Intelligent control method and device of air conditioning equipment, computer device and storage medium

Abstract

The application relates to the technical field of intelligent control, and particularly discloses an intelligent control method, device and equipment for an air conditioning device and a storage medium. The method comprises the following steps: obtaining user demand based on a signal acquisition module, and converting the user demand into a characteristic signal; calling a data acquisition module based on the characteristic signal, and collecting temperature data; generating a scheduling mode list of the air conditioning device based on an analysis result of the temperature data; and determining a target scheduling mode based on the user demand and the scheduling mode list, so as to control the air conditioning device. After the signal acquisition module is used to obtain the characteristic signal, the data acquisition module is called to collect real-time human body temperature and indoor and outdoor temperature data, the portability of operation is improved, and the real-time performance of data is ensured; through algorithm analysis, each scheduling mode is obtained, and the target scheduling mode is determined in combination with the user demand, so that the intelligence of controlling the air conditioning device is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent control, and particularly relates to an intelligent control method and device for an air conditioning equipment, a computer device and a storage medium. BACKGROUND

[0002] There are mainly three ways to control air conditioners in the existing smart home. The first way is to use a mobile phone software to achieve the effect of replacing a remote controller by using a mobile phone infrared sensor. The second way is to use a socket sensor to control a traditional air conditioner. The socket sensor integrates a wireless network module and an infrared remote control module. The wireless network module is connected to a home router to receive a command from a local area network, and the infrared module is responsible for sending signals. The third way is to use a sound box to convert a language signal into an infrared remote control signal to control an air conditioner. The above three ways are one-way infrared remote control, which cannot realize intelligent control and has information barriers with traditional remote controllers, and cannot accurately grasp the state of an air conditioner, resulting in low intelligence and portability of the intelligent control of the air conditioning equipment. Therefore, how to improve the intelligence and portability of the intelligent control of the air conditioning equipment has become a problem to be solved. SUMMARY

[0003] The present application provides an intelligent control method and device for an air conditioning equipment, a computer device and a storage medium to improve the intelligence and portability of the intelligent control of the air conditioning equipment.

[0004] In a first aspect, the present application provides an intelligent control method for an air conditioning equipment, which comprises the following steps.

[0005] Obtaining a user demand based on a signal acquisition module and converting the user demand into a characteristic signal;

[0006] Calling a data acquisition module based on the characteristic signal to acquire temperature data, wherein the temperature data comprises a human body temperature, an indoor temperature and an outdoor temperature;

[0007] Generating a scheduling mode list of the air conditioning equipment based on an analysis result of the temperature data;

[0008] Determining a target scheduling mode based on the user demand and the scheduling mode list to control the air conditioning equipment.

[0009] Further, the step of obtaining a user demand based on a signal acquisition module and converting the user demand into a characteristic signal comprises the following steps.

[0010] When the signal acquisition module receives a voice command of a user, determining the user identity by discriminating the voice command based on a preset timbre feature and a voice feature of the voice command;

[0011] When the user identity is a target user, based on the voice command, a user demand is acquired, and the user demand is converted into the characteristic signal.

[0012] Further, the signal-based acquisition module acquires a user demand and converts the user demand into a characteristic signal, and further includes:

[0013] When the signal acquisition module receives a device signal, a user device is searched in a local area network;

[0014] When the user device is searched, a user device identifier is extracted, and a target user device identifier is compared with the user device identifier to generate a comparison result;

[0015] When the comparison result is that the user device identifier is the same as the target user device identifier, the characteristic signal is generated.

[0016] Further, the signal-based acquisition module acquires a user demand and converts the user demand into a characteristic signal, and further includes:

[0017] When the signal acquisition module receives a remote command, a user demand in the remote command is extracted, and the user demand is converted into the characteristic signal.

[0018] Further, based on the analysis result of the temperature data, a scheduling mode list of an air conditioning device is generated, including:

[0019] Based on a preset weight ratio, a preset maximum temperature table, a preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature, a target temperature weight value is acquired;

[0020] A preset temperature weight threshold value is compared with the target temperature weight value to generate the scheduling mode list.

[0021] Further, based on the preset weight ratio, the preset maximum temperature table, the preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature, the target temperature weight value is acquired, including:

[0022] Based on the preset maximum temperature table, the human body temperature, the indoor temperature, and the outdoor temperature, a target preset weight ratio is determined;

[0023] Based on the preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature, a first difference value between the human body temperature and a preset suitable human body temperature, a second difference value between the indoor temperature and a preset suitable indoor temperature, and a third difference value between the outdoor temperature and a preset suitable outdoor temperature are generated;

[0024] generate the target temperature weight value based on the target preset weight ratio, the first difference value, the second difference value, and the third difference value.

