature, for example, after the heating device is controlled to heat the water at 300W for 5 minutes, the power is reduced from 300W to 100W, and the heating is stopped when the water is heated to 40 ℃.
The first pushing module 40 is configured to control the cloud server to push the current usage suggestion to a user.
It can be understood that the cloud server is in communication connection with a user terminal, and the user terminal includes but is not limited to a mobile terminal such as a mobile phone, a tablet computer, a smart wearable device, a computer, and the like. After the current use suggestion of the heating equipment is analyzed by the cloud server through the self-adaptive learning model according to the current energy consumption data, the current use habit and the current environment data, the current use suggestion is sent to the user terminal, and more comfortable and energy-saving setting reference is provided for a user.
Further, after the cloud server obtains the current use suggestion through analysis, the current use suggestion can be fed back to the heating equipment, and the heating equipment displays the current use suggestion on a connected display device so that a user can know and select the use suggestion as an operation strategy of the heating equipment, the operation state of the heating equipment is completely mastered, and the purposes of comfort and energy conservation are achieved.
In an embodiment, the cloud server may also send the usage advice back to the heating device after obtaining the usage advice, and the heating device may push the current usage advice to the user through a display screen, a speaker and other devices provided in the heating device, for example, the current usage advice is displayed through the display screen, or a sound of the current usage advice is sent through the speaker, and when receiving the current usage advice, the user may actively operate an entity key or a virtual key on the heating device, thereby implementing subsequent "strategic adjustment" on the temperature in the work place or the bath temperature.
In this embodiment, current energy consumption data of the heating equipment, current usage habits of the user on the heating equipment, and current environmental data of a place where the heating equipment is located are obtained, and the current energy consumption data, the current usage habits, and the current environmental data are uploaded to a cloud server in which a self-adaptive learning model is pre-established. And the cloud server performs data analysis on the current energy consumption data, the current use habits of the user and the current environment data by adopting a self-adaptive learning model to obtain a use suggestion suitable for the current heating equipment and the environment where the current heating equipment is located.
And the cloud server is in communication connection with the user terminal, on the basis of the current energy consumption data, the current use habit and the current environment data, after the current use suggestion of the heating equipment is analyzed, the current use suggestion is sent to the user terminal, a more comfortable and energy-saving setting reference is provided for a user, the user is helped to use the heating equipment more suitably under the current use environment, the operation of the heating equipment is made to be adaptive to the current use environment, the problem that the heating equipment is not suitable for operation only according to self experience or no operation experience of the user is avoided, further, the problem that the heating parameters set by the user are not appropriate, the heating time is too short or too long, the comfort of the user is influenced, the energy consumption of the equipment is larger, the energy consumption cost is high and the like.
EXAMPLE six
Referring to fig. 6, a block diagram of a heating apparatus according to a sixth embodiment of the present invention is provided, where the sixth embodiment is different from the fifth embodiment in that the heating apparatus further includes:
a second obtaining module 50, configured to obtain historical energy consumption data of the heating device in a historical time period, historical usage habits of a user on the heating device, and historical environmental data of a location where the heating device is located;
a second uploading module 60, configured to upload and store the historical energy consumption data, the historical usage habits, and the historical environmental data to the cloud server;
the first learning module 70 is configured to perform mining learning on the historical energy consumption data, the historical usage habits, and the historical environmental data to obtain adaptive learning rules;
a first establishing module 80, configured to establish an adaptive learning model in the cloud server based on the adaptive learning rule.
In this embodiment, the heating device acquires energy consumption data of the heating device, a usage habit of a user on the heating device, environmental data of a place where the heating device is located, and the like in real time, and sends the acquired data to the cloud server. The cloud server obtains and stores the service condition of the heating equipment in the past period of time for big data analysis, obtains the self-adaptive learning rule, and establishes the self-adaptive learning model according to the self-adaptive learning rule so as to provide a comfortable and energy-saving heating environment for the user by calculating the working strategy of the current heating equipment according to the current actual condition of the heating equipment when the heating equipment is subsequently used. The usage condition includes, but is not limited to, energy consumption data, usage habits of users on the heating equipment, environmental data of a place where the heating equipment is located corresponding to a usage time point, and the like.
