Intelligent air conditioner operation control system based on data analysis

Abstract

The invention discloses an intelligent air conditioner operation control system based on data analysis, which belongs to the technical field of air conditioner control and comprises an environment analysis module, a target analysis module and a control module. The environment analysis module is used for analyzing the working environment of the air conditioner and establishing an indoor model; supplementing a corresponding air conditioner model in the indoor model according to the air conditioner information; the target analysis module is used for performing action target analysis and displaying an indoor model to a user, and the user determines a target area according to the indoor model; segmenting the target area to obtain unit areas; integrating the position of each unit area and the position of the air conditioner into control analysis data; acquiring a preset temperature of the target area by a user; marking the control analysis data and the preset temperature in the indoor model; determining air conditioner adjusting parameters of each unit area according to the indoor model, and setting an air conditioner control scheme; and the control module is used for controlling the air conditioner according to the air conditioner control scheme.

Description

Technical Field

[0001] The present invention belongs to the technical field of air conditioner control, and specifically relates to an intelligent control system for air conditioner operation based on data analysis. Background Art

[0002] With the rapid development of smart home technology, users' demands for intelligent and personalized indoor environment control are increasing day by day. Traditional air conditioner control systems often adopt a unified temperature setting and are adjusted through mechanical temperature control switches or remote controls. Such a control method has many deficiencies. First of all, it lacks pertinence and cannot accurately control the temperature of specific areas indoors, resulting in a mismatch between the actual usage area of users and the set temperature, affecting comfort and energy consumption efficiency. Secondly, users need to frequently manually adjust the air conditioner temperature, which is cumbersome and inefficient. In addition, comprehensively adjusting the indoor temperature often causes unnecessary resource waste, especially in large spaces or complex house types, and this problem is particularly prominent. Although many current air conditioners are equipped with mobile application software that can realize air conditioner control through the application software, because the control functions of the air conditioner software are basically the same as those of the physical remote control, the utilization rate of the air conditioner software is low; nor can the above problems be solved.

[0003] Based on this, in order to solve the above problems and improve the application effect of the air conditioner software, the present invention provides an intelligent control system for air conditioner operation based on data analysis. Summary of the Invention

[0004] In order to solve the problems existing in the above solutions, the present invention provides an intelligent control system for air conditioner operation based on data analysis.

[0005] The object of the present invention can be achieved through the following technical solutions: An intelligent control system for air conditioner operation based on data analysis, including an environment analysis module, a target analysis module, and a control module; The environment analysis module is used to analyze the working environment of the air conditioner, identify and analyze the indoor map presented to the user, and establish a corresponding indoor model; obtain the air conditioner information of each air conditioner, supplement the corresponding air conditioner model in the indoor model according to each air conditioner information; and connect to each air conditioner according to each air conditioner information.

[0006] The target analysis module is used to perform action target analysis, present the indoor model to the user, and the user determines the target area according to the indoor model; divide the target area to obtain each unit area; Integrate the positions of each unit area and the positions of the air conditioners into control analysis data; obtain the preset temperature of the user for the target area; mark the control analysis data and the preset temperature in the indoor model; Determine the air-conditioning adjustment parameters for each unit area according to the indoor model, and set the air-conditioning control plan according to the air-conditioning adjustment parameters corresponding to each unit area.

[0007] Further, the method for a user to determine a target area in the indoor model includes: Identify the initial marked points marked by the user on the indoor model; identify the indoor attributes of the initial marked points; generate an initial area according to the indoor attributes; Mark the initial area correspondingly on the indoor model. The user makes adjustments according to the displayed initial area, and marks the adjusted initial area as the target area.

[0008] Further, the method for dividing the target area includes: Obtain the adjustment data of the air conditioner corresponding to the target area, identify the position of the target area and the position of the air conditioner, and integrate them into position data; Conduct application simulation according to the adjustment data and the position data to determine the target segmentation plan, and divide the target area according to the target segmentation plan to obtain each unit area.

