CN110940062B - Air conditioner control method and device - Google Patents
Air conditioner control method and device Download PDFInfo
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- CN110940062B CN110940062B CN201811115991.2A CN201811115991A CN110940062B CN 110940062 B CN110940062 B CN 110940062B CN 201811115991 A CN201811115991 A CN 201811115991A CN 110940062 B CN110940062 B CN 110940062B
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- 238000010801 machine learning Methods 0.000 claims abstract description 15
- 238000004378 air conditioning Methods 0.000 claims description 8
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/50—Control or safety arrangements characterised by user interfaces or communication
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/88—Electrical aspects, e.g. circuits
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Abstract
The invention discloses an air conditioner control method and device. Wherein, the method comprises the following steps: acquiring spatial information of the air conditioner and a working environment, wherein the spatial information comprises the size and the pattern of the working environment and the position of the air conditioner in the working space; inputting a prediction model according to spatial information, and outputting a control instruction corresponding to the spatial information by the prediction model, wherein the prediction model is obtained by using a plurality of groups of training data through machine learning training, and each group of data in the plurality of groups of training data comprises: the spatial information and a control instruction corresponding to the spatial information; and controlling the air conditioner to work according to the control instruction. The invention solves the technical problem that the temperature difference between different spaces is larger due to different sizes or different patterns of the different spaces in the prior art.
Description
Technical Field
The invention relates to the technical field of air conditioner control, in particular to an air conditioner control method and device.
Background
The air conditioner is an indispensable electrical appliance in people's life, and the intelligent frequency conversion technology of current air conditioner has realized energy-conserving purpose to a great extent, and of course this kind of mode is only limited to the region that the area is relatively little, for example, family sitting room, bedroom etc.. When many air conditioners are operated at the same time in a large closed place such as a convention and exhibition center, a conference hall, etc., it is difficult to ensure that the temperature of the area where the air conditioners are operated is constant. For example, there may be a living room and a bedroom in a house, and the air conditioner is generally installed in the living room, but because the bedroom is located a certain distance from the living room and the pattern of the bedroom is different from that of the living room, the above factors may cause a large temperature difference between the bedroom and the living room. However, when the air conditioner works in different spaces with large temperature difference, on one hand, people feel uncomfortable, and on the other hand, electricity is wasted. Therefore, the prior art has the problem that the temperature difference between different spaces is large due to different sizes or different patterns of the different spaces.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides an air conditioner control method and device, which at least solve the technical problem that in the prior art, temperature difference between different spaces is large due to the fact that the sizes or the patterns of the different spaces are different.
According to an aspect of an embodiment of the present invention, there is provided an air conditioner control method including: acquiring spatial information of an air conditioner and a working environment, wherein the spatial information comprises the size and the pattern of the working environment and the position of the air conditioner in the working space; inputting a prediction model according to the spatial information, and outputting a control instruction corresponding to the spatial information by the prediction model, wherein the prediction model is obtained by using multiple sets of training data through machine learning training, and each set of data in the multiple sets of training data comprises: spatial information and a control instruction corresponding to the spatial information; and controlling the air conditioner to work according to the control instruction.
Optionally, the obtaining of the spatial information of the air conditioner and the working environment includes: acquiring an electronic map of the working environment; and acquiring the position of the air conditioner in the electronic map.
Optionally, inputting a prediction model according to the spatial information, and outputting a control instruction corresponding to the spatial information by the prediction model before the method includes: judging whether the acquired space information of the air conditioner and the working environment changes compared with the space information acquired last time; and under the condition that the spatial information of the air conditioner and the working environment changes, predicting a corresponding control instruction according to the spatial information.
Optionally, inputting a prediction model according to the spatial information, and outputting a control instruction corresponding to the spatial information by the prediction model includes: inputting a prediction sub-model according to the spatial information, and outputting the temperature difference condition corresponding to the spatial information by the prediction sub-model; determining the control instruction according to the temperature difference condition; the predictor model is obtained by using a plurality of groups of training data and training through machine learning, and each group of data in the plurality of groups of training data comprises: the temperature difference condition corresponding to the space information.
Optionally, the temperature difference condition is a temperature difference of different spaces of the working environment.
Optionally, the control instruction comprises at least one of: adjusting the working temperature of the air conditioner, changing the working mode of the air conditioner, moving the position of the air conditioner and adjusting the air speed of the air conditioner.