[0025] Further, before obtaining the target temperature weight value based on the preset weight ratio, the preset highest temperature table, the preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature, the method further comprises:

[0026] generate the preset highest temperature table based on a preset highest human body temperature, a preset highest indoor temperature, and a preset highest outdoor temperature.

[0027] generate the preset suitable temperature table based on a preset suitable human body temperature, a preset suitable indoor temperature, and a preset suitable outdoor temperature.

[0028] In a second aspect, the present application further provides an intelligent control device of an air conditioning equipment, the device comprising:

[0029] a feature signal obtaining module, configured to obtain a user demand based on the signal obtaining module, and convert the user demand into a feature signal;

[0030] a temperature data collecting module, configured to collect temperature data based on the feature signal and the data collecting module, wherein the temperature data comprises a human body temperature, an indoor temperature, and an outdoor temperature;

[0031] a scheduling mode obtaining module, configured to generate a scheduling mode list of the air conditioning equipment based on an analysis result of the temperature data;

[0032] an air conditioner control module, configured to determine a target scheduling mode based on the user demand and the scheduling mode list, so as to control the air conditioning equipment.

[0033] In a third aspect, the present application further provides a computer device, comprising a memory and a processor; the memory is configured to store a computer program; the processor is configured to execute the computer program and realize the intelligent control method of the air conditioning equipment as described above when executing the computer program.

[0034] In a fourth aspect, the present application further provides a computer readable storage medium, which stores a computer program; the computer program is executed by a processor to make the processor realize the intelligent control method of the air conditioning equipment as described above.

[0035] This application discloses an intelligent control method, device, computer equipment, and storage medium for air conditioning equipment. Based on a signal acquisition module, user needs are obtained and converted into feature signals. Based on these feature signals, a data acquisition module is invoked to collect temperature data, including human body temperature, indoor temperature, and outdoor temperature. Based on the analysis results of the temperature data, a scheduling mode list for the air conditioning equipment is generated. Based on the user needs and the scheduling mode list, a target scheduling mode is determined to control the air conditioning equipment. This method utilizes a signal acquisition module to obtain feature signals, then invokes a data acquisition module to collect real-time human body temperature and indoor / outdoor temperature data, improving operational portability and ensuring data real-time performance. Through algorithm analysis, various scheduling modes are obtained, and combined with user needs, a target scheduling mode is determined to control the air conditioning equipment, improving the intelligence of air conditioning equipment control and thus enhancing the intelligence and portability of intelligent control of the air conditioning equipment. Attached Figure Description

[0036] To more clearly illustrate the technical solutions of the embodiments of this application, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 This is a schematic flowchart of a first embodiment of an intelligent control method for an air conditioning device provided in this application;

[0038] Figure 2 This is a schematic flowchart of a second embodiment of an intelligent control method for an air conditioning device provided in this application;

[0039] Figure 3 This is a schematic flowchart of a third embodiment of an intelligent control method for an air conditioning device provided in this application;

[0040] Figure 4 This is a schematic flowchart of a fourth embodiment of an intelligent control method for an air conditioning device provided in this application;

[0041] Figure 5 A schematic block diagram of an intelligent control device for an air conditioning unit provided for an embodiment of this application;

[0042] Figure 6 A schematic block diagram of the structure of a computer device provided for an embodiment of this application. Detailed Implementation

[0043] With reference to the drawings, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only some of the embodiments of the present application, but not all of them. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts are within the scope of the present application.

[0044] The flowcharts shown in the drawings are only illustrative, and do not necessarily include all contents and operations / steps, nor are they necessarily executed in the described order. For example, some operations / steps can be further decomposed, combined or partially merged, so that the actual execution order can be changed according to actual situations.

[0045] It should be understood that the terms used in the present application are only for the purpose of describing specific embodiments and are not intended to limit the present application. As used in the present application specification and the appended claims, unless otherwise clearly indicated by the context, the singular forms "a", "an" and "the" are intended to include the plural forms.

[0046] It should also be understood that the term "and / or" used in the present application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes these combinations.

[0047] Embodiments of the present application provide an intelligent control method and device of an air conditioning equipment, a computer device and a storage medium. The intelligent control method of the air conditioning equipment can be applied to a server to realize identification of a wool party by monitoring a marketing activity published by a merchant in real time. The server can be an independent server or a server cluster.

[0048] Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. In the case of no conflict, the following embodiments and features in the embodiments can be combined with each other.

[0049] Please refer to Figure 1 , Figure 1 is a schematic flowchart of a first embodiment of an intelligent control method of an air conditioning equipment provided by the embodiments of the present application. The intelligent control method of the air conditioning equipment can be applied to a server. After obtaining a feature signal, the human body temperature is collected, the indoor and outdoor temperatures are used as information sources, and a scheduling mode is obtained to control the air conditioning equipment.