[0009] Further, the method for obtaining the adjustment data includes: Set each reserve air conditioner, set the action areas for each reserve air conditioner to cool or heat positions at different angles and different distances, and integrate them into the adjustment data of the corresponding reserve air conditioner; Establish a reserve library according to each reserve air conditioner and the corresponding adjustment data; Identify the air-conditioning information, and match the corresponding adjustment data from the reserve library according to the air-conditioning information.

[0010] Further, the method for conducting application simulation according to the adjustment data and the position data includes: Step SA1: Identify the action area corresponding to the target area when the air conditioner is turned on according to the adjustment data, and mark it as the starting area; When the starting area is not less than the target area, the target segmentation plan is not to divide, and the analysis ends; When the starting area is less than the target area, enter step SA2; Step SA2: Perform moving division based on the starting area to obtain each separated area; establish an equivalent judgment model according to the adjustment data; Step SA3: Analyze the starting area and the adjacent separated areas through the equivalent judgment model to obtain the corresponding equivalent judgment value; Step SA4: When there is no equivalent judgment value of 1, mark the starting area as a unit area, and mark the adjacent separated area as the new starting area, and return to step SA3. When there is no starting area, form the target segmentation plan according to each unit area, and end the analysis; When the equivalence judgment value is 1, the separated area with the equivalence judgment value of 1 is merged with the starting area to obtain a merged area; the merged area and the adjacent separated area are analyzed by the equivalence judgment model to obtain the corresponding equivalence judgment value. Step SA5: When there is no equivalence judgment value of 1, mark the merged area as a unit area, mark the adjacent separated area as a new starting area, and return to step SA3. When there is no starting area, form a target segmentation scheme according to each unit area and end the analysis. When the equivalence judgment value is 1, the separated area with the equivalence judgment value of 1 is merged with the merged area to obtain a new merged area; the new merged area and the adjacent separated area are analyzed by the equivalence judgment model to obtain the corresponding equivalence judgment value. Step SA6: Return to step SA5.

[0011] Further, the expression of the equivalence judgment model is: ; In the formula: s is the input data, the output data is the equivalence judgment value DP(s), and the equivalence judgment value is 1 or 0.

[0012] The control module is used to control the air conditioner, obtain the air conditioner control scheme, and control the air conditioner according to the air conditioner control scheme.

[0013] Further, it further includes an effect evaluation module. The effect evaluation module is used to evaluate the air conditioner effect, perform real-time temperature detection on each unit area to obtain the detected temperatures corresponding to each unit area; obtain the preset temperatures corresponding to each detected temperature. According to the formula Calculate the corresponding deviation value. In the formula: PQ is the deviation value; YB is the preset temperature; CB is the detected temperature. Identify the deviation values corresponding to each verification area; identify the detection times corresponding to each deviation value, and generate a corresponding deviation curve according to each detection time. The horizontal axis of the deviation curve is the detection time, and the vertical axis is the deviation value. Perform effect evaluation according to the deviation curve to obtain the corresponding effect evaluation result. The effect evaluation result includes effect abnormality and effect normality.

[0014] Further, the method for performing effect evaluation according to the deviation curve includes: Fit the deviation curve to obtain the corresponding deviation function, and mark the deviation function as HY(t); According to the formula Calculate the corresponding abnormal value. In the formula: PK is the abnormal value; t is the detection time. When the outlier is greater than the threshold value X1, the evaluation effect is abnormal; When the outlier is not greater than the threshold value X1, the evaluation effect is normal.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: Through the mutual cooperation among the environment analysis module, the target analysis module and the control module, intelligent control of the air conditioner is realized according to the user's needs, the resource utilization rate is improved under the condition of meeting the user's usage requirements, and resource waste is reduced; at the same time, the usage rate of the configuration control software is improved, which is convenient for the air conditioner party to transmit information based on the control software; by setting the effect evaluation module, full utilization of the air conditioner data is realized, abnormal situations in the process of using the air conditioner are discovered in time, and it is convenient for the user to handle them in time. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention, and those of ordinary skill in the art can also obtain other drawings based on these drawings without creative efforts.