According to another aspect of the embodiments of the present invention, there is also provided an air conditioning control apparatus including: the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring the spatial information of an air conditioner and a working environment, and the spatial information comprises the size and the pattern of the working environment and the position of the air conditioner in the working space; the prediction module is used for inputting a prediction model according to the spatial information and outputting a control instruction corresponding to the spatial information by the prediction model, wherein the prediction model is obtained by using multiple groups of training data through machine learning training, and each group of data in the multiple groups of training data comprises: spatial information and a control instruction corresponding to the spatial information; and the control module is used for controlling the air conditioner to work according to the control instruction.
According to another aspect of the embodiments of the present invention, there is also provided a storage medium, where the storage medium stores program instructions, and when the program instructions are executed, the storage medium is controlled by an apparatus to execute any one of the above methods.
According to another aspect of the embodiments of the present invention, there is also provided a processor, configured to execute a program, where the program executes to perform the method described in any one of the above.
According to another aspect of the embodiment of the invention, an air conditioner is further provided, and the air conditioner comprises the air conditioner control device.
In the embodiment of the invention, the method comprises the steps of acquiring the spatial information of an air conditioner and a working environment, wherein the spatial information comprises the size and the pattern of the working environment and the position of the air conditioner in the working space; inputting a prediction model according to the spatial information, and outputting a control instruction corresponding to the spatial information by the prediction model, wherein the prediction model is obtained by using multiple sets of training data through machine learning training, and each set of data in the multiple sets of training data comprises: spatial information and a control instruction corresponding to the spatial information; according to the mode of controlling the air conditioner to work according to the control command, the aim of executing different control on the air conditioner according to the size and the layout of different spaces is fulfilled through the prediction model, so that the technical effect of reducing the temperature difference among different spaces is achieved, and the technical problem that the temperature difference among different spaces is large due to the fact that the sizes or the layouts of different spaces are different in the prior art is solved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a flowchart of an air conditioner control method according to an embodiment of the present invention;
fig. 2 is a schematic structural diagram of an air conditioning control device according to an embodiment of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to an embodiment of the present invention, there is provided an embodiment of an air conditioning control method, it should be noted that the steps shown in the flowchart of the drawings may be executed in a computer system such as a set of computer executable instructions, and that although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in an order different from that here.
Fig. 1 is a flowchart of an air conditioner control method according to an embodiment of the present invention, as shown in fig. 1, the method including the steps of:
step S102, acquiring spatial information of the air conditioner and a working environment, wherein the spatial information comprises the size and the pattern of the working environment and the position of the air conditioner in the working space;
step S104, inputting a prediction model according to the spatial information, and outputting a control instruction corresponding to the spatial information by the prediction model, wherein the prediction model is obtained by using a plurality of groups of training data through machine learning training, and each group of data in the plurality of groups of training data comprises: the spatial information and a control instruction corresponding to the spatial information;
and step S106, controlling the air conditioner to work according to the control instruction.
Through the steps, the air conditioner and the space information of the working environment can be obtained, wherein the space information comprises the size and the pattern of the working environment and the position of the air conditioner in the working space; inputting a prediction model according to spatial information, and outputting a control instruction corresponding to the spatial information by the prediction model, wherein the prediction model is obtained by using a plurality of groups of training data through machine learning training, and each group of data in the plurality of groups of training data comprises: the spatial information and a control instruction corresponding to the spatial information; according to the mode of controlling the air conditioner to work according to the control instruction, the aim of executing different control on the air conditioner according to the size and the layout of different spaces is fulfilled through the prediction model, so that the technical effect of reducing the temperature difference among different spaces is achieved, and the technical problem that the temperature difference among different spaces is large due to the fact that the sizes or the layouts of different spaces are different in the prior art is solved.
When the air conditioner and the spatial information of the working environment are acquired, where the spatial information of the air conditioner is the position of the air conditioner in the space where the air conditioner is located, and the spatial information of the working environment is the size and the configuration of the working environment, it should be noted that the working environment is different spaces in the same area or the same space in the same area, and the same area is an area that can be affected by the air conditioner. For example, the building may be a one-floor space of a building, or a house of a residential building. The space size can be characterized by a specific area, or can be determined by a fixed multiple of the space size, for example, the space size can be a specific area value, or can be one or more standard balcony areas. Wherein, the pattern can be a regular shape pattern, such as a regular rectangle, a square, an equilateral, etc.; or may be irregularly shaped, e.g., trapezoidal, curved, curvilinear, etc.
After a prediction model is built, a plurality of regions with different spatial sizes and patterns are trained through machine learning, wherein training data comprise spatial information and control instructions corresponding to the spatial information. Through the prediction model, the air conditioner control mode corresponding to the space size and the pattern is accurately predicted, and the temperature difference among different spaces can be effectively reduced. The intelligent control of the air conditioner is effectively improved, and electric energy can be effectively saved.