[0050] As Figure 1 shown, the intelligent control method of the air conditioning equipment specifically includes steps S101 to S104.

[0051] S101, obtaining user demand based on a signal acquisition module, and converting the user demand into a characteristic signal.

[0052] In one embodiment, the air conditioning equipment distributed scheduling intelligent control method based on kaihongOs operating system takes obtaining a characteristic signal as the start of process scheduling. First, a signal acquisition module is called, and user demand can be obtained through various devices, and then the user demand is converted into a characteristic signal.

[0053] In one embodiment, the characteristic signal can be composed of signals in various scenarios. For example, in a human-computer interaction scenario, an intelligent sound box and other human-computer interaction devices are used as the source of signal characteristics. When remotely operating, a remote device sends demand to a device in a local area network, the device converts the demand into a characteristic signal and transmits it to a super terminal, thereby realizing remote control of the air conditioner. When a user initially connects to the terminal, pairing is required. After successful pairing, the super terminal memorizes the mac (Media Access Control Address, local area network address) address of the user's device as the identification of the target user. When the user arrives home, the super terminal queries the devices connected to the local area network, finds the target user's device, and then calls the intelligent self-generating control program.

[0054] S102, based on the characteristic signal, calling a data acquisition module to acquire temperature data, wherein the temperature data includes human body temperature, indoor temperature and outdoor temperature.

[0055] In one embodiment, the time when the characteristic signal is obtained is taken as the start of process scheduling. At this time, the data acquisition module sends process scheduling to obtain human body temperature data, indoor temperature data and outdoor temperature data.

[0056] Specifically, the data acquisition module includes a temperature sensor, such as a bracelet device that can obtain human body temperature, an indoor temperature sensor and an outdoor temperature sensor.

[0057] S103, generating a scheduling mode list of air conditioning equipment based on the analysis result of the temperature data.

[0058] In one embodiment, the temperature data collected by the data acquisition module is analyzed by an algorithm. According to different weight ratios, indoor and outdoor temperatures and body surface temperatures are mathematically calculated to obtain different scheduling modes and generate a scheduling mode list.

[0059] Specifically, first, the weight ratio of each temperature is determined according to each temperature maximum value in the preset temperature maximum value table and the real-time collected temperature data, and then the difference between each suitable temperature in the preset suitable temperature table and the real-time collected temperature data is obtained by calculation, the target temperature weight is obtained from the weight ratio and the difference, and the available scheduling mode is determined from the preset weight threshold to generate a scheduling mode list.

[0060] In S104, a target scheduling mode is determined based on the user demand and the scheduling mode list, so as to control the air conditioning equipment.

[0061] In one embodiment, after obtaining the scheduling mode, the scheduling mode that best meets the user demand is selected as the target scheduling mode based on the user demand, so as to control the air conditioner.

[0062] The above embodiment provides an intelligent control method and device of air conditioning equipment, computer equipment and storage medium. The user demand is obtained based on a signal acquisition module, and the user demand is converted into a feature signal. The temperature data is collected based on the feature signal and a data acquisition module, wherein the temperature data includes human body temperature, indoor temperature and outdoor temperature. The scheduling mode list of the air conditioning equipment is generated based on the analysis result of the temperature data. The target scheduling mode is determined based on the user demand and the scheduling mode list, so as to control the air conditioning equipment. After the feature signal is obtained by the signal acquisition module, the real-time human body temperature, indoor and outdoor temperature data are collected by the data acquisition module, the portability of operation is improved, and the real-time performance of data is ensured. The target scheduling mode is determined by algorithm analysis and user demand, so as to control the air conditioning equipment, improve the intelligence of the air conditioning equipment, and further improve the intelligence and portability of the intelligent control of the air conditioning equipment.

[0063] Please refer to Figure 2 , Figure 2 is a schematic flow chart of a second embodiment of an intelligent control method of air conditioning equipment provided by the embodiment. The intelligent control method of air conditioning equipment can be applied to a server. After the feature signal is obtained, the human body temperature, indoor and outdoor temperature data are collected as information sources, and the scheduling mode is obtained for controlling the air conditioning equipment.

[0064] As Figure 2 shown, the step S101 of the intelligent control method of air conditioning equipment specifically includes steps S201 to S202.

[0065] In S201, when the signal acquisition module receives the voice command of the user, the voice command is identified based on the preset timbre feature and the voice feature of the voice command, and the user identity is determined.

[0066] In one embodiment, when the feature signal is obtained, the user demand can be obtained by using the human-computer interaction device and converted into the feature signal. For example, the user transmits the demand to the sound equipment through voice, the sound equipment determines whether the current user is the target user by calling the deep learning model to identify the tone according to the stored tone characteristics and voice characteristics.

