Air management method, device and equipment and storage medium

Abstract

The invention relates to the technical field of household appliances, in particular to an air management method, device and equipment and a storage medium. Confidence data of all online terminal equipment in a target trusteeship area is obtained, target issuing terminal equipment is selected based on the confidence data of all the online terminal equipment, and when a control instruction needs to be issued, the control instruction is sent to the target trusteeship area. And issuing the control instruction to the target issuing terminal device with the highest confidence coefficient, and forwarding the control instruction to each online air management terminal device through the target issuing terminal device, thereby realizing all-region air management of the target hosting region, and avoiding the unstable management process of the air treatment device in the prior art, and improving the management efficiency. The technical problem is solved, and the stability of air management is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of household appliances, and in particular to an air management method, device, equipment and storage medium. Background Art

[0002] In the traditional air management process, in order to achieve the management, control and linkage of air management-related equipment within the home, it is generally based on the temperature control logic of the indoor ambient temperature, and a fixed control instruction is sent to a certain connector or terminal device to control the air treatment equipment in the entire home. In this process, if the terminal device or connector fails or goes offline, it will affect the efficiency of air management within the home, and is affected by factors such as the network environment, and the control process is extremely unstable.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present invention is to provide an air management method, device, equipment and storage medium, aiming to solve the technical problem in the prior art that the management process of air treatment equipment is unstable and easily affected by external equipment.

[0005] To achieve the above object, the present invention provides an air management method, which comprises the following steps:

[0006] Obtain confidence data of each online terminal device in the target hosting area;

[0007] Determining a target sending terminal device according to the confidence data and each online terminal device; and

[0008] The air management instruction is sent to the target sending terminal device, so as to be forwarded to each online air management terminal device through the target sending terminal device to perform air management.

[0009] Optionally, before obtaining the confidence data of each online terminal device in the target hosting area, the method further includes:

[0010] Functionally classify each online terminal device to obtain a set of devices in multiple functional categories;

[0011] Get parameter information of sub-devices in each device set;

[0012] Calculating the device context similarity of each sub-device according to the parameter information; and

[0013] The confidence data of each device set is determined according to the device context similarity of each sub-device.

[0014] Optionally, calculating the device context similarity of each sub-device according to the parameter information includes:

[0015] generating a credibility calculation array and a target parameter mean value according to the parameter information, wherein the credibility calculation array includes an online rate, a function mutual exclusion coefficient, time node information, and frequency change information; and

[0016] The device context similarity of each sub-device is calculated according to the credibility calculation array, the preset regularization parameter and the target parameter mean.

[0017] Optionally, calculating the device context similarity of each sub-device according to the credibility calculation array, a preset regularization parameter and the target parameter mean value includes:

[0018] Obtaining the mean and standard deviation of each parameter in the credibility calculation array;

[0019] Normalizing the parameter credibility calculation array according to the mean and standard deviation of each parameter to obtain a target credibility calculation array; and

[0020] The device context similarity of each sub-device is calculated according to the target credibility calculation array, the preset regularization parameter and the target parameter mean.

[0021] Optionally, determining the confidence data of each device set according to the device context similarity of each sub-device includes:

[0022] Determine target sub-devices that belong to the same device set; and

[0023] The context similarities of the target sub-devices are summed to obtain confidence data of each device set.

[0024] Optionally, the summing up the context similarities of the target sub-devices to obtain the confidence data of each device set includes:

[0025] Determining a weight threshold corresponding to the target sub-device; and

[0026] A summation process is performed according to the weight threshold and the context similarity of the target sub-device to obtain the confidence data of each device set.

[0027] Optionally, determining a target delivery terminal device according to the confidence data and each online terminal device includes:

[0028] Determine the device set corresponding to each online terminal device according to the device mutual function matrix table;

[0029] sorting the set of devices according to the confidence data; and

[0030] Determine the target terminal device based on the sorting results.