Further, after the adaptive learning model is established in the cloud server, the first analysis module 30 includes:
the second analysis module is used for comparing and analyzing the historical energy consumption data, the historical use habits and the historical environment data with the current energy consumption data, the current use habits and the current environment data to obtain a data difference value;
and the third analysis module is used for mining and analyzing the data difference values according to the self-adaptive learning rule to obtain the current use suggestion of the heating equipment.
In this embodiment, the cloud server performs big data analysis by acquiring and storing the use condition of the heating equipment in a past period of time, acquires the adaptive learning rule, and establishes the adaptive learning model according to the adaptive learning rule, so that when the heating equipment is subsequently used, the working strategy of the current heating equipment is calculated according to the current actual condition of the heating equipment, and a comfortable and energy-saving heating environment is provided for a user.
EXAMPLE seven
Referring to fig. 7, a modular view of a heating apparatus according to a seventh embodiment of the present invention is shown, where the seventh embodiment is different from the fifth and sixth embodiments in that the heating apparatus further includes:
a first receiving module 90, configured to receive an operation instruction sent by the user terminal according to the current usage suggestion;
and the first control module 100 is used for controlling the heating equipment to operate in a first operation mode contained in the current use suggestion according to the operation instruction.
Specifically, in this embodiment, the cloud server sends the current usage suggestion obtained by the adaptive learning model analysis to the user terminal. Similarly, the user terminal is connected with the heating equipment in a communication mode, and after the current use suggestion is received, the user sends a corresponding operation instruction to the heating equipment through the user terminal according to the current use suggestion. And after receiving an operation instruction sent by the user terminal, the heating equipment is controlled to operate in a first operation mode contained in the current use suggestion. The first operation mode can be understood as a mode that each parameter in the heating equipment adopts a numerical value matched with the current use suggestion, and under the first operation mode, the heating equipment can achieve the purposes of adjusting the temperature in a workplace or the temperature of bath water to a relatively comfortable temperature and consuming relatively lower energy.
In this embodiment, after receiving the current usage suggestion analyzed by the cloud server, the user sends an operation instruction corresponding to the current usage suggestion to the heating device through the user terminal. And after receiving the operation instruction sent by the user terminal, the heating equipment operates in a first operation mode contained in the current use suggestion. Through the final confirmation operation of the user, the heating equipment can run according to the current use suggestion obtained by the self-adaptive learning model, the working state of saving energy and ensuring environmental comfort is achieved, and the control of the user on the heating equipment is also improved.
Example eight
Referring to fig. 8, a modular view of a heating apparatus according to an eighth embodiment of the present invention is shown, where the eighth embodiment is different from the seventh embodiment in that the heating apparatus further includes:
a second receiving module 110, configured to receive a control instruction input from the outside;
and the second control module 120 is configured to control the heating device to operate in a second operation mode included in the control instruction according to the control instruction.
It can be understood that different populations have different requirements for the environmental temperature, and the same population may have individual differences, so that even the optimal working strategy obtained through big data analysis may have a situation that cannot meet the current user requirements. Therefore, when the heating equipment operates in the first operation mode corresponding to the current use suggestion, if a control instruction input from the outside is received, the heating equipment can respond to the control instruction and operate in the second operation mode contained in the control instruction, so that the controllability of the heating equipment is maintained, and more personalized requirements of users are met.
In this embodiment, the second operation mode may be understood as a mode in which a user actively operates (i.e., controls) the heating device so that the heating device correspondingly generates a change in the operation state. For example, if the user wants to increase the temperature, and presses the temperature-increasing button through a device such as a remote controller, etc. to actively send a control instruction for increasing the temperature, the second operation mode included in the control instruction may be a corresponding temperature increase, so as to achieve the purpose of increasing the temperature; if the user wants to heat up more quickly in a short time, and presses a fast button or the like through a device such as a remote controller or the like to actively send a control instruction for fast heating up, the second operation mode can correspondingly increase the power to achieve the purpose of fast heating up. The above description of the second mode of operation is exemplary only and should not be construed as limiting the invention.