[0067] S202, when the user identity is the target user, obtaining the user demand based on the voice command, and converting the user demand into the feature signal.

[0068] In one embodiment, when the current user is the target user, the user demand information in the voice command is extracted, and then the user demand is converted into the feature signal.

[0069] The above embodiment provides an intelligent control method and device of air conditioning equipment, computer equipment and storage medium. Based on the signal acquisition module, the user demand is obtained and converted into the feature signal. Based on the feature signal, the data acquisition module is called to collect temperature data, wherein the temperature data includes human body temperature, indoor temperature and outdoor temperature. Based on the analysis result of the temperature data, a scheduling mode list of the air conditioning equipment is generated. Based on the user demand and the scheduling mode list, a target scheduling mode is determined to control the air conditioning equipment. After the feature signal is obtained by the signal acquisition module, the data acquisition module is called to collect real-time human body temperature, indoor and outdoor temperature data, which improves the portability of operation and ensures the real-time of data. Through algorithm analysis, each scheduling mode is obtained, and the target scheduling mode is determined combined with the user demand to control the air conditioning equipment, which improves the intelligence of controlling the air conditioning equipment, and further improves the intelligence and portability of the intelligent control of the air conditioning equipment.

[0070] Please refer to Figure 3 , Figure 3 is a schematic flow chart of a third embodiment of an intelligent control method of air conditioning equipment provided by the embodiments of the present application. The intelligent control method of air conditioning equipment can be applied to a server, after obtaining a feature signal, human body temperature, indoor and outdoor temperature information is obtained to obtain a scheduling mode for controlling the air conditioning equipment.

[0071] As Figure 3 shown, the step S103 of the intelligent control method of air conditioning equipment specifically includes steps S301 to S302.

[0072] S301, obtaining a target temperature weight value based on a preset weight ratio, a preset highest temperature table, a preset suitable temperature table, the human body temperature, the indoor temperature and the outdoor temperature.

[0073] Before obtaining the target temperature weight value based on the preset weight ratio, the preset highest temperature table, the preset suitable temperature table, the human body temperature, the indoor temperature and the outdoor temperature, further comprising: generating the preset highest temperature table based on the preset highest human body temperature, the preset highest indoor temperature and the preset highest outdoor temperature; generating the preset suitable temperature table based on the preset suitable human body temperature, the preset suitable indoor temperature and the preset suitable outdoor temperature.

[0074] In one embodiment, the preset indoor and outdoor highest temperatures and the preset highest human body temperature are collected to generate the preset highest temperature table, and the preset indoor and outdoor suitable temperatures and the preset suitable human body temperature are collected to generate the preset suitable temperature table.

[0075] Specifically, the human body temperature, the indoor temperature and the outdoor temperature are compared with the preset highest human body temperature, the preset highest indoor temperature and the preset highest outdoor temperature in the highest temperature table respectively, when the outdoor temperature and the human body temperature exceed the preset highest outdoor temperature, the human body temperature and the outdoor temperature are given higher weights, when the indoor temperature exceeds the preset highest indoor temperature, the indoor temperature is given a higher weight, and when the indoor temperature and the human body temperature exceed the preset highest temperature, the indoor temperature and the human body temperature are given higher weights.

[0076] In one embodiment, the target preset weight ratio is obtained by comparing the temperature data with each preset highest temperature respectively, and the difference between each temperature and the suitable temperature is obtained by difference calculation of the current temperature data and the suitable temperature, and the target temperature weight value is obtained by calculation according to the difference and the weight ratio.

[0077] S302, comparing the preset temperature weight threshold value with the target temperature weight value to generate the scheduling mode list.

[0078] In one embodiment, different scheduling modes correspond to different temperature weight threshold values, when the target temperature weight value obtained by calculation reaches a certain threshold value, the scheduling mode corresponding to the current threshold value is obtained as the target scheduling mode to control the air conditioning equipment.

[0079] Specifically, for example, the preset temperature threshold value and the corresponding scheduling mode are (1) less than 15, the scheduling mode is sleep mode; (2) greater than or equal to 15 and less than 20, the scheduling mode can be energy saving mode or sleep mode; (3) greater than or equal to 20, the scheduling mode can be fast cooling mode or energy saving mode or sleep mode. When the target temperature weight value obtained by calculation is 23, the scheduling mode list includes fast cooling mode, energy saving mode and sleep mode.