[0017] Figure 1 It is a block diagram of the principle of the present invention; Figure 2 It is an example diagram of the indoor view of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The following will clearly and completely describe the technical solutions of the present invention in conjunction with the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0019] As Figures 1 to 2 shown, the intelligent control system for air conditioner operation based on data analysis includes an environment analysis module, a target analysis module, a control module and an effect evaluation module; The environment analysis module is used to analyze the working environment of the air conditioner, obtain the floor plan corresponding to the user's home, and mark it as the indoor view, as Figure 2As shown; through the indoor map with corresponding size marks, the existing model generation technology is used to generate the corresponding two-dimensional model, which is marked as the indoor model. A three-dimensional model is the best, but in order to facilitate identification and establishment, a two-dimensional indoor model is generally generated based on a plan view; according to the air-conditioning information such as the location and model of each air-conditioner, the air-conditioning model of the corresponding air-conditioner is added to the indoor model to indicate its location and other information; according to the information of each air-conditioner, it is paired and connected with each air-conditioner, and the air-conditioning can be controlled by software later.

[0020] The target analysis module is used to perform action target analysis. The action target is the target area where the air conditioning is required. When the user needs to use the air conditioner, the software is opened through the mobile phone, and the indoor model is displayed to the user. The user determines the target area based on the indoor model. The target area is the area where the user expects the air conditioning to be effective. Segment the target area to obtain each unit area; Integrate the location of each unit area and the location of the air conditioner into control analysis data; obtain the user's preset temperature for the target area, that is, the temperature input by the user, such as 25°C; mark the control analysis data and the preset temperature in the indoor model; The air-conditioning adjustment parameters of each unit area are determined according to the indoor model, including parameters such as temperature, angle, and wind speed, so that the perceived temperature in the unit area is the preset temperature, which is specifically determined based on the analysis of the air-conditioning performance; illustratively, the platform analyzes each reserve air-conditioner in advance to determine its adjustment performance, and then determines the impact of the air-conditioning on the corresponding unit area under the current spatial conditions; specifically, the air-conditioning adjustment parameters can be determined based on existing artificial intelligence technologies, such as establishing an intelligent model based on neural networks, and performing analysis through the intelligent model.

[0021] Set the air conditioning control plan according to the air conditioning adjustment parameters corresponding to each unit area.

[0022] In one embodiment, the method for the user to determine the target area according to the indoor model is: the user directly manually marks the indoor model.

[0023] In another embodiment, since determining the target area according to the above embodiment will have a large error and require the user to spend more effort, this embodiment adopts the following method: The user clicks on the indoor model, which means that it is not necessary to mark the entire target area completely, such as clicking on a sofa, a bed, a dining table, etc.; mark the clicked position as the initial marking point; identify the indoor attributes of the initial marking point, such as the attributes of a sofa, a bed, a dining table, the floor tiles in the living room, etc.; generate an initial area according to the indoor attributes. For example, for a sofa, the initial area is the area corresponding to the sofa and its surrounding area; for a dining table, it is the area corresponding to the dining table and its surrounding area; for the floor tiles in the living room, it is a preset area, such as the entire living room or a preset area of the living room activity area centered on this point. Specifically, it can be preset by the platform according to usage habits, and the user can also adjust it during use to form the initial areas corresponding to each indoor attribute.

[0024] Mark the initial area on the indoor model accordingly. The user makes corresponding adjustments according to the displayed initial area and has the functions of the previous embodiment, that is, the user can adjust the area based on the initial area, such as increasing or decreasing, to form the target area.

[0025] The method for dividing the target area includes: Obtain the adjustment data corresponding to the air conditioner in the target area, identify the positions of the target area and the air conditioner, and integrate them into position data; perform application simulation according to the adjustment data and the position data to determine the target segmentation plan, and divide the target area according to the target segmentation plan to obtain each unit area.