In this embodiment, when the heating equipment receives a control instruction input from the outside, the second operation mode included in the control instruction is adopted to operate, so that the requirement of the user on the ambient temperature can be met to the maximum extent in the process of heating the user by the heating equipment, the comfort level of the user is improved, and more personalized requirements of the user are met.
The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.
Claims (10)
1. A method for controlling a heating facility, the method comprising the steps of:
acquiring current energy consumption data of the heating equipment, current use habits of users on the heating equipment and current environmental data of a place where the heating equipment is located;
uploading the current energy consumption data, the current usage habits and the current environment data to a cloud server which is communicated with the heating equipment, wherein the cloud server is provided with a self-adaptive learning model;
controlling the self-adaptive learning model to carry out mining analysis on the current energy consumption data, the current use habit and the current environment data to obtain a current use suggestion for the heating equipment;
and controlling the cloud server to push the current use suggestion to a user terminal.
2. The method for controlling a heating facility according to claim 1, before the obtaining the current energy consumption data of the heating facility, the current usage habit of the heating facility by the user, and the current environmental data of the location where the heating facility is located, further comprising:
acquiring historical energy consumption data of the heating equipment in a historical time period, historical use habits of users on the heating equipment and historical environmental data of a place where the heating equipment is located;
uploading the historical energy consumption data, the historical use habits and the historical environment data to the cloud server and storing the historical energy consumption data, the historical use habits and the historical environment data;
mining and learning the historical energy consumption data, the historical use habits and the historical environment data to obtain a self-adaptive learning rule;
and establishing a self-adaptive learning model in the cloud server based on the self-adaptive learning rule.
3. The heating facility control method according to claim 2, wherein the step of controlling the adaptive learning model to mine and analyze the current energy consumption data, the current usage habits, and the current environmental data to obtain a current usage recommendation for the heating facility comprises:
comparing and analyzing the historical energy consumption data, the historical use habits and the historical environment data with the current energy consumption data, the current use habits and the current environment data to obtain a data difference value;
and mining and analyzing the data difference values according to the self-adaptive learning rule to obtain a current use suggestion for the heating equipment.
4. The heating facility control method according to claim 1, wherein the heating facility is further connected to the user terminal in a communication manner, and after the controlling the cloud server to send the current usage recommendation to the user terminal, the method further comprises:
receiving an operation instruction sent by the user terminal according to the current use suggestion;
and controlling the heating equipment to operate in a first operation mode contained in the current use suggestion according to the operation instruction.
5. The heating facility control method according to claim 4, wherein the controlling the heating facility to operate in the first operation mode included in the current usage advice according to the operation command includes:
receiving a control instruction input from the outside;
and controlling the heating equipment to operate in a second operation mode contained in the control command according to the control command.
6. A heating installation, characterized in that it comprises:
the first acquisition module is used for acquiring current energy consumption data of the heating equipment, current use habits of users on the heating equipment and current environment data of places where the heating equipment is located;
the first uploading module is used for uploading the current energy consumption data, the current use habit and the current environment data to a cloud server communicated with the heating equipment, and the cloud server is provided with a self-adaptive learning model;
the first analysis module is used for controlling the self-adaptive learning model to mine and analyze the current energy consumption data, the current use habit and the current environment data to obtain a current use suggestion for the heating equipment;
and the first pushing module is used for controlling the cloud server to push the current use suggestion to the user terminal.
