Air conditioner, map data generation method thereof, and computer readable storage medium

Abstract

The application discloses a kind of map data generation methods applied to air conditioner, this method includes: obtaining the target space position information of different positions in the space of air conditioner and its corresponding air detection data;The air detection data includes the sub-detection data corresponding to a plurality of air evaluation parameters respectively;Determine the first map position information corresponding to each target space position information;According to each first map position information and its corresponding a plurality of sub-detection data generates target one-dimensional array, obtains the air map data of the space of air conditioner.The application also discloses an air conditioner and computer readable storage medium.The application aims at reducing the redundancy of data in air conditioner, improves the efficiency of accuracy of air conditioner operation decision.

Description

Technical Field

[0001] This invention relates to the field of air conditioning technology, and more particularly to a map data generation method, an air conditioner, and a computer-readable storage medium. Background Technology

[0002] With the development of economy and technology, air conditioners are being used more and more widely, and their performance is becoming more and more diversified. At present, air conditioners generally need to detect different air data in different locations in the environment during operation, such as temperature, humidity, wind speed, and pollutant concentration, in order to control the operation of the air conditioner based on the detected data.

[0003] However, currently, air conditioners generally detect and process air data from different locations and dimensions independently, recording and processing it as multiple discrete arrays. This can easily lead to data redundancy when there are many measurement points or many dimensions of air that need to be detected. Furthermore, discrete data is difficult to reflect the overall air quality of the indoor space, affecting the efficiency and accuracy of subsequent air conditioning operation decisions. Summary of the Invention

[0004] The main objective of this invention is to provide a map data generation method, an air conditioner, and a computer-readable storage medium, which aims to reduce data redundancy in the air conditioner and improve the efficiency and accuracy of air conditioner operation decisions.

[0005] To achieve the above objectives, the present invention provides a map data generation method for use in air conditioners, the map data generation method comprising the following steps:

[0006] Acquire target spatial location information and corresponding air detection data at different locations within the operating space of the air conditioner; the air detection data includes sub-detection data corresponding to various air evaluation parameters.

[0007] Determine the first map location information corresponding to each of the target spatial location information;

[0008] Based on each of the first map location information and its corresponding multiple sub-detection data, a one-dimensional array of targets is generated to obtain air map data of the air conditioner's operating space.

[0009] Optionally, the step of generating a one-dimensional array of targets based on each of the first map location information and its corresponding multiple sub-detection data includes:

[0010] Obtain an initial one-dimensional array, which includes multiple sub-one-dimensional arrays. Each sub-one-dimensional array represents a pixel unit of the air map data. The sub-one-dimensional array includes first data and second data. The first data includes preset map location information of the corresponding pixel unit. The second data includes the initial values ​​of the various air evaluation parameters corresponding to the spatial location represented by the corresponding pixel unit.

[0011] Determine the target array as the sub-one-dimensional array containing each of the first map location information matching the preset map location information;

[0012] In the initial one-dimensional array, the initial values ​​in the corresponding target array are updated according to the multiple sub-detection data corresponding to each of the first map location information, so as to obtain the target one-dimensional array.

[0013] Optionally, the initial value is the data of the corresponding air assessment parameter detected before the current time, or the initial value is a preset value, which indicates that there is no detection data for the corresponding air assessment parameter.

[0014] Optionally, the step of generating a one-dimensional array based on multiple spatial location information and various sub-detection data corresponding to each spatial location information to obtain air map data of the air conditioner's operating space includes:

[0015] When the air detection module corresponding to the air detection data is fixed within the operating space of the air conditioner, a one-dimensional sparse array is generated based on multiple spatial location information and multiple sub-detection data corresponding to each spatial location information to obtain air map data of the operating space of the air conditioner.

[0016] Optionally, the data format of the one-dimensional array is ProtoBuf or JSON.

[0017] Optionally, the step of obtaining target spatial location information and corresponding air detection data at different locations within the operating space of the air conditioner includes:

[0018] Acquire initial data corresponding to multiple detection locations within the operating space of the air conditioner. The initial data includes spatial location information of the corresponding detection locations and sub-data corresponding to the various air evaluation parameters obtained by detection.

[0019] Determine any two adjacent positions among the plurality of detection positions as the first position and the second position;

[0020] Based on the preset map resolution, the spatial location information of the first location, and the spatial location information of the second location, it is determined whether the map locations corresponding to the first location and the second location belong to the same pixel unit in the air map data.