[0080] The intelligent control method, device, computer device and storage medium of the air conditioning equipment provided by the above embodiments generate the preset maximum temperature table based on the preset maximum human body temperature, the preset maximum indoor temperature and the preset maximum outdoor temperature; generate the preset suitable temperature table based on the preset suitable human body temperature, the preset suitable indoor temperature and the preset suitable outdoor temperature; obtain the target temperature weight based on the preset weight ratio, the preset maximum temperature table, the preset suitable temperature table, the human body temperature, the indoor temperature and the outdoor temperature; compare the preset temperature weight threshold with the target temperature weight to generate the scheduling mode list. The method compares the real-time collected temperature data with the preset maximum temperature to determine the target preset temperature weight ratio, and then determines the available target scheduling mode based on the difference between the preset suitable temperature and the current temperature data and the target temperature weight ratio, generates the target scheduling mode list, and improves the intelligence and portability of the control air conditioning equipment through algorithm analysis.

[0081] Please refer to Figure 4 , Figure 4 is a schematic flow chart of a fourth embodiment of an intelligent control method of an air conditioning equipment provided by the embodiments of the present application. The intelligent control method of the air conditioning equipment can be applied to a server, after obtaining a characteristic signal, the human body temperature, indoor and outdoor temperatures are information sources, and a scheduling mode is obtained to control the air conditioning equipment.

[0082] As Figure 4 indicated, the step S301 of the intelligent control method of the air conditioning equipment specifically includes steps S401 to S403.

[0083] S401, determine the target preset weight ratio based on the preset maximum temperature table, the human body temperature, the indoor temperature and the outdoor temperature.

[0084] In one embodiment, the human body temperature, the indoor temperature and the outdoor temperature are compared with the preset maximum human body temperature, the preset maximum indoor temperature and the preset maximum outdoor temperature in the maximum temperature table respectively. When the outdoor temperature and the human body temperature exceed the preset maximum outdoor temperature, the human body temperature and the outdoor temperature are given a higher weight. When the indoor temperature exceeds the preset maximum indoor temperature, the indoor temperature is given a higher weight. When the indoor temperature and the human body temperature exceed the preset maximum temperature, the indoor temperature and the human body temperature are given a higher weight.

[0085] Specifically, for example, when the outdoor temperature exceeds 40 degrees and the body surface temperature exceeds 37.8 degrees, the outdoor temperature and the body surface temperature weights account for 45% and 50% respectively, and the indoor temperature accounts for 5%; when the indoor temperature exceeds 30 degrees, the indoor temperature accounts for 70%, and the outdoor temperature and the body surface temperature account for 20% and 10% respectively; when the indoor temperature exceeds 30 degrees and the body surface temperature exceeds 37.8 degrees, the indoor temperature and the body surface temperature account for 45% and 50% respectively, and the outdoor temperature accounts for 5%.

[0086] S402, based on the preset suitable temperature table, the human body temperature, the indoor temperature and the outdoor temperature, generating a first difference value between the human body temperature and the preset human body suitable temperature, a second difference value between the indoor temperature and the preset indoor suitable temperature, and a third difference value between the outdoor temperature and the preset outdoor suitable temperature.

[0087] In one embodiment, the preset suitable temperature table includes a preset outdoor suitable temperature, a preset indoor suitable temperature and a preset human body suitable temperature, and the temperature data collected by the data collection module is calculated by difference with the suitable temperature to obtain the difference value between the human body temperature and the preset human body surface suitable temperature, the difference value between the indoor temperature and the preset indoor temperature, and the difference value between the outdoor temperature and the preset outdoor suitable temperature.

[0088] S403, based on the target preset weight ratio, the first difference value, the second difference value and the third difference value, generating the target temperature weight.

[0089] In one embodiment, the temperature difference value obtained by calculation is calculated by weight using the determined weight ratio to obtain the temperature weight. For example, assuming that the obtained target weight ratio is 45%, 50%, and the outdoor temperature accounts for 5%, the first, second and third difference values obtained by calculation are 20, 25 and 10 respectively, and the target temperature weight is 22.

[0090] The intelligent control method, device, computer equipment and storage medium of the air conditioning equipment provided by the above embodiments are based on a preset temperature maximum value table, the human body temperature, the indoor temperature and the outdoor temperature to determine a target preset weight ratio; based on the preset suitable temperature table, the human body temperature, the indoor temperature and the outdoor temperature, generating a first difference value between the human body temperature and the preset human body suitable temperature, a second difference value between the indoor temperature and the preset indoor suitable temperature, and a third difference value between the outdoor temperature and the preset outdoor suitable temperature; based on the target preset weight ratio, the first difference value, the second difference value and the third difference value, generating the target temperature weight. This method obtains the scheduling mode through algorithm analysis, determines the target scheduling mode in combination with user demand, controls the air conditioning equipment, improves the intelligence of controlling the air conditioning equipment, and further improves the intelligence and portability of the intelligent control of the air conditioning equipment.