[0026] The method for obtaining the adjustment data includes: The platform aggregates the air conditioners that meet the application and marks them as reserve air conditioners, such as various types of air conditioners of common major brands, or various models of the home brand, etc.; Obtain the size of the cooling or heating action area of each reserve air conditioner at different angles and different distances. The action area is set according to a certain cooling or heating effect standard, such as the best effect, etc.; determine it through testing, public data, etc., and integrate and set the adjustment data corresponding to each reserve air conditioner; Establish a reserve library according to each reserve air conditioner and the corresponding adjustment data; Identify the air conditioner information and match the corresponding adjustment data from the reserve library according to the air conditioner information.

[0027] The method for performing application simulation according to the adjustment data and the position data includes: Step SA1: Identify the action area corresponding to the air conditioner when it is turned on in the target area according to the adjustment data, and mark it as the starting area, that is, match according to the angle corresponding to the air conditioner when it is just turned on to determine its action area in the target area; When the starting area is not less than the target area, that is, the starting area can include the target area, then there is no need to perform segmentation, and the target segmentation plan is not to segment; it can act directly; When the starting area is smaller than the target area, in order to achieve a good experience in the target area, subsequent operations such as air swing control are required; proceed to step SA2; Step SA2: According to the air swing principle of the air conditioner, divide the area by moving with the starting area as the reference to obtain each separated area. That is, because the distance, swing angle, etc. can be used to calculate the corresponding affected area, compare it with the previous area to determine the increased area corresponding to this swing. When this side ends (all target areas on this side are completely divided), return to swing. For the areas that have been divided, there is no need to re-divide them until new divided areas are formed on the other side of the starting area, and so on, to form each separated area; Establish an equivalent judgment model based on the adjustment data. The equivalent judgment model is used to judge whether the air conditioner's effect is the same in different position areas. If the air conditioner effects are the same, it is considered to meet the equivalent judgment requirements. According to the adjustment data, various position areas can be simulated and determined. Combine the actual indoor area and size to limit the number of position areas. Manually mark each position area to form a training set. Train through the training set to achieve the effect judgment according to the equivalent judgment model. It is also possible to judge whether the air conditioner's effects on different positions are the same based on other existing technologies; the expression of the equivalent judgment model is ; In the formula: s is the input data, and the input data is the position area to be compared, such as each separated area and the starting area; the output data is the equivalent judgment value DP(s); Step SA3: Analyze the starting area and the adjacent separated areas through the equivalent judgment model. If there are two, both are analyzed separately; if there is one, only one is analyzed to obtain the corresponding equivalent judgment value; Step SA4: When there is no equivalent judgment value of 1, mark the starting area as a unit area, mark the adjacent separated area as a new starting area, and return to step SA3; When there is an equivalent judgment value of 1, merge the separated area with an equivalent judgment value of 1 and the starting area to obtain a merged area; analyze the merged area and the adjacent separated areas through the equivalent judgment model to obtain the corresponding equivalent judgment value; Step SA5: When there is no equivalent judgment value of 1, mark the merged area as a unit area, mark the adjacent separated area as a new starting area, and return to step SA3. When there is no starting area, end the analysis and form a target segmentation plan according to each unit area; When there is an equivalent judgment value of 1, merge the separated area with an equivalent judgment value of 1 and the merged area to obtain a new merged area; analyze the new merged area and the adjacent separated areas through the equivalent judgment model to obtain the corresponding equivalent judgment value; Step SA6: Return to step SA5.

[0028] The control module is used to control the air conditioner, obtain the air conditioner control scheme, and control the air conditioner according to the air conditioner control scheme.

[0029] Through the mutual cooperation among the environment analysis module, the target analysis module and the control module, the intelligent control of the air conditioner according to the user's needs is realized, the resource utilization rate is improved while meeting the user's usage requirements, and the resource waste is reduced; at the same time, the usage rate of the configuration control software is improved, which is convenient for the air conditioner party to transmit information based on the control software.