[0021] If so, then the initial data corresponding to one of the first position and the second position is determined as the target spatial location information and its corresponding air detection data;

[0022] If not, the initial data corresponding to the first position and the initial data corresponding to the second position shall be used as the target spatial location information and the corresponding air detection data for different positions.

[0023] Optionally, the step of obtaining target spatial location information and corresponding air detection data at different locations within the operating space of the air conditioner includes:

[0024] Control the air conditioner to transmit the first wireless signal;

[0025] The system receives detection data sent by air detection modules at different locations and signal characteristic values ​​of a second wireless signal, wherein the second wireless signal is the received signal formed by the first wireless signal in the air detection module.

[0026] Based on each signal feature value, the target spatial location information of the corresponding air detection module is determined, and the detection data is determined to be the air detection data corresponding to the target spatial location information.

[0027] Optionally, the step of determining the target spatial location information of the corresponding air detection module based on each signal feature value includes:

[0028] Calculate the polar coordinates of the location of the air detection module corresponding to each of the signal feature values;

[0029] The target spatial location information is determined based on the polar coordinates described above.

[0030] Optionally, the step of determining the target spatial location information of the current position of the air detection module based on the polar coordinates includes:

[0031] When the air conditioner belongs to the first type, the polar coordinates are used as the target spatial location information of the corresponding position;

[0032] When the air conditioner belongs to the second type, the result of performing coordinate transformation operation on each polar coordinate according to the angle between the air conditioner and the wall of the air conditioner's operating space is used as the target spatial position information of the corresponding position.

[0033] The first type is an air conditioner installed on the wall of the space where the air conditioner operates, and the second type is an air conditioner installed at an angle to the wall of the space where the air conditioner operates.

[0034] Optionally, the first wireless signal is transmitted through at least two antennas on the air conditioner, and the step of calculating the polar coordinates of the location of the corresponding air detection module based on each signal feature value includes:

[0035] Calculate the first distance between each of the at least two antennas and the air detection module based on the signal characteristic value and the preset distance between the at least two antennas;

[0036] The polar coordinates corresponding to the signal feature value are calculated based on the first distance corresponding to each of the at least two antennas and the preset distance.

[0037] In addition, to achieve the above objectives, this application also proposes an air conditioner, the air conditioner comprising: a memory, a processor, and a map data generation program stored in the memory and executable on the processor, wherein the map data generation program, when executed by the processor, implements the steps of the map data generation method as described in any of the preceding claims.

[0038] In addition, to achieve the above objectives, this application also proposes a computer-readable storage medium storing a map data generation program, which, when executed by a processor, implements the steps of the map data generation method as described in any of the preceding claims.

[0039] This invention proposes a map data generation method for air conditioners. After detecting multi-dimensional air quality data at different locations within the air conditioner's operating space, the method generates air map data in the form of a one-dimensional array, containing air data from different locations and dimensions. In this process, the air data from different locations and dimensions is no longer processed as multiple discrete arrays, but rather integrated using a one-dimensional array. This one-dimensional array allows for data compression, effectively reducing data redundancy and improving the efficiency of subsequent air conditioning decisions. Furthermore, the one-dimensional array integrating air data from different locations and dimensions accurately reflects the overall air quality of the indoor space, providing a comprehensive and accurate basis for subsequent air conditioner control, thereby improving the efficiency and accuracy of air conditioning operation decisions. Attached Figure Description

[0040] Figure 1 This is a schematic diagram of the hardware structure involved in the operation of an embodiment of the air conditioner of the present invention;

[0041] Figure 2 This is a flowchart illustrating an embodiment of the map data generation method of the present invention;

[0042] Figure 3 This is a flowchart illustrating another embodiment of the map data generation method of the present invention;

[0043] Figure 4 This is a flowchart illustrating another embodiment of the map data generation method of the present invention;

[0044] Figure 5 This is a flowchart illustrating another embodiment of the map data generation method of the present invention.

[0045] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0046] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0047] The main solution of this invention is: to obtain target spatial location information and corresponding air detection data at different locations within the operating space of the air conditioner; the air detection data includes sub-detection data corresponding to various air evaluation parameters; to determine the first map location information corresponding to each target spatial location information; and to generate a target one-dimensional array based on each first map location information and its corresponding multiple sub-detection data to obtain air map data of the operating space of the air conditioner.