[0091] Please refer to Figure 5 , Figure 5 An embodiment of the present application provides a schematic block diagram of an intelligent control device of an air conditioning equipment, which is used for executing the intelligent control method of the air conditioning equipment. The intelligent control device of the air conditioning equipment can be configured in a server.

[0092] As Figure 5 shown, the intelligent control device 500 of the air conditioning equipment comprises:

[0093] A feature signal obtaining module 501 is configured to obtain a user demand based on a signal acquisition module, and convert the user demand into a feature signal.

[0094] A temperature data collecting module 502 is configured to collect temperature data based on the feature signal by calling a data collecting module, wherein the temperature data comprises a human body temperature, an indoor temperature and an outdoor temperature.

[0095] A scheduling mode obtaining module 503 is configured to generate a scheduling mode list of the air conditioning equipment based on an analysis result of the temperature data.

[0096] An air conditioner control module 504 is configured to determine a target scheduling mode based on the user demand and the scheduling mode list, so as to control the air conditioning equipment.

[0097] In an embodiment, the feature signal obtaining module 501 comprises:

[0098] A voice command receiving unit is configured to determine a user identity by discriminating a voice command based on a preset timbre feature and a voice feature of the voice command when the signal acquisition module receives the voice command of the user.

[0099] A feature signal converting unit is configured to obtain a user demand based on the voice command, and convert the user demand into the feature signal when the user identity is a target user.

[0100] In an embodiment, the feature signal obtaining module 501 further comprises:

[0101] A device searching unit is configured to search a user device in a local area network when a device signal is received by the signal acquisition module.

[0102] An identification comparing unit is configured to extract a user device identification when the user device is searched, compare a target user device identification with the user device identification, and generate a comparison result.

[0103] The feature signal generation unit is configured to generate the feature signal when the comparison result is that the user equipment identifier is the same as the target user equipment identifier.

[0104] In one embodiment, the feature signal obtaining module 501 further comprises:

[0105] The remote command receiving unit is configured to extract a user demand in a remote command when the signal obtaining module receives the remote command, and convert the user demand into the feature signal.

[0106] In one embodiment, the scheduling mode obtaining module 503 comprises:

[0107] The target temperature weight obtaining unit is configured to obtain a target temperature weight based on a preset weight ratio, a preset maximum temperature table, a preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature.

[0108] The scheduling mode list generation unit is configured to compare a preset temperature weight threshold with the target temperature weight, and generate the scheduling mode list.

[0109] In one embodiment, the target temperature weight obtaining unit comprises:

[0110] The target weight ratio determining subunit is configured to determine a target preset weight ratio based on the preset maximum temperature table, the human body temperature, the indoor temperature, and the outdoor temperature.

[0111] The temperature difference value generation subunit is configured to generate a first difference value between the human body temperature and a preset suitable human body temperature, a second difference value between the indoor temperature and a preset suitable indoor temperature, and a third difference value between the outdoor temperature and a preset suitable outdoor temperature based on the preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature.

[0112] The target temperature weight generation subunit is configured to generate the target temperature weight based on the target preset weight ratio, the first difference value, the second difference value, and the third difference value.

[0113] In one embodiment, the scheduling mode obtaining module 503 further comprises:

[0114] The maximum temperature table generation subunit is configured to generate the preset maximum temperature table based on a preset maximum human body temperature, a preset maximum indoor temperature, and a preset maximum outdoor temperature.

[0115] The suitable temperature table generation subunit is configured to generate the preset suitable temperature table based on a preset suitable human body temperature, a preset suitable indoor temperature, and a preset suitable outdoor temperature.

[0116] It should be noted that, for the convenience and brevity of description, the specific working processes of the above-described apparatus and modules can be clearly understood by those skilled in the art, and the corresponding processes in the foregoing method embodiments can be referred to, which will not be described here.

[0117] The apparatus described above can be implemented in the form of a computer program, which can run on a computer device as shown in the specification. Figure 6

[0118] Please refer to Figure 6 , Figure 6 is a structural schematic block diagram of a computer device provided by an embodiment of the present application. The computer device can be a server.

[0119] Please refer to Figure 6 , the computer device includes a processor, a memory and a network interface connected through a system bus, wherein the memory can include a non-volatile storage medium and an internal memory.

[0120] The non-volatile storage medium can store an operating system and a computer program. The computer program includes program instructions which, when executed, can cause the processor to perform any kind of intelligent control method of an air conditioning device.

[0121] The processor is used to provide computing and control capabilities to support the operation of the entire computer device.

[0122] The internal memory provides an environment for the running of the computer program in the non-volatile storage medium, which, when executed by the processor, can cause the processor to perform any kind of intelligent control method of an air conditioning device.