[0031] In addition, to achieve the above-mentioned purpose, the present invention also proposes an air management device, the air management device comprising:

[0032] An acquisition module, used to acquire confidence data of each online terminal device in a target hosting area;

[0033] a determination module, configured to determine a target sending terminal device according to the confidence data and each online terminal device; and

[0034] The transmission module is used to send the air management instruction to the target sending terminal device, so as to forward it to each online air management terminal device through the target sending terminal device to perform air management.

[0035] In addition, to achieve the above-mentioned objectives, the present invention also proposes an air management device, which includes: a memory, a processor, and an air management program stored in the memory and executable on the processor, and the air management program is configured to implement the steps of the air management method described above.

[0036] In addition, to achieve the above-mentioned purpose, the present invention further proposes a storage medium, on which an air management program is stored, and when the air management program is executed by a processor, the steps of the air management method described above are implemented.

[0037] The present invention discloses an air management method, which comprises: obtaining confidence data of each online terminal device in a target hosting area; determining a target sending terminal device according to the confidence data and each online terminal device; sending an air management instruction to the target sending terminal device, so as to forward the instruction to each online air management terminal device through the target sending terminal device, so as to perform air management. Compared with the prior art, the present invention obtains the confidence data of each online terminal device in the target hosting area, and selects a target sending terminal device based on the confidence data of each online terminal device. When a control instruction needs to be sent, the control instruction is sent to the target sending terminal device with the highest confidence, so as to forward the instruction to each online air management terminal device through the target sending terminal device, so as to achieve full-area air management of the target hosting area, avoid the technical problem that the management process of the air treatment equipment in the prior art is unstable and easily affected by external equipment, and improve the stability of air management. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 It is a structural schematic diagram of an air management device in a hardware operating environment involved in an embodiment of the present invention;

[0039] Figure 2 This is a flow chart of a first embodiment of the air management method of the present invention;

[0040] Figure 3 A schematic diagram of a flow chart of instructions issued by an embodiment of an air management method of the present invention;

[0041] Figure 4 It is a flow chart of the second embodiment of the air management method of the present invention;

[0042] Figure 5 It is a structural block diagram of the first embodiment of the air management device of the present invention.

[0043] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0044] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0045] Reference Figure 1 , Figure 1 A schematic diagram of the air management device structure of the hardware operating environment involved in the embodiment of the present invention.

[0046] like Figure 1 As shown, the air management device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0047] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation of the air management device, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0048] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and an air management program.

[0049] exist Figure 1 In the air management device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the air management device of the present invention can be set in the air management device, and the air management device calls the air management program stored in the memory 1005 through the processor 1001, and executes the air management method provided by the embodiment of the present invention.

[0050] The embodiment of the present invention provides an air management method, referring to Figure 2 , Figure 2 It is a flow chart of a first embodiment of an air management method of the present invention.

[0051] In this embodiment, the air management method includes the following steps:

[0052] Step S10: Acquire the confidence data of each online terminal device in the target hosting area.

[0053] It should be noted that the executor of the method of this embodiment can be a device with functions such as data processing, network communication and program running, such as a cloud server or a cluster server, etc., or other devices that can achieve the same or similar functions. This embodiment does not impose specific restrictions on this. In this embodiment and the following embodiments, the cloud server will be used as an example for explanation.

[0054] It should be noted that when the whole house air equipment is connected to the Internet of Things, the cloud-based control is called AI hosting. Among the controlled devices, there are independent devices, such as home central air conditioners. The wire controllers in each room of the home central air conditioner can communicate with each other through the internal wired communication link of the central air conditioner. Each wire controller is equipped with independent WiFi and can be connected to the Internet independently.

[0055] There are two control methods in the AI ​​hosting process. One is to send instructions to all controlled terminals separately, and the other is to forward them through a certain device. The workload of the first control method is too large. In the second control method, if the device receiving the control instruction is offline or fails, all devices will not be able to receive the control instruction, and the AI ​​hosting effect will be poor.

[0056] In order to solve the above problem, this embodiment obtains the confidence data of each online terminal device in the target hosting area, and selects the target sending terminal device based on the confidence data of each online terminal device. When a control instruction needs to be issued, the control instruction is sent to the target sending terminal device with the highest confidence, so as to be forwarded to each online air management terminal device through the target sending terminal device, thereby realizing full-area air management of the target hosting area.

[0057] It is worth noting that the target hosting area refers to the area that needs to be managed by air hosting, which can be a home area, warehouse or factory building, etc. depending on the application scenario; the online terminal device in this embodiment can be various devices for air management, such as air conditioners, fans, dehumidifiers, humidifiers and fresh air fans, etc., which are powered on, depending on the application scenario and the hosting area. This embodiment does not impose any specific restrictions on this.

[0058] It is understandable that confidence data, also known as confidence score, is mainly used to measure the reliability of each online terminal device. Generally speaking, the higher the confidence score, the more reliable it is; the lower the confidence score, the less reliable it is and there is a risk of loss of control.

[0059] In a specific implementation, the confidence data is calculated in advance based on parameters such as the online rate, online and offline time, device restart or recovery time, and sensor change frequency of each online terminal device to obtain scoring data. This embodiment does not impose specific restrictions on the calculation of the confidence data of each online terminal device.

[0060] Step S20: determining a target delivery terminal device according to the confidence data and each online terminal device.

[0061] It should be noted that the target terminal device generally refers to the most reliable terminal device, so that when the control instructions are subsequently issued, the air management hosting will not fail due to signal loss or equipment failure, affecting the user experience.

[0062] Further, determining the target sending terminal device according to the confidence data and each online terminal device includes:

[0063] Determine the device set corresponding to each online terminal device according to the device mutual function matrix table;

[0064] sorting the set of devices according to the confidence data;

[0065] Determine the target terminal device based on the sorting results.

[0066] It can be understood that the device mutual function matrix table refers to a list that records the functions of each terminal device, wherein the device mutual function matrix table records the information of each device with similar functions or the same functions, including but not limited to: device model, brand, device parameters and other information. The device mutual function matrix table is mainly used to determine whether each terminal device has the same or similar functions, so as to facilitate the classification of each terminal device according to function and obtain a set of devices with the same or similar functions.

[0067] In the specific implementation, refer to Figure 3 , Figure 3 This is a schematic diagram of the instruction issuing process of an embodiment of the present invention. Generally, the terminal device in the device set with the highest confidence is used as the main issuing device, and the control instruction is sent to the main issuing device. If the terminal devices in the device set with the highest confidence are all offline, restarted, or the confidence level changes, the terminal device in the device set with the second highest confidence level is selected as the main issuing device to receive and forward the control instruction.

[0068] Step S30: Send the air management instruction to the target sending terminal device, so that it is forwarded to each online air management terminal device through the target sending terminal device to perform air management.

[0069] It should be understood that the air management instructions are mainly used to control the operating status of each online air management device in the target hosting area. The air management instructions include but are not limited to information such as the operating power, speed, and time of various air management devices.

[0070] In the specific implementation, if the hosting area is a home area, the air management equipment in the hosting area may include air conditioners, humidifiers, dehumidifiers, fans, and temperature sensors. Among these devices, if the air conditioner has the highest confidence, the cloud can send control instructions to other room wire controllers, indoor units, and other devices through any wire controller or indoor unit of the air conditioner in the home, so as to control the operating status of each online air management device and realize the hosting of air management. If the air conditioner goes offline during the management process, or the device is unavailable for a short period of time, the cloud control will be abnormal, resulting in reduced air management effect. At this time, the cloud command is sent to the device with the second highest credibility, improving the reliability of AI hosting and the robustness of the air management process.

[0071] This embodiment obtains the confidence data of each online terminal device in the target hosting area, and selects a target sending terminal device based on the confidence data of each online terminal device. When a control instruction needs to be issued, the control instruction is sent to the target sending terminal device with the highest confidence, so as to be forwarded to each online air management terminal device through the target sending terminal device, thereby realizing full-area air management of the target hosting area, avoiding the technical problems in the prior art that the management process of the air treatment equipment is unstable and easily affected by external equipment, and improving the stability of air management.

[0072] refer to Figure 4 , Figure 4 It is a flow chart of a second embodiment of an air management method of the present invention.

[0073] Based on the first embodiment above, in this embodiment, before step S10, the following steps are further included:

[0074] Step S01: functionally classify each online terminal device to obtain a set of devices of multiple functional categories.

[0075] It should be noted that the functional classification of each online terminal device to obtain a device set of multiple functional categories can be a device set obtained by classifying the functions of each device recorded in the device mutual function matrix table, and the same device can exist in different device sets at the same time. For example, the air conditioner and the fresh air fan both have the fresh air function, but the air conditioner also has the dehumidification function. Therefore, the device set corresponding to the dehumidification function may include air conditioners and dehumidifiers; the device set corresponding to the fresh air function may include air conditioners, fresh air fans, fans and other equipment. This embodiment does not make specific restrictions on this.

[0076] Step S02: Obtain parameter information of sub-devices in each device set.

[0077] It should be understood that the parameter information of each sub-device in the device set includes but is not limited to parameters such as the online rate of the online terminal device, the online and offline time, the time for device restart or recovery, and the frequency of sensor changes. This embodiment does not impose specific restrictions on this.

[0078] Step S03: Calculate the device context similarity of each sub-device according to the parameter information.

[0079] It can be understood that the context similarity is also called a device credibility evaluation index and is used to determine the relevance of a device in a device set.

[0080] Further, the calculating the device context similarity of each sub-device according to the parameter information includes:

[0081] Generate a credibility calculation array and a target parameter mean value according to the parameter information, wherein the credibility calculation array includes an online rate, a function mutual exclusion coefficient, time node information, and frequency change information;

[0082] The device context similarity of each sub-device is calculated according to the credibility calculation array, the preset regularization parameter and the target parameter mean.

[0083] In a specific implementation, the device online rate refers to the ratio of the time during which the device operates normally and is available for use to the total time within a specific time period; time node information includes but is not limited to time node information such as the time when the device goes online and offline and the time when the device is restarted or restored; frequency change information may include the frequency of sensor data collection, etc., and this embodiment does not impose specific restrictions on this.

[0084] The calculation formula of the context similarity of the device is as follows:

[0085] SCS(Ai,Aj)=exp(-λ∑Xi,j-μ)

[0086] Among them, SCS(Ai,Aj) refers to the context similarity of sub-devices in a certain device set, Xi,j refers to the value of the jth parameter of the i-th and j-th devices; λ is a regularization parameter to avoid overfitting; μ is the mean of all device parameters.

[0087] Further, the calculating the device context similarity of each sub-device according to the credibility calculation array, the preset regularization parameter and the target parameter mean value includes:

[0088] Obtaining the mean and standard deviation of each parameter in the credibility calculation array;

[0089] Normalizing the parameter credibility calculation array according to the mean and standard deviation of each parameter to obtain a target credibility calculation array;

[0090] The device context similarity of each sub-device is calculated according to the target credibility calculation array, the preset regularization parameter and the target parameter mean.

[0091] In a specific implementation, in order to improve the efficiency of data processing and simplify the process of output calculation, this embodiment may first normalize the parameter information of each device, and the normalization process may be implemented by the following formula:

[0092] Xi,j=(Xi,j-μ') / σ'

[0093] Where μ' and σ' are the mean and standard deviation of the jth parameter of the ith and jth device, respectively.

[0094] Step S04: Determine the confidence data of each device set according to the device context similarity of each sub-device.

[0095] It should be noted that the present embodiment issues instructions to a device set of a functional category to avoid a situation in which a single device is offline during the hosted air management process, thereby affecting the hosting effect. As for the confidence of a device set of a functional category, the context similarities of the sub-devices belonging to the device set can be superimposed to obtain the confidence data of the device set.

[0096] Further, the determining of the confidence data of each device set according to the device context similarity of each sub-device includes:

[0097] Determine the target sub-devices belonging to the same device set;

[0098] The context similarities of the target sub-devices are summed to obtain confidence data of each device set.

[0099] In the specific implementation, the calculation formula of the confidence data of the device set is as follows:

[0100] Trust(Ai)=ΣSCS(Ai,Aj)

[0101] Among them, Trust(Ai) is the confidence data of the device set, and SCS(Ai,Aj) is the context similarity of each sub-device in the device set.

[0102] Furthermore, the context similarities of the target sub-devices are summed to obtain the confidence data of each device set, including:

[0103] Determine a weight threshold corresponding to the target sub-device;

[0104] A summation process is performed according to the weight threshold and the context similarity of the target sub-device to obtain the confidence data of each device set.

[0105] In the specific implementation, in order to improve the reliability of the confidence data of the device set, the present embodiment can also assign weights to each sub-device under the device set to reduce the confidence weight ratio of devices that have less impact on air management. For example: for the fresh air function, fresh air fans, air conditioners and other equipment have a greater impact and relatively higher weights, while small fans have smaller air management capabilities and correspondingly lower weights.

[0106] This embodiment functionally classifies each online terminal to obtain a device set of multiple functional categories, thereby avoiding the problem of incorrect instruction issuance due to a single device failure or offline. At the same time, by obtaining parameter information of each sub-device in each device set, the context similarity of each sub-device is calculated, and the confidence data of the entire device set is calculated based on the context similarity of each sub-device, so that reliable and stable instruction issuance equipment can be selected later to improve air management efficiency.

[0107] In addition, an embodiment of the present invention further provides a storage medium, on which an air management program is stored. When the air management program is executed by a processor, the steps of the air management method described above are implemented.

[0108] Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0109] Reference Figure 5 , Figure 5 It is a structural block diagram of the first embodiment of the air management device of the present invention.

[0110] like Figure 5 As shown, the air management device proposed in the embodiment of the present invention includes:

[0111] The acquisition module 10 is used to acquire the confidence data of each online terminal device in the target hosting area.

[0112] It should be noted that when the whole house air equipment is connected to the Internet of Things, the cloud-based control is called AI hosting. Among the controlled devices, there are independent devices, such as home central air conditioners. The wire controllers in each room of the home central air conditioner can communicate with each other through the internal wired communication link of the central air conditioner. Each wire controller is equipped with independent WiFi and can be connected to the Internet independently.

[0113] There are two control methods in the AI ​​hosting process. One is to send instructions to all controlled terminals separately, and the other is to forward them through a certain device. The workload of the first control method is too large. In the second control method, if the device receiving the control instruction is offline or fails, all devices will not be able to receive the control instruction, and the AI ​​hosting effect will be poor.

[0114] In order to solve the above problem, this embodiment obtains the confidence data of each online terminal device in the target hosting area, and selects the target sending terminal device based on the confidence data of each online terminal device. When a control instruction needs to be issued, the control instruction is sent to the target sending terminal device with the highest confidence, so as to be forwarded to each online air management terminal device through the target sending terminal device, thereby realizing full-area air management of the target hosting area.

[0115] It is worth noting that the target hosting area refers to the area that needs to be managed by air hosting, which can be a home area, warehouse or factory building, etc. depending on the application scenario; the online terminal device in this embodiment can be various devices for air management, such as air conditioners, fans, dehumidifiers, humidifiers and fresh air fans, etc., which are powered on, depending on the application scenario and the hosting area. This embodiment does not impose any specific restrictions on this.

[0116] It is understandable that confidence data, also known as confidence score, is mainly used to measure the reliability of each online terminal device. Generally speaking, the higher the confidence score, the more reliable it is; the lower the confidence score, the less reliable it is and there is a risk of loss of control.

[0117] In a specific implementation, the confidence data is calculated in advance based on parameters such as the online rate, online and offline time, device restart or recovery time, and sensor change frequency of each online terminal device to obtain scoring data. This embodiment does not impose specific restrictions on the calculation of the confidence data of each online terminal device.

[0118] The determination module 20 is used to determine the target sending terminal device according to the confidence data and the online terminal devices.

[0119] It should be noted that the target terminal device generally refers to the most reliable terminal device, so that when the control instructions are subsequently issued, the air management hosting will not fail due to signal loss or equipment failure, affecting the user experience.

[0120] Further, determining the target sending terminal device according to the confidence data and each online terminal device includes:

[0121] Determine the device set corresponding to each online terminal device according to the device mutual function matrix table;

[0122] sorting the set of devices according to the confidence data;

[0123] Determine the target terminal device based on the sorting results.

[0124] It can be understood that the device mutual function matrix table refers to a list that records the functions of each terminal device, wherein the device mutual function matrix table records the information of each device with similar functions or the same functions, including but not limited to: device model, brand, device parameters and other information. The device mutual function matrix table is mainly used to determine whether each terminal device has the same or similar functions, so as to facilitate the classification of each terminal device according to function and obtain a set of devices with the same or similar functions.

[0125] In the specific implementation, the terminal device in the device set with the highest confidence is generally used as the main sending device, and control instructions are sent to the main sending device. If the terminal devices in the device set with the highest confidence are all offline, restarted, or the confidence level changes, the terminal device in the device set with the second highest confidence level is selected as the main sending device to receive and forward the control instructions.

[0126] The transmission module 30 is used to send the air management instruction to the target sending terminal device, so as to forward the air management instruction to each online air management terminal device through the target sending terminal device to perform air management.

[0127] It should be understood that the air management instructions are mainly used to control the operating status of each online air management device in the target hosting area. The air management instructions include but are not limited to information such as the operating power, speed, and time of various air management devices.

[0128] In the specific implementation, if the hosting area is a home area, the air management equipment in the hosting area may include air conditioners, humidifiers, dehumidifiers, fans, and temperature sensors. Among these devices, if the air conditioner has the highest confidence, the cloud can send control instructions to other room wire controllers, indoor units, and other devices through any wire controller or indoor unit of the air conditioner in the home, so as to control the operating status of each online air management device and realize the hosting of air management. If the air conditioner goes offline during the management process, or the device is unavailable for a short period of time, the cloud control will be abnormal, resulting in reduced air management effect. At this time, the cloud command is sent to the device with the second highest credibility, improving the reliability of AI hosting and the robustness of the air management process.

[0129] In one embodiment, the acquisition module 10 is also used to functionally classify each online terminal device to obtain a device set of multiple functional categories; obtain parameter information of sub-devices in each device set; calculate the device context similarity of each sub-device based on the parameter information; and determine the confidence data of each device set based on the device context similarity of each sub-device.

[0130] In one embodiment, the acquisition module 10 is also used to generate a credibility calculation array and a target parameter mean according to the parameter information, wherein the credibility calculation array includes an online rate, a function mutual exclusion coefficient, time node information, and frequency change information; and calculate the device context similarity of each sub-device according to the credibility calculation array, a preset regularization parameter, and the target parameter mean.

[0131] In one embodiment, the acquisition module 10 is also used to obtain the mean and standard deviation of each parameter in the credibility calculation array; normalize the parameter credibility calculation array according to the mean and standard deviation of each parameter to obtain a target credibility calculation array; calculate the device context similarity of each sub-device according to the target credibility calculation array, a preset regularization parameter and the target parameter mean.

[0132] In one embodiment, the acquisition module 10 is further used to determine target sub-devices belonging to the same device set; and to sum the context similarities of the target sub-devices to obtain confidence data of each device set.

[0133] In one embodiment, the acquisition module 10 is further used to determine a weight threshold corresponding to the target sub-device; and perform summation processing based on the weight threshold and the context similarity of the target sub-device to obtain confidence data of each device set.

[0134] In one embodiment, the transmission module 30 is further used to determine a device set corresponding to each online terminal device according to the device mutual function matrix table; sort the device set according to the confidence data; and determine the target sending terminal device according to the sorting result.

[0135] This embodiment obtains the confidence data of each online terminal device in the target hosting area, and selects a target sending terminal device based on the confidence data of each online terminal device. When a control instruction needs to be issued, the control instruction is sent to the target sending terminal device with the highest confidence, so as to be forwarded to each online air management terminal device through the target sending terminal device, thereby realizing full-area air management of the target hosting area, avoiding the technical problems in the prior art that the management process of the air treatment equipment is unstable and easily affected by external equipment, and improving the stability of air management.

[0136] It should be understood that, although the various steps in the flowchart in the embodiment of the present application are displayed in sequence according to the indication of the arrows, these steps are not necessarily performed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps does not have a strict order restriction, and it can be performed in other orders. Moreover, at least a portion of the steps in the figure may include a plurality of sub-steps or a plurality of stages, and these sub-steps or stages are not necessarily performed at the same time, but can be performed at different times, and their execution order is not necessarily performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0137] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

[0138] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of them according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0139] In addition, for technical details that are not described in detail in this embodiment, reference can be made to the air management method provided in any embodiment of the present invention, and they will not be repeated here.

[0140] In addition, it should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or system including the element.

[0141] The serial numbers of the above embodiments of the present invention are only for description and do not represent the advantages or disadvantages of the embodiments.

[0142] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an 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, which is stored in a storage medium (such as a read-only memory (ROM) / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, a computer, a server, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0143] The above are only preferred embodiments of the present invention, and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An air management method, characterized in that: The air management method comprises: Obtain confidence data of each online terminal device in the target hosting area; Determining a target sending terminal device according to the confidence data and each online terminal device; and The air management instruction is sent to the target sending terminal device, so as to be forwarded to each online air management terminal device through the target sending terminal device to perform air management.

2. The air management method according to claim 1, characterized in that: Before obtaining the confidence data of each online terminal device in the target hosting area, the method further includes: Functionally classify each online terminal device to obtain a set of devices in multiple functional categories; Get parameter information of sub-devices in each device set; Calculating the device context similarity of each sub-device according to the parameter information; and The confidence data of each device set is determined according to the device context similarity of each sub-device.

3. The air management method according to claim 2, characterized in that: The calculating the device context similarity of each sub-device according to the parameter information includes: generating a credibility calculation array and a target parameter mean value according to the parameter information, wherein the credibility calculation array includes an online rate, a function mutual exclusion coefficient, time node information, and frequency change information; and The device context similarity of each sub-device is calculated according to the credibility calculation array, the preset regularization parameter and the target parameter mean.

4. The air management method according to claim 3, characterized in that: The calculating the device context similarity of each sub-device according to the credibility calculation array, the preset regularization parameter and the target parameter mean value includes: Obtaining the mean and standard deviation of each parameter in the credibility calculation array; Normalizing the parameter credibility calculation array according to the mean and standard deviation of each parameter to obtain a target credibility calculation array; and The device context similarity of each sub-device is calculated according to the target credibility calculation array, the preset regularization parameter and the target parameter mean.

5. The air management method according to claim 2, characterized in that: The step of determining the confidence data of each device set according to the device context similarity of each sub-device includes: Determine target sub-devices that belong to the same device set; and The context similarities of the target sub-devices are summed to obtain confidence data of each device set.

6. The air management method according to claim 5, characterized in that: The summing up of the context similarities of the target sub-devices to obtain the confidence data of each device set includes: Determining a weight threshold corresponding to the target sub-device; and A summation process is performed according to the weight threshold and the context similarity of the target sub-device to obtain the confidence data of each device set.

7. The air management method according to any one of claims 1 to 6, characterized in that: The step of determining the target sending terminal device according to the confidence data and each online terminal device includes: Determine the device set corresponding to each online terminal device according to the device mutual function matrix table; sorting the set of devices according to the confidence data; and Determine the target terminal device based on the sorting results.

8. An air management device, characterized in that: The air management device comprises: An acquisition module, used to acquire confidence data of each online terminal device in a target hosting area; a determination module, configured to determine a target sending terminal device according to the confidence data and each online terminal device; and The transmission module is used to send the air management instruction to the target sending terminal device, so as to forward it to each online air management terminal device through the target sending terminal device to perform air management.

9. An air management device, characterized in that: The air management device comprises: a memory, a processor, and an air management program stored in the memory and executable on the processor, wherein the air management program is configured to implement the air management method according to any one of claims 1 to 7.

10. A storage medium, characterized in that: The storage medium stores an air management program, and when the air management program is executed by the processor, the air management method according to any one of claims 1 to 7 is implemented.

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