[0048] In current technology, air conditioners typically detect and process air data from different locations and dimensions independently, recording and processing it as multiple discrete arrays. This can easily lead to data redundancy when there are many measurement points or many dimensions of air to be detected. Furthermore, the discrete data makes it difficult to reflect the overall air quality of the indoor space, affecting the efficiency and accuracy of subsequent air conditioning operation decisions.

[0049] The present invention provides the above-mentioned solution, which aims to reduce data redundancy in air conditioners and improve the efficiency and accuracy of air conditioner operation decisions.

[0050] This invention provides an air conditioner. Specifically, it can be an air conditioner that is fixed in an indoor environment or a portable air conditioner.

[0051] In this embodiment of the invention, reference is made to Figure 1 The air conditioner includes a control device 1 and an air detection module 2 connected to the control device 1. The air detection module 2 is specifically used to detect data corresponding to multiple air evaluation parameters, including but not limited to temperature, humidity, particulate matter, wind speed, formaldehyde, etc.

[0052] The air detection module 2 can be installed on the air conditioner body or independently on the outside of the air conditioner body.

[0053] In one implementation of this embodiment, the air detection module 2 is a module with autonomous movement function. The air detection module 2 can move within the working space of the air conditioner and detect air data at different locations.

[0054] In another implementation of this embodiment, there may be multiple air detection modules 2, which are distributed and fixed at different positions within the working space of the air conditioner.

[0055] Specifically, refer to Figure 1 The control device 1 includes a processor 1001 (e.g., CPU), a memory 1002, etc. The memory 1002 can be a high-speed RAM or a stable memory (non-volatile memory), such as a disk storage device. Optionally, the memory 1002 can also be a storage device independent of the aforementioned processor 1001.

[0056] Those skilled in the art will understand that Figure 1 The device structure shown does not constitute a limitation on the device and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0057] like Figure 1 As shown, the memory 1002, which is a computer-readable storage medium, may include a map data generation program. Figure 1 In the apparatus shown, the processor 1001 can be used to call the map data generation program stored in the memory 1002 and execute the relevant steps of the map data generation method in the following embodiments.

[0058] This invention also provides a map data generation method, applied to the aforementioned air conditioner.

[0059] Reference Figure 2 This application proposes an embodiment of a map data generation method. In this embodiment, the map data generation method includes:

[0060] Step S10: Obtain target spatial location information and corresponding air detection data at different locations within the operating space of the air conditioner; the air detection data includes sub-detection data corresponding to various air evaluation parameters.

[0061] Air quality data can be detected by either a mobile air quality detection module or an array of fixed air quality detection modules.

[0062] The types of various air quality assessment parameters can be set according to the actual operating needs of the air conditioner, including but not limited to some or all of temperature, humidity, particulate matter, carbon dioxide concentration, wind speed, and formaldehyde. For example, when multiple air quality assessment parameters include temperature, humidity, particulate matter, wind speed, and formaldehyde, the sub-detection data corresponding to the air data detected at each location will include temperature detection data, humidity detection data, particulate matter detection data, wind speed detection data, and formaldehyde detection data, respectively.

[0063] The different locations here can be any multiple locations in space, or multiple locations that meet preset conditions.

[0064] Specifically, in this embodiment, a preset coordinate system is established for the operating space of the air conditioner, and the target spatial location information is specifically the coordinates of the corresponding location in the preset coordinate system. In other embodiments, the target spatial location information may also include the distance and / or direction of the corresponding location relative to the air conditioner.

[0065] Step S20: Determine the first map location information corresponding to each of the target spatial location information;

[0066] Specifically, the conversion relationship between spatial location and map location can be determined based on pre-set map parameters (such as resolution, scale, map length, map height, etc.), and the target spatial location information can be converted into first map location information according to the determined conversion relationship.

[0067] Step S30: Generate a one-dimensional array of targets based on each of the first map location information and its corresponding multiple sub-detection data to obtain air map data of the air conditioner's operating space.

[0068] Specifically, the first map location information and various sub-detection data are combined according to the pre-set array rules to form a target one-dimensional array.

[0069] Alternatively, an initial one-dimensional array containing location information of different locations within the air conditioner's operating space can be obtained. The target one-dimensional array is then obtained by updating the initial one-dimensional array based on the location information of the first map and its corresponding multiple sub-detection data.