[0123] The network interface is used for network communication, such as sending assigned tasks, etc. Those skilled in the art can understand that Figure 6 The structure shown in the specification is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. The specific computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0124] ​It should be appreciated that the processor can be a central processing unit (CPU), the processor can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic device, discrete hardware component, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0125] In one embodiment, the processor is configured to execute a computer program stored in the memory to implement the following steps:

[0126] The signal acquisition module is configured to obtain a user demand and convert the user demand into a feature signal.

[0127] The data acquisition module is configured to collect temperature data based on the feature signal, wherein the temperature data includes a human body temperature, an indoor temperature, and an outdoor temperature.

[0128] The analysis module is configured to generate a scheduling mode list of the air conditioning equipment based on an analysis result of the temperature data.

[0129] The control module is configured to determine a target scheduling mode based on the user demand and the scheduling mode list, and control the air conditioning equipment.

[0130] In one embodiment, when the processor implements the signal acquisition module to obtain a user demand and convert the user demand into a feature signal, the processor is configured to implement:

[0131] When the signal acquisition module receives a voice command of a user, the voice command is identified based on a preset timbre feature and a voice feature of the voice command to determine a user identity.

[0132] When the user identity is a target user, the user demand is obtained based on the voice command, and the user demand is converted into the feature signal.

[0133] In one embodiment, when the processor implements the signal acquisition module to obtain a user demand and convert the user demand into a feature signal, the processor is further configured to implement:

[0134] When the signal acquisition module receives a device signal, a user device is searched in a local area network.

[0135] When the user equipment is searched, a user equipment identifier is extracted, the target user equipment identifier is compared with the user equipment identifier, and a comparison result is generated;

[0136] When the comparison result is that the user equipment identifier is the same as the target user equipment identifier, the feature signal is generated.

[0137] In an embodiment, when the processor implements the signal acquisition module based on the signal, obtains the user demand, and converts the user demand into the feature signal, the processor is further configured to:

[0138] When the signal acquisition module receives a remote command, the user demand in the remote command is extracted, and the user demand is converted into the feature signal.

[0139] In an embodiment, when the processor generates the scheduling mode list of the air conditioning equipment based on the analysis result of the temperature data, the processor is configured to:

[0140] Based on a preset weight ratio, a preset maximum temperature table, a preset suitable temperature table, the body temperature, the indoor temperature, and the outdoor temperature, a target temperature weight value is obtained.

[0141] A preset temperature weight threshold value is compared with the target temperature weight value, and the scheduling mode list is generated.

[0142] In an embodiment, when the processor obtains the target temperature weight value based on the preset weight ratio, the preset maximum temperature table, the preset suitable temperature table, the body temperature, the indoor temperature, and the outdoor temperature, the processor is configured to:

[0143] Based on the preset maximum temperature table, the body temperature, the indoor temperature, and the outdoor temperature, a target preset weight ratio is determined.

[0144] Based on the preset suitable temperature table, the body temperature, the indoor temperature, and the outdoor temperature, a first difference between the body temperature and a preset suitable body temperature, a second difference between the indoor temperature and a preset suitable indoor temperature, and a third difference between the outdoor temperature and a preset suitable outdoor temperature are generated.

[0145] Based on the target preset weight ratio, the first difference, the second difference, and the third difference, the target temperature weight value is generated.

[0146] In an embodiment, before the processor obtains the target temperature weight value based on the preset weight ratio, the preset maximum temperature table, the preset suitable temperature table, the body temperature, the indoor temperature, and the outdoor temperature, the processor is further configured to:

[0147] generate the preset maximum temperature table based on a preset maximum human body temperature, a preset maximum indoor temperature, and a preset maximum outdoor temperature;

[0148] generate the preset suitable temperature table based on a preset suitable human body temperature, a preset suitable indoor temperature, and a preset suitable outdoor temperature.

[0149] The embodiments of the present application further provide a computer readable storage medium, which stores a computer program. The computer program includes program instructions. The processor executes the program instructions to implement the intelligent control method of any air conditioning equipment provided by the embodiments of the present application.

[0150] The computer readable storage medium can be an internal storage unit of the computer device, for example, a hard disk or a memory of the computer device. The computer readable storage medium can also be an external storage device of the computer device, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc.

[0151] The above merely describes the specific embodiments of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of various equivalent modifications or replacements within the technical range disclosed by the present application, and these modifications or replacements should be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A method for intelligent control of an air conditioning device, characterized in that, include: Based on the signal acquisition module, user needs are obtained and the user needs are converted into feature signals; Based on the aforementioned characteristic signal, the data acquisition module is invoked to collect temperature data, which includes human body temperature, indoor temperature, and outdoor temperature. Based on the analysis results of the temperature data, a list of scheduling modes for the air conditioning equipment is generated. Based on the user requirements and the list of scheduling modes, a target scheduling mode is determined to control the air conditioning equipment. The step of generating a scheduling mode list for air conditioning equipment based on the analysis results of the temperature data includes: The target temperature weight is obtained based on the preset weight ratio, the preset maximum temperature value table, the preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature. The preset temperature weight threshold is compared with the target temperature weight to generate the scheduling mode list; The step of obtaining the target temperature weight based on a preset weight ratio, a preset maximum temperature table, a preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature includes: Based on the preset maximum temperature value table, the human body temperature, the indoor temperature, and the outdoor temperature, a target preset weight ratio is determined; Based on the preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature, a first difference between the human body temperature and the preset suitable human body temperature, a second difference between the indoor temperature and the preset suitable indoor temperature, and a third difference between the outdoor temperature and the preset suitable outdoor temperature are generated. The target temperature weight is generated based on the target preset weight ratio, the first difference, the second difference, and the third difference; Before obtaining the target temperature weight based on a preset weight ratio, a preset maximum temperature table, a preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature, the method further includes: The preset maximum temperature value table is generated based on the preset maximum human body temperature, the preset maximum indoor temperature, and the preset maximum outdoor temperature. The preset suitable temperature table is generated based on preset suitable human body temperature, preset suitable indoor temperature, and preset suitable outdoor temperature.

2. The intelligent control method for air conditioning equipment according to claim 1, characterized in that, The signal acquisition module obtains user needs and converts those needs into feature signals, including: When the signal acquisition module receives a user's voice command, it judges the voice command based on preset timbre features and the voice features of the voice command to determine the user's identity; When the user is identified as the target user, the user's needs are obtained based on the voice command, and the user's needs are converted into the feature signal.

3. The intelligent control method for air conditioning equipment according to claim 1, characterized in that, The signal acquisition module, which obtains user needs and converts the user needs into feature signals, further includes: When the signal acquisition module receives a device signal, it searches for user equipment within the local area network; When the user equipment is found, the user equipment identifier is extracted, and the target user equipment identifier is compared with the user equipment identifier to generate a comparison result; When the comparison result shows that the user equipment identifier is the same as the target user equipment identifier, the feature signal is generated.

4. The intelligent control method for air conditioning equipment according to any one of claims 1-3, characterized in that, The signal acquisition module, which obtains user needs and converts the user needs into feature signals, further includes: When the signal acquisition module receives a remote command, it extracts the user requirements from the remote command and converts the user requirements into the feature signal.

5. An intelligent control device for an air conditioning unit, characterized in that, include: The feature signal acquisition module is used to obtain user needs based on the signal acquisition module and convert the user needs into feature signals. A temperature data acquisition module is used to collect temperature data based on the characteristic signal by calling the data acquisition module, wherein the temperature data includes human body temperature, indoor temperature and outdoor temperature; The scheduling mode acquisition module is used to generate a scheduling mode list for the air conditioning equipment based on the analysis results of the temperature data. An air conditioning control module is used to determine a target scheduling mode based on the user requirements and the scheduling mode list, so as to control the air conditioning equipment. The scheduling mode acquisition module includes: The target temperature weighting unit is used to obtain the target temperature weighting based on a preset weighting ratio, a preset maximum temperature value table, a preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature. The scheduling mode list generation unit is used to compare the preset temperature weight threshold with the target temperature weight to generate the scheduling mode list; The target temperature weighting unit includes: The target weight ratio determination subunit is used to determine the target preset weight ratio based on the preset maximum temperature value table, the human body temperature, the indoor temperature, and the outdoor temperature; The temperature difference generation subunit is used to generate a first difference between the human body temperature and the preset suitable human body temperature, a second difference between the indoor temperature and the preset suitable indoor temperature, and a third difference between the outdoor temperature and the preset suitable outdoor temperature based on the preset suitable temperature table, the human body temperature, the indoor temperature, and the outdoor temperature. The target temperature weighting generation subunit is used to generate the target temperature weighting value based on the target preset weighting ratio, the first difference, the second difference, and the third difference. The scheduling mode acquisition module further includes: The maximum temperature value generation subunit is used to generate the preset maximum temperature value table based on the preset maximum human body temperature, the preset maximum indoor temperature, and the preset maximum outdoor temperature. The suitable temperature table generation subunit is used to generate the preset suitable temperature table based on the preset suitable human body temperature, the preset suitable indoor temperature, and the preset suitable outdoor temperature.

6. A computer device, characterized in that, The computer device includes a memory and a processor; The memory is used to store computer programs; The processor is configured to execute the computer program and, in executing the computer program, implement the intelligent control method for the air conditioning equipment as described in any one of claims 1 to 4.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, causes the processor to implement the intelligent control method for the air conditioning equipment as described in any one of claims 1 to 4.

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