And correspondingly controlling the air conditioner according to the control instruction obtained by the prediction model. The control instruction can realize the adjustment of the working temperature of the air conditioner, the change of the working mode of the air conditioner, the movement of the position of the air conditioner, the adjustment of the air speed of the air conditioner and the like. When the intelligent air conditioner is used in the technical field of intelligent air conditioners, the energy-saving purpose is achieved, a comfortable humanized service is provided, and the user experience is improved.
In the embodiment of the invention, the electric appliances are effectively controlled according to the space sizes and the patterns of different spaces in the same area, and the comfort level of a user in different spaces in the same area is improved. In addition, this technique can expand a plurality of domestic appliance, for example, the lighting apparatus of electric heater, audio amplifier, steerable luminance etc. can solve when a plurality of appliances simultaneous workings, because the different uncomfortable problem that leads to the user to produce of difference of electrical apparatus operating condition of the different environment that leads to of locating for when the electrical apparatus realizes intelligent regulation control, promoted the degree of depth experience of user to intellectuality.
Optionally, the obtaining of the spatial information of the air conditioner and the working environment includes: acquiring an electronic map of a working environment; and acquiring the position of the air conditioner in the electronic map.
The electronic map for acquiring the working environment of the air conditioner may be a two-dimensional plane map or a three-dimensional stereo map, wherein the position of the air conditioner in the electronic map may be represented in the form of map coordinates or a relative position identified by a fixed object in the space. The electronic map can be updated in real time as the air conditioner or other space object moves. For example, in a large conference room, when the air conditioner operates by moving its own position, the air conditioner is moved to a different place in the conference room from the position of the chairman station, and the position of the air conditioner in the electronic map is also changed. If someone in the meeting room occupies a certain position of the air conditioner moving route, the electronic map is updated in time, and the position is regarded as an obstacle, so that the air conditioner can adjust the working route and the like. If the positions of the table, the chair, the cabinet and the like in the conference room are changed, the electronic map is updated. By acquiring the electronic map of the working environment of the air conditioner and the position of the air conditioner in the electronic map, the position information of the air conditioner and the change of the working space information of the air conditioner can be timely mastered, so that the air conditioner can effectively adjust the working state.
Optionally, inputting the prediction model according to the spatial information, and outputting the control instruction corresponding to the spatial information by the prediction model before includes: judging whether the acquired space information of the air conditioner and the working environment changes compared with the space information acquired last time; and under the condition that the space information of the air conditioner and the working environment changes, predicting a corresponding control command according to the space information.
Because the air conditioner can constantly detect the temperature of the working environment, when the space information of the air conditioner and the working environment is acquired in real time, if the space information is different, the temperature detected by the air conditioner may possibly change. The air conditioner compares the space information of the air conditioner and the working environment which are obtained currently with the space information which is obtained last time, and whether the space information where the air conditioner is located is changed is further judged. If the spatial information of the air conditioner and the working environment changes, the air conditioner can adjust according to the temperature difference generated by the difference of the spatial information; if the space information of the air conditioner and the working environment is not changed, the air conditioner can continuously execute the last control command. In the embodiment of the present invention, the number of the air conditioners may be one or more, and the air conditioners may be in a fixed state, a moving state, or a combination of the two states. It should be noted that, the comparison between the currently acquired spatial information of the air conditioner and the working environment and the last acquired spatial information may be the same spatial information or a comparison between different spatial information. Through the comparison, the change condition of the spatial information can be mastered, and the control instruction corresponding to the spatial information can be accurately predicted according to the change condition, so that the accurate control of the working state of the air conditioner is realized.
Optionally, inputting the prediction model according to the spatial information, and outputting the control command corresponding to the spatial information by the prediction model includes: inputting the prediction sub-model according to the spatial information, and outputting the temperature difference condition corresponding to the spatial information by the prediction sub-model; determining a control instruction according to the temperature difference condition; wherein, the prediction submodel is for using multiunit training data, obtains through machine learning training, and every group data in the multiunit training data all includes: the space information and the temperature difference condition corresponding to the space information.
In the prediction submodel, the temperature difference of the same area and different spaces during the air conditioner working is taken into consideration, and the prediction submodel is trained according to the areas with different space sizes and patterns and the temperature difference corresponding to the areas, so that the air conditioner control mode corresponding to the temperature difference of the space sizes and the patterns is determined by adopting the prediction submodel, wherein the air conditioner control mode is used for reducing the temperature difference of different spaces, and the temperature difference of different spaces in the same area can be accurately reduced.