7. The heating installation of claim 6, further comprising:
the second acquisition module is used for acquiring historical energy consumption data of the heating equipment in a historical time period, historical use habits of users on the heating equipment and historical environmental data of a place where the heating equipment is located;
the second uploading module is used for uploading the historical energy consumption data, the historical using habits and the historical environment data to the cloud server and storing the historical energy consumption data, the historical using habits and the historical environment data;
the first learning module is used for mining and learning the historical energy consumption data, the historical use habits and the historical environment data to obtain a self-adaptive learning rule;
the first establishing module is used for establishing an adaptive learning model in the cloud server on the basis of the adaptive learning rule.
8. The heating installation of claim 7, further comprising:
the second analysis module is used for comparing and analyzing the historical energy consumption data, the historical use habits and the historical environment data with the current energy consumption data, the current use habits and the current environment data to obtain a data difference value;
and the third analysis module is used for mining and analyzing the data difference values according to the self-adaptive learning rule to obtain the current use suggestion of the heating equipment.
9. The heating installation of claim 6, wherein the heating installation is further communicatively coupled to the user terminal, the heating installation further comprising:
a first receiving module, configured to receive an operation instruction sent by the user terminal according to the current usage suggestion;
and the first control module is used for controlling the heating equipment to operate in a first operation mode contained in the current use suggestion according to the operation instruction.
10. The heating installation of claim 9, further comprising:
the second receiving module is used for receiving a control instruction input from the outside;
and the second control module is used for controlling the heating equipment to operate in a second operation mode contained in the control instruction according to the control instruction.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011015059.XA CN112161322B (en) | 2020-09-24 | 2020-09-24 | Heating equipment and control method thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011015059.XA CN112161322B (en) | 2020-09-24 | 2020-09-24 | Heating equipment and control method thereof |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN112161322A true CN112161322A (en) | 2021-01-01 |
| CN112161322B CN112161322B (en) | 2022-04-29 |
Family
ID=73863643
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011015059.XA Active CN112161322B (en) | 2020-09-24 | 2020-09-24 | Heating equipment and control method thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112161322B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113706029A (en) * | 2021-08-31 | 2021-11-26 | 广东电网有限责任公司 | Self-adaptive management method, device and system for household energy |
| CN114738827A (en) * | 2022-04-12 | 2022-07-12 | 建科环能科技有限公司 | Household electric heating intelligent group control method and system based on user habits |
Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0356609A1 (en) * | 1988-08-31 | 1990-03-07 | Landis & Gyr Business Support AG | Set-point adjuster for a domestic hot water storage regulator |
| CN101256418A (en) * | 2008-03-28 | 2008-09-03 | 清华大学 | Combination control method for exit temperature of heating furnace |
| CN102193525A (en) * | 2010-03-05 | 2011-09-21 | 朗德华信（北京）自控技术有限公司 | System and method for monitoring device based on cloud computing |
| CN103162346A (en) * | 2013-03-27 | 2013-06-19 | 新奥科技发展有限公司 | Central heating monitoring system based on cloud service and adjustment method thereof |
| CN104791903A (en) * | 2015-04-30 | 2015-07-22 | 北京上庄燃气热电有限公司 | Intelligent heating network dispatching system |
| CN105387565A (en) * | 2015-11-24 | 2016-03-09 | 深圳市酷开网络科技有限公司 | Temperature adjusting method and device |