[0070] Furthermore, to ensure the efficiency of the analysis when the air map data is subsequently applied to air conditioning operation decisions, the data format of the one-dimensional array is ProtoBuf or JSON format.

[0071] Furthermore, to facilitate the rapid retrieval of necessary data from the air quality map data during subsequent air conditioner decision-making, the air quality map data, in addition to the target one-dimensional array, may also include map width x, map height y, map resolution r, and data dimension n, where the data dimension n specifically represents the number of air quality evaluation parameters. x and y are in pixel units in the air quality map, and the map resolution is in meters. In this embodiment, the map resolution ranges from 0.2m to 1m.

[0072] This invention proposes a map data generation method. After detecting multi-dimensional air quality data at different locations within the operating space of an air conditioner, the method generates air map data containing air data of different locations and dimensions in the form of a one-dimensional array. In this process, the air data of different locations and dimensions are no longer processed as multiple discrete arrays, but are integrated in the form of a one-dimensional array. The resulting one-dimensional array can compress the data, effectively reducing data redundancy and improving the efficiency of subsequent air conditioning decisions. Furthermore, the one-dimensional array integrating air data of different locations and dimensions in the space can accurately reflect the overall air quality of the indoor space, providing a comprehensive and accurate decision-making basis for subsequent air conditioner control, thereby improving the efficiency and accuracy of air conditioning operation decisions.

[0073] Furthermore, based on the above embodiments, another embodiment of the map data generation method of this application is proposed. In this embodiment, reference is made to... Figure 3 The step of generating a one-dimensional array of targets based on each of the first map location information and its corresponding multiple sub-detection data includes:

[0074] Step S31: Obtain an initial one-dimensional array, which includes multiple sub-one-dimensional arrays. Each sub-one-dimensional array represents a pixel unit of the air map data. The sub-one-dimensional array includes first data and second data. The first data includes preset map location information of the corresponding pixel unit. The second data includes the initial values ​​of the various air evaluation parameters corresponding to the spatial location represented by the corresponding pixel unit.

[0075] Specifically, map data can be pre-set using n*m pixel units, where n and m are both greater than 1. The values ​​of n and m are determined based on the pre-set map height and width. Pre-set map location information is identified using pixel units, with a pre-set origin as the reference point. The column and row numbers of the pixel units are used as the horizontal and vertical coordinates of the pre-set map location information, respectively.

[0076] Specifically, each air quality assessment parameter has a corresponding initial value, meaning the number of initial values ​​included in the second data is the same as the number of air quality assessment parameters. The initial values ​​corresponding to the various air quality assessment parameters in the second data are arranged in a first preset order within the initial one-dimensional array.

[0077] The first and second data in each sub-one-dimensional array can be arranged sequentially or alternately according to a preset rule. Specifically, the first data may include a preset map location information, which is sequentially concatenated with the second data to form a sub-one-dimensional array; or, the first data may include a number of preset map location information equal to the number of air quality assessment parameters, with each preset map location information concatenated with the initial data corresponding to one type of air quality assessment parameter to form a sub-data group, and then multiple sub-data groups are arranged in a first preset order to form a sub-one-dimensional array. For example, if the preset map location information is (x, y), and the initial values ​​of the five air quality assessment parameters included in the second data are (a, b, c, d, e), then the data arrangement of each sub-one-dimensional array can be (x, y, a, b, c, d, e), or (x, y, a, x, y, b, x, y, c, x, y, d, x, y, e).

[0078] Multiple sub-one-dimensional data in the initial one-dimensional array can be arranged in a second preset order. For example, multiple initial one-dimensional arrays can be arranged in ascending or descending order of preset map location information in the initial one-dimensional array.

[0079] Wherein, the initial value is the data of the corresponding air quality assessment parameter detected before the current time, or the initial value is a preset value, which indicates that there is no detection data for the corresponding air quality assessment parameter. Specifically, when no air quality detection data is obtained in any space, all initial values ​​in the initial one-dimensional array can be preset values ​​(e.g., 0); when air quality detection data is obtained for some locations within the space represented by the map, the initial values ​​in the sub-one-dimensional array corresponding to the locations where no air quality detection data has been obtained are preset values, and the initial values ​​in the sub-one-dimensional array corresponding to the locations where air quality detection data has been obtained are the detection values ​​of the corresponding air quality assessment parameters in the air quality detection data at that location.

[0080] Step S32: Determine the target array as the sub-one-dimensional array where each of the first map location information matches the preset map location information;

[0081] Specifically, the first map location information can be map coordinates. A preset set of map coordinates for all location points in the pixel unit corresponding to the preset map location information can be predetermined. The sub-one-dimensional array containing the preset map location information corresponding to the preset map coordinate set is the target array. Each piece of first map location information can correspond to a specific target array.

[0082] Step S33: In the initial one-dimensional array, update each initial value in the corresponding target array according to the multiple sub-detection data corresponding to each first map location information to obtain the target one-dimensional array.

[0083] Specifically, each initial value in the target array is replaced with the sub-detection data of the corresponding type of air quality assessment parameter in the first map location information, and the initial one-dimensional array after updating all target arrays is used as the target one-dimensional array.

[0084] In this embodiment, generating a target one-dimensional array in the above manner ensures that the generated target one-dimensional array accurately represents the air quality detection status within the air conditioner's operating space, thereby reducing the amount of data while providing a comprehensive and accurate decision-making basis for subsequent air conditioner control.

[0085] Furthermore, based on any of the above embodiments, step S30 may include: when the air detection module corresponding to the air detection data is fixed within the operating space of the air conditioner, generating a one-dimensional sparse array based on multiple spatial location information and multiple sub-detection data corresponding to each spatial location information to obtain air map data of the operating space of the air conditioner. Specifically, step S30 includes steps S31 to S33, where the result obtained by replacing each initial value in the target array with the sub-detection data of the corresponding type of air evaluation parameter in the first map location information can be used as a pending array. Data in other sub-one-dimensional arrays in the pending array whose initial values ​​are preset values ​​are considered valid data. The pending array is compressed according to the determined valid data and the preset generation rules of the sparse array, and the compressed one-dimensional sparse array is used as air map data.

[0086] In this embodiment, the air detection data in space is characterized by a one-dimensional sparse array, which helps to further reduce data redundancy and improve the efficiency of subsequent air map data for air conditioning operation decisions.

[0087] Furthermore, based on any of the above embodiments, another embodiment of the map data generation method of this application is proposed. In this embodiment, reference is made to... Figure 4 Step S10 includes:

[0088] Step S101: Obtain initial data corresponding to multiple detection locations within the operating space of the air conditioner. The initial data includes spatial location information of the corresponding detection locations and sub-data corresponding to the various air evaluation parameters obtained from the detection.

[0089] Specifically, air detection modules can be fixedly installed at multiple detection locations, and data from various air evaluation parameters detected by the air detection modules can be used as sub-data here.

[0090] Alternatively, the movable air detection module can be controlled to move within the working space of the air conditioner, and the data detected by the air detection module at multiple detection locations along the movement path can be obtained to obtain the sub-data here.

[0091] Specifically, in this embodiment, a preset coordinate system is established for the operating space of the air conditioner, and the spatial position information specifically refers to the coordinates of the corresponding detection position in the preset coordinate system. In other embodiments, the spatial position information may also include the distance and / or direction of the corresponding detection position relative to the air conditioner.

[0092] The number of detected locations here is greater than or equal to the number of locations represented by the target spatial location information mentioned above.

[0093] Step S102: Determine any two adjacent positions among the plurality of detection positions as the first position and the second position;

[0094] Step S103: Determine whether the map positions corresponding to the first position and the second position belong to the same pixel unit in the air map data based on the preset map resolution, the spatial position information of the first position and the spatial position information of the second position.

[0095] If yes, proceed to step S104; otherwise, proceed to step S105.

[0096] In this embodiment, the distance between the first and second locations can be calculated based on the spatial location information of the first and second locations. When the distance is less than a preset map resolution, it can be determined that the map locations corresponding to the first and second locations belong to the same pixel unit; when the distance is greater than the preset map resolution, it can be determined that the map locations corresponding to the first and second locations do not belong to the same pixel unit.

[0097] In other embodiments, the distance between the first and second locations can be calculated based on the spatial location information of the first location and the spatial location information of the second location. The difference between the distance and the preset map resolution can be determined. When the difference is less than a preset threshold, it can be determined that the map locations corresponding to the first and second locations belong to the same pixel unit. When the difference is greater than or equal to the preset threshold, it can be determined that the map locations corresponding to the first and second locations do not belong to the same pixel unit.

[0098] Step S104: Determine the initial data corresponding to one of the first position and the second position as the target spatial position information and its corresponding air detection data;

[0099] Specifically, the spatial location information in the initial data of the first location can be used as one of the aforementioned multiple target spatial location information, and the sub-data in the initial data of the first location can be used as one of the aforementioned multiple air detection data. Alternatively, the spatial location information in the initial data of the second location can be used as one of the aforementioned multiple target spatial location information, and the sub-data in the initial data of the second location can be used as one of the aforementioned multiple air detection data.

[0100] Step S105: The initial data corresponding to the first position and the initial data corresponding to the second position are respectively used as target spatial location information and corresponding air detection data for different positions.

[0101] Specifically, the spatial location information in the initial data of the first position and the spatial location information in the initial data of the second position can both be used as the target spatial location information, and the sub-data in the initial data of the first position and the sub-data in the initial data of the second position can be used as the aforementioned multiple air detection data.

[0102] In this embodiment, by using a preset map resolution, it is determined whether two adjacent detection locations belong to the same pixel unit in the subsequently determined map. Only one of the two air data belonging to the same pixel unit is retained for generating air map data, while air data that do not belong to the same pixel unit are both used to generate air map data. This satisfies the map accuracy requirements while further reducing data redundancy.

[0103] Furthermore, based on any of the above embodiments, another embodiment of the map data generation method of this application is proposed. In this embodiment, reference is made to... Figure 5 S10 includes:

[0104] Step S11: Control the air conditioner to transmit the first wireless signal;

[0105] Step S12: Receive detection data sent by air detection modules at different locations and signal characteristic values ​​of a second wireless signal, wherein the second wireless signal is the received signal formed by the first wireless signal in the air detection module.

[0106] In this embodiment, both the first and second wireless signals are Bluetooth signals. Specifically, the air detection module and the air conditioner communicate using the Bluetooth 5.1 communication standard. In other embodiments, the first and second wireless signals can also be other types of wireless signals used for positioning, such as infrared signals.

[0107] The air detection module can detect data from the above-mentioned various air evaluation parameters at different locations as the detection data here. At the same time, the air detection module can also receive a first wireless signal through a receiver at different locations, and the received signal becomes a second wireless signal. The air detection modules at different locations can extract the signal feature value of the second wireless signal at that location and send it together with the detection data detected at that location to the air conditioner.

[0108] Signal characteristics may specifically include signal reception time, signal reception amplitude, and / or signal frequency.

[0109] Step S13: Determine the target spatial location information of the corresponding air detection module based on each signal feature value, and determine the detection data as the air detection data corresponding to the target spatial location information.

[0110] A signal characteristic value at a location corresponds to a specific target spatial location. Different signal characteristic values ​​correspond to different target spatial location information. The correspondence between signal characteristic values ​​and target spatial location information can be determined by the characteristic parameters related to the wireless signals transmitted by the air conditioner and the characteristic parameters related to the wireless signals received by the air detection module; different characteristic parameters result in different correspondences. The correspondence can take the form of calculation formulas, mapping relationships, etc.

[0111] In this embodiment, the air conditioner transmits a first wireless signal through an antenna array, and the air detection module receives a second wireless signal through an antenna. Then, based on the angle of departure (AOD) measurement method, a first correspondence between the signal feature value and the target spatial location information can be determined, and the target spatial location information corresponding to the signal feature value can be determined based on the first correspondence.

[0112] In other embodiments, the air conditioner can also transmit a first wireless signal through an antenna, and the air detection module can receive a second wireless signal through an antenna array. Then, a second correspondence between the signal feature value and the target spatial location information can be determined based on the angle of arrival (AOA) measurement method, and the target spatial location information corresponding to the signal feature value can be determined based on the second correspondence.

[0113] In this embodiment, the air detection modules at different locations in the air conditioner's operating space are located based on wireless signals, which helps to obtain more accurate target spatial location information, thereby ensuring that the subsequent map data can accurately reflect the actual distribution of air quality in the space.

[0114] It should be noted that when step S10 includes steps S101 to S105 as described above, the process of obtaining the initial data in step S101 is the same as that in steps S11 to S13, and will not be repeated here.

[0115] Specifically, in this embodiment, the step of determining the target spatial location information of the corresponding air detection module based on each signal feature value includes:

[0116] Step S131: Calculate the polar coordinates of the location of the corresponding air detection module based on each signal feature value;

[0117] Specifically, a polar coordinate system can be established with the reference point on the air conditioner as the origin. Based on the characteristic values ​​of each signal, the direction and distance of the corresponding air detection module relative to the origin can be determined. Based on this direction and distance, the corresponding coordinate values ​​in the polar coordinate system can be determined as the polar coordinates of the corresponding position.

[0118] In this embodiment, the first wireless signal is transmitted through at least two antennas on the air conditioner. The process of calculating the corresponding polar coordinates based on AOD positioning using signal feature values ​​is as follows: calculate the first distance between each of the at least two antennas and the air detection module according to the signal feature values ​​and the preset distance between the at least two antennas; calculate the polar coordinates corresponding to the signal feature values ​​according to the first distance corresponding to each of the at least two antennas and the preset distance.

[0119] Specifically, the signal transmission angle corresponding to the target antenna among the at least two antennas is calculated based on the first distance corresponding to each of the at least two antennas and the preset distance. The signal transmission angle is the angle between the straight line where the at least two antennas are located and the straight line where the first wireless signal transmitted by the target antenna is located. The polar coordinates are calculated based on the signal transmission angle, the first distance corresponding to the target antenna, and the preset distance.

[0120] Specifically, the first wireless signal includes sub-signals transmitted by antenna 1 and antenna 2 respectively. The distance d0 between the two antennas, as well as preset signal characteristic parameters such as the signal frequency and wavelength of the sub-signals, can be predetermined. The distances d1 and d2 between the location of the corresponding air detection module and antenna 1 and antenna 2 can be calculated through the signal characteristic values. The polar coordinates of the corresponding location can be calculated using d1 and d2. The calculation method is as follows:

[0121] Angle α = cos 1 from the antenna -1 (d0*d0+d1*d1-d2*d2) / (2d0*d1);

[0122] Euclidean coordinates are:

[0123] Where α is the signal transmission angle of the target antenna, and the Euclidean coordinates are polar coordinates.

[0124] Step S132: Determine the target spatial location information of the corresponding position based on each of the polar coordinates.

[0125] Specifically, the polar coordinates can be used as the target spatial location information for the corresponding positions, or the result of coordinate transformation of the polar coordinates according to pre-defined rules can be used as the target spatial location information for the corresponding positions.

[0126] In this embodiment, the polar coordinates obtained by calculating the signal feature values ​​are used to determine the target spatial location information of the corresponding position. This helps to ensure that the determined target spatial location information can accurately reflect the direction and distance of the detection position corresponding to the air detection data relative to the air conditioner, thereby improving the accuracy of the subsequently generated air map data.

[0127] Furthermore, in this embodiment, when the air conditioner belongs to the first type, the polar coordinates are used as the target spatial location information for the corresponding position; when the air conditioner belongs to the second type, the result of performing coordinate transformation on each polar coordinate based on the angle between the air conditioner and the wall of the air conditioner's operating space is used as the target spatial location information for the corresponding position; the first type is an air conditioner installed on the wall of the air conditioner's operating space (e.g., wall-mounted air conditioner, ceiling-mounted air conditioner, window air conditioner, etc.), and the second type is an air conditioner set at an angle to the wall of the air conditioner's operating space (e.g., cabinet air conditioner, portable air conditioner, etc.). In this embodiment, coordinate transformation helps to prevent locations where air data cannot be detected in the subsequently generated air map data, thereby further reducing data redundancy.

[0128] Furthermore, embodiments of the present invention also propose a computer-readable storage medium storing a map data generation program, wherein when the map data generation program is executed by a processor, it implements the relevant steps of any of the above embodiments of the map data generation method.

[0129] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0130] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0131] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) as described above, and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0132] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A map data generation method, applied to an air conditioner, characterized in that, The map data generation method includes the following steps: Acquire target spatial location information and corresponding air detection data at different locations within the operating space of the air conditioner; the air detection data includes sub-detection data corresponding to various air evaluation parameters. Determine the first map location information corresponding to each of the target spatial location information; Based on each of the first map location information and its corresponding multiple sub-detection data, a one-dimensional array of targets is generated to obtain air map data of the air conditioner's operating space.

2. The map data generation method as described in claim 1, characterized in that, The step of generating a one-dimensional array of targets based on each of the first map location information and its corresponding multiple sub-detection data includes: Obtain an initial one-dimensional array, which includes multiple sub-one-dimensional arrays. Each sub-one-dimensional array represents a pixel unit of the air map data. The sub-one-dimensional array includes first data and second data. The first data includes preset map location information of the corresponding pixel unit. The second data includes the initial values ​​of the various air evaluation parameters corresponding to the spatial location represented by the corresponding pixel unit. Determine the target array as the sub-one-dimensional array containing each of the first map location information matching the preset map location information; In the initial one-dimensional array, the initial values ​​in the corresponding target array are updated according to the multiple sub-detection data corresponding to each of the first map location information, so as to obtain the target one-dimensional array.

3. The map data generation method as described in claim 2, characterized in that, The initial value is the data of the corresponding air quality assessment parameter detected before the current moment, or the initial value is a preset value, which indicates that there is no detection data for the corresponding air quality assessment parameter.

4. The map data generation method as described in claim 1, characterized in that, The step of generating a one-dimensional array of targets based on each of the first map location information and its corresponding multiple sub-detection data to obtain air map data of the air conditioner's operating space includes: When the air detection module corresponding to the air detection data is fixed within the working space of the air conditioner, a one-dimensional sparse array is generated based on multiple first map location information and multiple sub-detection data corresponding to each first map location information to obtain the air map data of the working space of the air conditioner.

5. The map data generation method as described in claim 1, characterized in that, The data format of the one-dimensional array is either ProtoBuf or JSON.

6. The map data generation method according to any one of claims 1 to 5, characterized in that, The steps for obtaining target spatial location information and corresponding air detection data at different locations within the operating space of the air conditioner include: Acquire initial data corresponding to multiple detection locations within the operating space of the air conditioner. The initial data includes spatial location information of the corresponding detection locations and sub-data corresponding to the various air evaluation parameters obtained by detection. Determine any two adjacent positions among the plurality of detection positions as the first position and the second position; Based on the preset map resolution, the spatial location information of the first location, and the spatial location information of the second location, it is determined whether the map locations corresponding to the first location and the second location belong to the same pixel unit in the air map data. If so, then the initial data corresponding to one of the first position and the second position is determined as the target spatial location information and its corresponding air detection data; If not, the initial data corresponding to the first position and the initial data corresponding to the second position shall be used as the target spatial location information and the corresponding air detection data for different positions.

7. The map data generation method according to any one of claims 1 to 5, characterized in that, The steps for obtaining target spatial location information and corresponding air detection data at different locations within the operating space of the air conditioner include: Control the air conditioner to transmit the first wireless signal; The system receives detection data sent by air detection modules at different locations and signal characteristic values ​​of a second wireless signal, wherein the second wireless signal is the received signal formed by the first wireless signal in the air detection module. Based on each signal feature value, the target spatial location information of the corresponding air detection module is determined, and the detection data is determined to be the air detection data corresponding to the target spatial location information.

8. The map data generation method as described in claim 7, characterized in that, The step of determining the target spatial location information of the corresponding air detection module based on each signal feature value includes: Calculate the polar coordinates of the location of the air detection module corresponding to each of the signal feature values; The target spatial location information is determined based on the polar coordinates described above.

9. The map data generation method as described in claim 8, characterized in that, The step of determining the target spatial location information of the current position of the air detection module based on the polar coordinates includes: When the air conditioner belongs to the first type, the polar coordinates are used as the target spatial location information of the corresponding position; When the air conditioner belongs to the second type, the result of performing coordinate transformation operation on each polar coordinate according to the angle between the air conditioner and the wall of the air conditioner's operating space is used as the target spatial position information of the corresponding position. The first type is an air conditioner installed on the wall of the space where the air conditioner operates, and the second type is an air conditioner installed at an angle to the wall of the space where the air conditioner operates.

10. The map data generation method as described in claim 8, characterized in that, The first wireless signal is transmitted through at least two antennas on the air conditioner, and the step of calculating the polar coordinates of the location of the corresponding air detection module based on each signal feature value includes: Calculate the first distance between each of the at least two antennas and the air detection module based on the signal characteristic value and the preset distance between the at least two antennas; The polar coordinates corresponding to the signal feature value are calculated based on the first distance corresponding to each of the at least two antennas and the preset distance.

11. An air conditioner, characterized in that, The air conditioner includes: a memory, a processor, and a map data generation program stored in the memory and executable on the processor, wherein when the map data generation program is executed by the processor, it implements the steps of the map data generation method as described in any one of claims 1 to 10.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a map data generation program, which, when executed by a processor, implements the steps of the map data generation method as described in any one of claims 1 to 10.

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