Optionally, the temperature difference condition is a temperature difference of different spaces of the working environment.
When the air conditioner works in different working environments, due to the difference of the position of the air conditioner, the size and the pattern of the space where the air conditioner is located, certain difference of temperature under the action of the air conditioner is inevitably caused. For example, in summer, the air conditioner is used at home to cool, the area of the living room is generally larger than that of the bedroom, and the time for the temperature of the bedroom to reach the target temperature is earlier than that of the living room under the action of the air conditioner. When the living room and the bedroom are cooled simultaneously, the two rooms have temperature difference, namely the temperature difference of different spaces of the working environment where the air conditioner is located.
Optionally, the control instructions include at least one of: adjusting the working temperature of the air conditioner, changing the working mode of the air conditioner, moving the position of the air conditioner and adjusting the air speed of the air conditioner.
The air conditioner control method comprises the steps of generating a corresponding air conditioner control instruction according to the air conditioner and the space information of the working environment, effectively controlling the working of the air conditioner, specifically, adjusting the working temperature of the air conditioner, changing the working mode of the air conditioner, moving the position of the air conditioner, adjusting the air speed of the air conditioner and the like through the control instruction. For example, the air conditioner can reasonably adjust the temperature difference of the area according to the temperature difference generated by different spaces of the same area by moving the position and adjusting the temperature control mode of the air conditioner, such as adjusting the working frequency and the wind speed, so that the intelligent degree of temperature adjustment of the air conditioner is improved, the temperature difference of the whole large-scale place is kept at a reasonable level, and the effect of saving electricity is achieved to a certain extent.
Further, if the air conditioner moves and is placed in other areas, if the air conditioner detects that the air conditioner moves, adjustment is not needed to be performed based on the change of the current space, and the regulation and control mode is restarted under the condition that the stable space size is detected.
Fig. 2 is a schematic structural diagram of an air conditioning control apparatus according to an embodiment of the present invention; as shown in fig. 2, the air conditioning control apparatus includes: an acquisition module 22, a prediction module 24, and a control module 26. The air conditioning control device will be described in detail below.
The acquisition module 22 is used for acquiring the air conditioner and the spatial information of the working environment, wherein the spatial information comprises the size and the pattern of the working environment and the position of the air conditioner in the working space; the prediction module 24 is connected to the obtaining module 22, and configured to input a prediction model according to the spatial information, and output a control instruction corresponding to the spatial information by the prediction model, where the prediction model is obtained by using multiple sets of training data through machine learning training, and each set of data in the multiple sets of training data includes: the spatial information and a control instruction corresponding to the spatial information; and the control module 26 is connected with the prediction module 24 and is used for controlling the air conditioner to work according to the control instruction.
By the air conditioner control device, the air conditioner and the space information of the working environment can be acquired, wherein the space information comprises the size and the pattern of the working environment and the position of the air conditioner in the working space; inputting a prediction model according to spatial information, and outputting a control instruction corresponding to the spatial information by the prediction model, wherein the prediction model is obtained by using a plurality of groups of training data through machine learning training, and each group of data in the plurality of groups of training data comprises: the spatial information and a control instruction corresponding to the spatial information; according to the mode of controlling the air conditioner to work according to the control instruction, the aim of executing different control on the air conditioner according to the size and the layout of different spaces is fulfilled through the prediction model, so that the technical effect of reducing the temperature difference among different spaces is achieved, and the technical problem that the temperature difference among different spaces is large due to the fact that the sizes or the layouts of different spaces are different in the prior art is solved.
When the air conditioner and the spatial information of the working environment are acquired, where the spatial information of the air conditioner is the position of the air conditioner in the space where the air conditioner is located, and the spatial information of the working environment is the size and the configuration of the working environment, it should be noted that the working environment is different spaces in the same area or the same space in the same area, and the same area is an area that can be affected by the air conditioner. For example, the building may be a one-floor space of a building, or a house of a residential building. The space size can be characterized by a specific area, or can be determined by a fixed multiple of the space size, for example, the space size can be a specific area value, or can be one or more standard balcony areas. Wherein, the pattern can be a regular shape pattern, such as a regular rectangle, a square, an equilateral, etc.; or may be irregularly shaped, e.g., trapezoidal, curved, curvilinear, etc.