| CN105974869A (en) * | 2016-06-28 | 2016-09-28 | 江苏长宁电力科技有限公司 | Energy-saving monitoring center applied to building environment adaptive energy-saving management system |
| CN106052140A (en) * | 2016-06-27 | 2016-10-26 | 京东方科技集团股份有限公司 | Water heater control device, water heater and control method of water heater |
| CN107166735A (en) * | 2017-05-09 | 2017-09-15 | 珠海格力电器股份有限公司 | Control method, device and the equipment of water heater and water heater mixed water temperature |
| CN107643686A (en) * | 2017-09-27 | 2018-01-30 | 上海深研智能科技有限公司 | The control system and method that water purifier heating power is distributed rationally |
| CN108518730A (en) * | 2018-04-10 | 2018-09-11 | 广东环境保护工程职业学院 | A kind of energy saving central heating net and self-adaptation control method based on atmospheric temperature control |
| CN109827292A (en) * | 2019-01-16 | 2019-05-31 | 珠海格力电器股份有限公司 | Construction method, control method, the household electrical appliances of household electrical appliances adaptive power conservation Controlling model |
| US20190187644A1 (en) * | 2011-12-13 | 2019-06-20 | Patrick Andrew Shiel | Development of certain building data profiles and their use in an automated optimization method to reduce thermal energy consumption in commercial buildings during the heating season |
| CN109915886A (en) * | 2019-01-23 | 2019-06-21 | 深圳市合信达控制系统有限公司 | A kind of control method of energy-saving heating equipment, system and energy-saving heating equipment |
| CN110332605A (en) * | 2019-07-16 | 2019-10-15 | 常州英集动力科技有限公司 | Heat supply network energy consumption index analysis and early warning method and system based on BP neural network |
| CN111006303A (en) * | 2019-12-13 | 2020-04-14 | 艾沃（深圳）智能环境科技有限公司 | Intelligent heating control system and method |
| CN111339641A (en) * | 2020-02-13 | 2020-06-26 | 山东神舟制冷设备有限公司 | Refrigeration system management method and device, cloud platform and storage medium |
| CN111367193A (en) * | 2020-03-31 | 2020-07-03 | 北京天成冠通能源科技有限公司 | Building automation control method and system |
| CN111609534A (en) * | 2020-05-25 | 2020-09-01 | 珠海拓芯科技有限公司 | Temperature control method and device and central temperature control system |
-
2020
- 2020-09-24 CN CN202011015059.XA patent/CN112161322B/en active Active
Patent Citations (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP0356609A1 (en) * | 1988-08-31 | 1990-03-07 | Landis & Gyr Business Support AG | Set-point adjuster for a domestic hot water storage regulator |
| CN101256418A (en) * | 2008-03-28 | 2008-09-03 | 清华大学 | Combination control method for exit temperature of heating furnace |
| CN102193525A (en) * | 2010-03-05 | 2011-09-21 | 朗德华信（北京）自控技术有限公司 | System and method for monitoring device based on cloud computing |
| US20190187644A1 (en) * | 2011-12-13 | 2019-06-20 | Patrick Andrew Shiel | Development of certain building data profiles and their use in an automated optimization method to reduce thermal energy consumption in commercial buildings during the heating season |
| CN103162346A (en) * | 2013-03-27 | 2013-06-19 | 新奥科技发展有限公司 | Central heating monitoring system based on cloud service and adjustment method thereof |
| CN104791903A (en) * | 2015-04-30 | 2015-07-22 | 北京上庄燃气热电有限公司 | Intelligent heating network dispatching system |
| CN105387565A (en) * | 2015-11-24 | 2016-03-09 | 深圳市酷开网络科技有限公司 | Temperature adjusting method and device |
| CN106052140A (en) * | 2016-06-27 | 2016-10-26 | 京东方科技集团股份有限公司 | Water heater control device, water heater and control method of water heater |
| CN105974869A (en) * | 2016-06-28 | 2016-09-28 | 江苏长宁电力科技有限公司 | Energy-saving monitoring center applied to building environment adaptive energy-saving management system |
| CN107166735A (en) * | 2017-05-09 | 2017-09-15 | 珠海格力电器股份有限公司 | Control method, device and the equipment of water heater and water heater mixed water temperature |
| CN107643686A (en) * | 2017-09-27 | 2018-01-30 | 上海深研智能科技有限公司 | The control system and method that water purifier heating power is distributed rationally |
| CN108518730A (en) * | 2018-04-10 | 2018-09-11 | 广东环境保护工程职业学院 | A kind of energy saving central heating net and self-adaptation control method based on atmospheric temperature control |