[0030] The effect evaluation module is used to evaluate the effect of the air conditioner. Since the preset temperature of each unit area can be determined based on the above embodiments, on the premise of the above data, when the actual temperature is detected through a mobile phone device or the like, the actual effect of the air conditioner can be analyzed, and the effect analysis can be realized without installing monitoring devices, various sensors and other devices at home; the analysis process is as follows: Perform real-time temperature detection on each unit area to obtain the detected temperatures corresponding to the unit areas; that is, one detected temperature is retained for each unit area, and the unit areas that cannot be detected are not detected. Generally, the temperature of the corresponding unit area is detected according to the location of the mobile phone; the unit areas with detected temperatures are marked as verification areas; as the user moves or other situations occur, other unit areas may become verification areas, and as long as they are within the process of this air conditioner startup, they can all participate in the evaluation, that is, the data at the same moment is not required; Obtain the preset temperature corresponding to each detected temperature, and according to the formula Calculate the corresponding deviation value; in the formula: PQ is the deviation value; YB is the preset temperature; CB is the detected temperature; Identify the deviation values corresponding to each verification area; identify the detection times corresponding to each deviation value, and generate a corresponding deviation curve according to each detection time. The horizontal axis is the detection time, and the vertical axis is the deviation value, that is, all the deviation values are integrated into the same deviation curve according to the detection order, and the order of any detection time can be arbitrary; Perform effect evaluation according to the deviation curve to obtain the corresponding effect evaluation result. The effect evaluation result includes effect abnormality and effect normality. The effect abnormality may be caused by the doors and windows not being closed, or the air conditioner's cooling or heating abnormality, etc.

[0031] The method for performing effect evaluation according to the deviation curve includes: Fit the deviation curve to obtain the corresponding deviation function, and mark the deviation function as HY(t); According to the formula Calculate the corresponding abnormal value; in the formula: PK is the abnormal value; t is the detection time; When the abnormal value is greater than the threshold X1, evaluate that the effect is abnormal; When the abnormal value is not greater than the threshold X1, evaluate that the effect is normal.

[0032] By setting up an effect evaluation module, the full utilization of air conditioner data is realized, and abnormal situations during the use of the air conditioner can be detected in a timely manner, which is convenient for users to handle in a timely manner.

[0033] The above formulas are all calculated by removing the dimension and taking their numerical values. The formula is a formula obtained by collecting a large amount of data for software simulation to be the one closest to the actual situation. The preset parameters and preset thresholds in the formula are set by those skilled in the art according to the actual situation or obtained by simulating a large amount of data.

[0034] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. The intelligent control system for air conditioning operation based on data analysis is characterized by: It includes environment analysis module, target analysis module and control module; The environment analysis module is used to analyze the working environment of the air conditioner, identify and analyze the indoor picture displayed by the user, and establish a corresponding indoor model; obtain the air conditioning information of each air conditioner, and supplement the corresponding air conditioning model in the indoor model according to each air conditioning information; and connect with each air conditioner according to each air conditioning information; The target analysis module is used to perform target analysis, display the indoor model to the user, and the user determines the target area based on the indoor model; segment the target area to obtain each unit area; Integrate the position of each unit area and the position of the air conditioner into control analysis data; obtain the user's preset temperature for the target area; and mark the control analysis data and the preset temperature in the indoor model; Determine the air conditioning adjustment parameters of each unit area according to the indoor model, and set the air conditioning control scheme according to the air conditioning adjustment parameters corresponding to each unit area; The control module is used to control the air conditioner, obtain the air conditioner control scheme, and control the air conditioner according to the air conditioner control scheme.

2. The air conditioning operation intelligent control system based on data analysis according to claim 1 is characterized in that: Methods for users to determine the target area based on the indoor model include: Identify initial marking points marked by a user on an indoor model; identify indoor properties of the initial marking points; generate an initial area according to the indoor properties; The initial area is marked accordingly on the indoor model, and the user makes adjustments according to the displayed initial area, and the adjusted initial area is marked as the target area.

3. The air conditioning operation intelligent control system based on data analysis according to claim 1 is characterized in that: Methods for segmenting the target area include: Acquire adjustment data of the air conditioner corresponding to the target area, identify the location of the target area and the location of the air conditioner, and integrate them into location data; An application simulation is performed based on the adjustment data and the position data, a target segmentation scheme is determined, and the target area is segmented according to the target segmentation scheme to obtain each unit area.

4. The air conditioning operation intelligent control system based on data analysis according to claim 3 is characterized in that: Methods for obtaining adjustment data include: Set up each reserve air conditioner, set up the cooling or heating action area of ​​each reserve air conditioner at different angles and distances, and integrate them into adjustment data of the corresponding reserve air conditioner; Establish a reserve library based on each reserve air conditioner and the corresponding adjustment data; Identify the air conditioning information and match the corresponding adjustment data from the reserve library according to the air conditioning information.

5. The air conditioning operation intelligent control system based on data analysis according to claim 3 is characterized in that: Methods for applying simulation based on adjustment data and position data include: Step SA1: identifying the corresponding action area on the target area when the air conditioner is turned on according to the adjustment data, and marking it as the starting area; When the starting area is not smaller than the target area, the target segmentation scheme is no segmentation and the analysis ends; When the starting area is smaller than the target area, proceed to step SA2; Step SA2: Perform mobile division based on the starting area to obtain each separated area; establish an equivalent judgment model based on the adjustment data; Step SA3: Analyze the starting area and the adjacent separation area through the equivalence judgment model to obtain corresponding equivalence judgment values; Step SA4: When no equivalent judgment value is 1, the starting area is marked as a unit area, and the adjacent separation area is marked as a new starting area, and the process returns to step SA3. When there is no starting area, a target segmentation scheme is formed according to each unit area, and the analysis ends. When the equivalent judgment value is 1, the separated area with the equivalent judgment value of 1 is merged with the starting area to obtain a merged area; the merged area and the adjacent separated areas are analyzed by the equivalent judgment model to obtain the corresponding equivalent judgment value; Step SA5: When no equivalent judgment value is 1, the merged area is marked as a unit area, and the adjacent separated area is marked as a new starting area, and the process returns to step SA3. When there is no starting area, a target segmentation scheme is formed according to each unit area, and the analysis ends. When the equivalent judgment value is 1, the separated area with the equivalent judgment value of 1 is merged with the merged area to obtain a new merged area; the new merged area and the adjacent separated area are analyzed by the equivalent judgment model to obtain the corresponding equivalent judgment value; Step SA6: Return to step SA5.

6. The air conditioning operation intelligent control system based on data analysis according to claim 5 is characterized in that: The expression of the equivalent judgment model is: ； Where: s is the input data, the output data is the equivalence judgment value DP(s), and the equivalence judgment value is 1 or 0.

7. The air conditioning operation intelligent control system based on data analysis according to claim 1 is characterized in that: It also includes an effect evaluation module, which is used to evaluate the air conditioning effect, perform real-time temperature detection on each unit area, obtain each detected temperature corresponding to the unit area; and obtain the preset temperature corresponding to each detected temperature; According to the formula Calculate the corresponding deviation value; Where: PQ is the deviation value; YB is the preset temperature; CB is the detection temperature; Identify the deviation value corresponding to each verification area; identify the detection time corresponding to each deviation value, and generate a corresponding deviation curve according to each detection time, wherein the horizontal axis of the deviation curve is the detection time and the vertical axis is the deviation value; The effect evaluation is performed according to the deviation curve to obtain corresponding effect evaluation results, which include abnormal effects and normal effects.

8. The air conditioning operation intelligent control system based on data analysis according to claim 7 is characterized in that: Methods for evaluating effects based on deviation curves include: Fit the deviation curve to obtain the corresponding deviation function, and mark the deviation function as HY(t); According to the formula Calculate the corresponding outlier value; Where: PK is the abnormal value; t is the detection time; When the outlier value is greater than the threshold X1, the evaluation effect is abnormal; When the outlier value is not greater than the threshold X1, the evaluation effect is normal.

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