After a prediction model is built, a plurality of regions with different spatial sizes and patterns are trained through machine learning, wherein training data comprise spatial information and control instructions corresponding to the spatial information. Through the prediction model, the air conditioner control mode corresponding to the space size and the pattern is accurately predicted, and the temperature difference among different spaces can be effectively reduced. The intelligent control of the air conditioner is effectively improved, and electric energy can be effectively saved.
And correspondingly controlling the air conditioner according to the control instruction obtained by the prediction model. The control instruction can realize the adjustment of the working temperature of the air conditioner, the change of the working mode of the air conditioner, the movement of the position of the air conditioner, the adjustment of the air speed of the air conditioner and the like. When the intelligent air conditioner is used in the technical field of intelligent air conditioners, the energy-saving purpose is achieved, a comfortable humanized service is provided, and the user experience is improved.
According to another aspect of the embodiments of the present invention, there is also provided a storage medium storing program instructions, wherein when the program instructions are executed, the apparatus on which the storage medium is located is controlled to execute the method of any one of the above.
According to another aspect of the embodiments of the present invention, there is also provided a processor, configured to execute a program, where the program executes to perform the method of any one of the above.
According to another aspect of the embodiment of the invention, an air conditioner is also provided, and the air conditioner comprises the air conditioner control device.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (8)
1. An air conditioner control method, comprising:
acquiring spatial information of an air conditioner and a working environment, wherein the spatial information comprises the size and the pattern of the working environment and the position of the air conditioner in the working space;
inputting a prediction model according to the spatial information, and outputting a control instruction corresponding to the spatial information by the prediction model, wherein the prediction model is obtained by using multiple sets of training data through machine learning training, and each set of data in the multiple sets of training data comprises: spatial information and a control instruction corresponding to the spatial information;
controlling the air conditioner to work according to the control instruction;
the method for acquiring the space information of the air conditioner and the working environment comprises the following steps:
acquiring an electronic map of the working environment;
acquiring the position of the air conditioner in the electronic map;
inputting a prediction model according to the spatial information, wherein before the prediction model outputs a control instruction corresponding to the spatial information, the method comprises the following steps:
judging whether the acquired space information of the air conditioner and the working environment changes compared with the space information acquired last time;
and under the condition that the spatial information of the air conditioner and the working environment changes, predicting a corresponding control instruction according to the spatial information.
2. The method of claim 1, wherein a prediction model is input according to the spatial information, and outputting a control command corresponding to the spatial information by the prediction model comprises:
inputting a prediction sub-model according to the spatial information, and outputting the temperature difference condition corresponding to the spatial information by the prediction sub-model;
determining the control instruction according to the temperature difference condition;
the predictor model is obtained by using a plurality of groups of training data and training through machine learning, and each group of data in the plurality of groups of training data comprises: the temperature difference condition corresponding to the space information.
3. The method of claim 2, wherein the temperature differential condition is a temperature differential between different spaces of the work environment.
4. The method of any of claims 1 to 3, wherein the control instructions comprise at least one of:
adjusting the working temperature of the air conditioner, changing the working mode of the air conditioner, moving the position of the air conditioner and adjusting the air speed of the air conditioner.
5. An air conditioning control device, characterized by comprising:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring the spatial information of an air conditioner and a working environment, and the spatial information comprises the size and the pattern of the working environment and the position of the air conditioner in the working space;
the prediction module is used for inputting a prediction model according to the spatial information and outputting a control instruction corresponding to the spatial information by the prediction model, wherein the prediction model is obtained by using multiple groups of training data through machine learning training, and each group of data in the multiple groups of training data comprises: spatial information and a control instruction corresponding to the spatial information;
the control module is used for controlling the air conditioner to work according to the control instruction;
the acquisition module is also used for acquiring an electronic map of the working environment; acquiring the position of the air conditioner in the electronic map;
the air conditioner control device is also used for executing the following steps:
inputting a prediction model according to the spatial information, wherein before the prediction model outputs a control instruction corresponding to the spatial information, the method comprises the following steps:
judging whether the acquired space information of the air conditioner and the working environment changes compared with the space information acquired last time;
and under the condition that the spatial information of the air conditioner and the working environment changes, predicting a corresponding control instruction according to the spatial information.
6. A storage medium storing program instructions, wherein the program instructions, when executed, control an apparatus in which the storage medium is located to perform the method of any one of claims 1 to 4.
7. A processor, characterized in that the processor is configured to run a program, wherein the program when running performs the method of any of claims 1 to 4.
8. An air conditioner characterized in that it comprises the air conditioning control device of claim 5.
Priority Applications (1)
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