| CN109827292A (en) * | 2019-01-16 | 2019-05-31 | 珠海格力电器股份有限公司 | Construction method, control method, the household electrical appliances of household electrical appliances adaptive power conservation Controlling model |
| CN109915886A (en) * | 2019-01-23 | 2019-06-21 | 深圳市合信达控制系统有限公司 | A kind of control method of energy-saving heating equipment, system and energy-saving heating equipment |
| CN110332605A (en) * | 2019-07-16 | 2019-10-15 | 常州英集动力科技有限公司 | Heat supply network energy consumption index analysis and early warning method and system based on BP neural network |
| CN111006303A (en) * | 2019-12-13 | 2020-04-14 | 艾沃（深圳）智能环境科技有限公司 | Intelligent heating control system and method |
| CN111339641A (en) * | 2020-02-13 | 2020-06-26 | 山东神舟制冷设备有限公司 | Refrigeration system management method and device, cloud platform and storage medium |
| CN111367193A (en) * | 2020-03-31 | 2020-07-03 | 北京天成冠通能源科技有限公司 | Building automation control method and system |
| CN111609534A (en) * | 2020-05-25 | 2020-09-01 | 珠海拓芯科技有限公司 | Temperature control method and device and central temperature control system |
Non-Patent Citations (1)
| Title |
|---|
| 冯剑等: "基于数据驱动的分散式电采暖负荷运行特性分析", 《内蒙古电力技术》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113706029A (en) * | 2021-08-31 | 2021-11-26 | 广东电网有限责任公司 | Self-adaptive management method, device and system for household energy |
| CN114738827A (en) * | 2022-04-12 | 2022-07-12 | 建科环能科技有限公司 | Household electric heating intelligent group control method and system based on user habits |
| CN114738827B (en) * | 2022-04-12 | 2023-09-26 | 建科环能科技有限公司 | User habit-based intelligent group control method and system for heating by using electricity |
Also Published As
| Publication number | Publication date |
|---|---|
| CN112161322B (en) | 2022-04-29 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6306727B2 (en) | Smart home scene switching method and system | |
| CN105573135B (en) | A kind of control method and device of intelligent appliance | |
| CN103982986B (en) | Air-conditioner and comfortable control method thereof and device | |
| CN112161322B (en) | Heating equipment and control method thereof | |
| EP2544333A1 (en) | Appliance control system | |
| CN104776547A (en) | Control method of air conditioner, terminal and air conditioner | |
| CN110531633B (en) | Cooperative control method and device based on intelligent home operating system and storage medium | |
| JP2010213367A (en) | Energy saving system using ubiquitous sensor and intelligent table tap | |
| CN104214888B (en) | Air-conditioner and its temprature control method, device | |
| CN105485863B (en) | A kind of control device of air-conditioning and the method for controlling air conditioning electricity | |
| CN104154631A (en) | Controller capable of automatically adjusting parameters of equipment | |
| WO2016155552A1 (en) | Information pushing method and apparatus based on smart home system | |
| CN209356874U (en) | Temperature controller and smart home system | |
| CN104833038A (en) | VRF air conditioner centralized control method and VRF air conditioner integrated controller | |
| CN106647295B (en) | Smart home system and cooperative operation method thereof | |
| KR20140062367A (en) | Building energy management system and method for controlling the same | |
| CN104728926A (en) | Floor heating system temperature adjusting method and device | |
| KR20170053238A (en) | Internet (IoT) smart home / building automation system and its control method for energy saving and power saving by crowd service | |
| JP5907811B2 (en) | Power consumption adjustment system | |
| KR101668630B1 (en) | Device, system and method for smart control using gps, recording medium for performing the method | |
| CN111381505A (en) | Intelligent household control system and control method thereof | |
| CN104896573A (en) | Heat-supply intelligent temperature controller | |
| TW201702982A (en) | Energy resource consumption management method reduces consumption of energy resource under state of no stopping supplying energy resource | |
| CN204494713U (en) | Based on the high intelligent air condition of Internet of Things | |
| CN105867478B (en) | A kind of processing method, electronic equipment and processing 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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |