Air conditioner control method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides an air conditioner control method and device, electronic equipment and a storage medium, and relates to the technical field of smart home. The method comprises the steps that in response to a temperature control instruction sent by user equipment to an air conditioner, network signal parameters corresponding to network equipment are collected, the temperature control instruction is used for instructing the air conditioner to execute corresponding temperature control operation; performing feature extraction on the network signal parameters to obtain corresponding signal features; performing temperature analysis on the smart home environment according to the signal features to obtain a corresponding environment temperature of the smart home environment within a target time period after the current time point, the environment temperature changing along with the change of time or keeping unchanged; whether the air conditioner is subjected to temperature control or not is judged according to the environment temperature, so that the control cost of the air conditioner is reduced, and the control flexibility and real-time performance are improved.

Description

Technical Field

[0001] The present invention relates to the field of smart home technology, and in particular to a method for controlling an air conditioner, a control device for an air conditioner, an electronic device, and a computer-readable storage medium. Background Art

[0002] With the rapid development of smart home technology, home environment monitoring and automated control have become key factors in improving living comfort and energy efficiency. Existing ambient temperature detection mainly relies on physical sensors, such as thermometers and thermocouples, which usually need to be installed in specific locations, involving wiring, power supply and other issues, and are costly. At the same time, in the process of temperature control of air conditioners, it relies on manual operation by users or simple preset programs, which lacks flexibility and real-time performance. Summary of the invention

[0003] The embodiments of the present invention provide a control method, device, electronic device and computer-readable storage medium for an air conditioner to solve or partially solve the problems of high cost, poor control flexibility and real-time performance in the temperature control process of the air conditioner.

[0004] An embodiment of the present invention discloses a method for controlling an air conditioner, which is applied to a control system, wherein the control system is communicatively connected to a network device, an air conditioner, and a user device, and the control system, the network device, the air conditioner, and the user device are located in a smart home environment. The method includes:

[0005] In response to the user device sending a temperature control instruction to the air conditioner, collecting a network signal parameter corresponding to the network device, wherein the temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation;

[0006] Performing feature extraction on the network signal parameters to obtain corresponding signal features;

[0007] Performing temperature analysis on the smart home environment according to the signal characteristics to obtain the corresponding ambient temperature of the smart home environment in a target time period after a current time point, wherein the ambient temperature changes or remains unchanged over time;

[0008] Determine whether to perform temperature control on the air conditioner according to the ambient temperature.

[0009] In some feasible implementations, judging whether to perform temperature control on the air conditioner according to the ambient temperature includes:

[0010] Determining a temperature control range corresponding to the air conditioning control instruction;

[0011] The environmental change range is compared with the temperature control range, and whether to perform temperature control on the air conditioner is determined according to the comparison result.

[0012] In some feasible implementations, judging whether to perform temperature control on the air conditioner according to the comparison result includes:

[0013] If the ambient temperature is within the temperature control range, maintaining the air conditioning control instruction;

[0014] If the ambient temperature is outside the temperature control range, a temperature adjustment instruction for the air conditioner is generated, where the temperature adjustment instruction is used to instruct the air conditioner to perform a corresponding temperature control operation.

[0015] In some feasible implementations, if the ambient temperature is outside the temperature control range, generating a temperature adjustment instruction for the air conditioner includes:

[0016] If the ambient temperature is greater than the temperature control range, a temperature reduction instruction for the air conditioner is generated and sent to the air conditioner, wherein the temperature reduction instruction is used to instruct the air conditioner to perform a corresponding temperature reduction operation;

[0017] If the ambient temperature is less than the temperature control range, a temperature increase instruction for the air conditioner is generated and sent to the air conditioner, wherein the temperature increase instruction is used to instruct the air conditioner to perform a corresponding temperature increase operation.

[0018] Some possible implementations also include:

[0019] In response to generating the temperature adjustment instruction, generating a confirmation request corresponding to the temperature adjustment instruction, and sending the confirmation request to the user device, the confirmation request being used to prompt the user whether to execute the temperature adjustment instruction;

[0020] In response to receiving a confirmation message for the confirmation request, the temperature adjustment instruction is sent to the air conditioner.

[0021] In some feasible implementations, the signal feature includes at least one of signal strength, signal phase, channel state information, and frequency drift, and performing temperature analysis on the smart home environment according to the signal feature to obtain an ambient temperature corresponding to the smart home environment in a target time period after a current time point includes:

[0022] determining a temperature prediction model for the air conditioner;

[0023] Input at least one of the signal strength, the signal phase, the channel state information, and the frequency drift into the temperature prediction model to perform temperature analysis on the smart home environment to obtain the corresponding ambient temperature of the smart home environment in a target time period after the current time point.

[0024] In some feasible implementations, the collecting network signal parameters corresponding to the network device includes:

[0025] collecting a first network signal parameter between the network device and the air conditioner;

[0026] and / or, collecting a second network signal parameter between the network device and the user equipment;

[0027] And / or, collecting a third network signal parameter between the network device and the control system.

[0028] The embodiment of the present invention further discloses a control device for an air conditioner, which is applied to a control system, wherein the control system is communicatively connected to a network device, an air conditioner, and a user device, and the control system, the network device, the air conditioner, and the user device are located in a smart home environment. The device comprises:

[0029] a signal parameter acquisition module, configured to acquire network signal parameters corresponding to the network device in response to the user device sending a temperature control instruction to the air conditioner, wherein the temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation;

[0030] A feature extraction module, used to extract features of the network signal parameters to obtain corresponding signal features;

[0031] A temperature analysis module, used to perform temperature analysis on the smart home environment according to the signal characteristics, to obtain the ambient temperature of the smart home environment corresponding to a target time period after a current time point, wherein the ambient temperature changes or remains unchanged over time;

[0032] A control module is used to determine whether to perform temperature control on the air conditioner according to the ambient temperature.

[0033] In some feasible implementations, the control module is specifically used to:

[0034] Determining a temperature control range corresponding to the air conditioning control instruction;

[0035] The environmental change range is compared with the temperature control range, and whether to perform temperature control on the air conditioner is determined according to the comparison result.

[0036] In some feasible implementations, the control module is specifically used to:

[0037] If the ambient temperature is within the temperature control range, maintaining the air conditioning control instruction;

[0038] If the ambient temperature is outside the temperature control range, a temperature adjustment instruction for the air conditioner is generated, where the temperature adjustment instruction is used to instruct the air conditioner to perform a corresponding temperature control operation.

[0039] In some feasible implementations, the control module is specifically used to:

[0040] If the ambient temperature is greater than the temperature control range, a temperature reduction instruction for the air conditioner is generated and sent to the air conditioner, wherein the temperature reduction instruction is used to instruct the air conditioner to perform a corresponding temperature reduction operation;

[0041] If the ambient temperature is less than the temperature control range, a temperature increase instruction for the air conditioner is generated and sent to the air conditioner, wherein the temperature increase instruction is used to instruct the air conditioner to perform a corresponding temperature increase operation.

[0042] Some possible implementations also include:

[0043] a request sending module, configured to generate a confirmation request corresponding to the temperature adjustment instruction in response to generating the temperature adjustment instruction, and send the confirmation request to the user device, wherein the confirmation request is used to prompt the user whether to execute the temperature adjustment instruction;

[0044] The instruction sending module is used to send the temperature adjustment instruction to the air conditioner in response to receiving a confirmation message for the confirmation request.

[0045] In some feasible implementations, the signal feature includes at least one of signal strength, signal phase, channel state information, and frequency drift, and the temperature analysis module is specifically used for:

[0046] determining a temperature prediction model for the air conditioner;

[0047] Input at least one of the signal strength, the signal phase, the channel state information, and the frequency drift into the temperature prediction model to perform temperature analysis on the smart home environment to obtain the corresponding ambient temperature of the smart home environment in a target time period after the current time point.

[0048] In some feasible implementations, the signal parameter acquisition module is specifically used to:

[0049] collecting a first network signal parameter between the network device and the air conditioner;

[0050] and / or, collecting a second network signal parameter between the network device and the user equipment;

[0051] And / or, collecting a third network signal parameter between the network device and the control system.

[0052] The embodiment of the present invention further discloses an electronic device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0053] The memory is used to store computer programs;

[0054] The processor is used to implement the method described in the embodiment of the present invention when executing the program stored in the memory.

[0055] The embodiment of the present invention further discloses a computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, enables the processors to execute the method described in the embodiment of the present invention.

[0056] The embodiments of the present invention include the following advantages:

[0057] In an embodiment of the present invention, it can be applied to a control system, and the control system can be communicatively connected with a network device, an air conditioner, and a user device, etc. The control system, the network device, the air conditioner, and the user device are located in a smart home environment. During the operation of the air conditioner, the control system can respond to the user device sending a temperature control instruction to the air conditioner, collect network signal parameters corresponding to the network device, and the temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation, and then perform feature extraction on the network signal parameters to obtain corresponding signal features, and then perform temperature analysis on the smart home environment according to the signal features to obtain the corresponding ambient temperature of the smart home environment in a target time period after the current time point, and whether the ambient temperature changes or remains constant over time. unchanged, and then determine whether to control the temperature of the air conditioner according to the ambient temperature. Therefore, after the user controls the temperature of the air conditioner through the user device, the control system can determine whether the air conditioner needs further temperature control based on the characteristics corresponding to the network signal parameters. On the one hand, temperature detection based on network signals and temperature prediction using existing equipment can effectively reduce hardware and maintenance costs. On the other hand, determining whether temperature control is needed based on signal characteristics can effectively reduce the frequency of manual adjustment by users, improve the flexibility of device control, and at the same time ensure the real-time nature of device control. It also enables the air conditioner control to be adaptively adjusted as the ambient temperature changes, thereby improving the automation and intelligence of device control. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 is a flowchart of a method for controlling an air conditioner provided in an embodiment of the present invention;

[0059] Figure 2 is a schematic diagram of the flow of air conditioning control provided in an embodiment of the present invention;

[0060] Figure 3 is a structural block diagram of a control device for an air conditioner provided in an embodiment of the present invention;

[0061] Figure 4 It is a block diagram of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0062] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0063] As an example, with the rapid development of smart home technology, home environment monitoring and automated control have become key factors in improving living comfort and energy efficiency. Existing ambient temperature detection mainly relies on physical sensors, such as thermometers and thermocouples, which usually need to be installed in specific locations, involving wiring, power supply and other issues, and are costly. At the same time, in the process of temperature control of air conditioners, it relies on manual operation by users or simple preset programs, which lacks flexibility and real-time performance.

[0064] In this regard, in the present invention, it is applied to a control system, and the control system can be communicatively connected with network devices, air conditioners, and user devices. The control system, network devices, air conditioners, and user devices are located in a smart home environment. During the operation of the air conditioner, the control system can respond to the user device sending a temperature control instruction to the air conditioner, collect network signal parameters corresponding to the network device, and the temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation. Then, feature extraction is performed on the network signal parameters to obtain corresponding signal features, and then temperature analysis is performed on the smart home environment based on the signal features to obtain the corresponding ambient temperature of the smart home environment in a target time period after the current time point. The ambient temperature changes or remains unchanged over time. Change, and then determine whether to control the temperature of the air conditioner according to the ambient temperature. Therefore, after the user controls the temperature of the air conditioner through the user device, the control system can determine whether the air conditioner needs further temperature control based on the characteristics corresponding to the network signal parameters. On the one hand, temperature detection based on network signals and temperature prediction using existing equipment can effectively reduce hardware costs and maintenance costs. On the other hand, determining whether temperature control is needed based on signal characteristics can effectively reduce the frequency of manual adjustment by users, improve the flexibility of equipment control, and at the same time ensure the real-time performance of equipment control. It also allows the air conditioner control to be adaptively adjusted as the ambient temperature changes, thereby improving the automation and intelligence of equipment control.

[0065] Reference Figure 1 , shows a flowchart of a method for controlling an air conditioner provided in an embodiment of the present invention, which is applied to a control system, wherein the control system respectively communicates with a network device, an air conditioner, and a user device, and the control system, the network device, the air conditioner, and the user device are located in a smart home environment, and specifically may include the following steps:

[0066] Step 101, in response to the user device sending a temperature control instruction to the air conditioner, collecting network signal parameters corresponding to the network device, wherein the temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation;

[0067] In an embodiment of the present invention, for the control system, it can be the core of the smart home environment, responsible for coordinating and managing the operation of all devices. It can communicate with network devices, air conditioners, user devices, etc. through the network, and receive and send instructions; for network devices, it can be responsible for transmitting data and signals in the smart home environment, and can serve as a communication bridge between the control system, air conditioners and user devices to transmit instructions and data; for air conditioners, it can be a device for temperature adjustment in the smart home environment; for user devices, it can be the main tool for users to interact with the smart home system. For example, users can send corresponding temperature control instructions to the air conditioner through a mobile phone application, or receive the corresponding operating status and ambient temperature information of the air conditioner.

[0068] Optionally, the control system may be a central control device, or application software running on a corresponding device, etc., and the present invention is not limited to this.

[0069] In a specific implementation, the user can input temperature control operations for the air conditioner on the user device, such as setting the temperature, air volume, air outlet direction, etc. of the air conditioner. After the user device generates a temperature control instruction corresponding to the temperature control operation, the temperature control instruction can be sent to the air conditioner. After receiving the temperature control instruction, the air conditioner can perform the corresponding temperature control operation, such as operating according to the corresponding temperature, air volume and air outlet direction.

[0070] Furthermore, after the air conditioner has executed the temperature control command set by the user, since there are corresponding communication connections between the network device and the air conditioner, the network device and the user device, and the network device and the control system, the control system can collect the network signal parameters corresponding to the network device, so as to analyze the ambient temperature corresponding to the smart home environment through the network signal parameters.

[0071] It should be noted that the network signal parameters may be signal parameters corresponding to the WiFi signal. The control system may perform temperature detection based on the WiFi Sensing technology. Specifically, the WiFi signal may be affected by temperature changes when propagating in the environment. The ambient temperature of the smart home environment may be predicted by analyzing changes in the propagation characteristics of the network signal, thereby determining whether to adjust the temperature based on the prediction results.

[0072] In some feasible implementations, the control system can collect a first network signal parameter between the network device and the air conditioner; and / or collect a second network signal parameter between the network device and the user device; and / or collect a third network signal parameter between the network device and the control system, thereby predicting the ambient temperature based on the collected network signal parameters, and determining whether to perform temperature adjustment based on the prediction results. On the one hand, based on the network signal parameters between multiple devices, the data type is enriched and the accuracy of subsequent temperature predictions is improved. On the other hand, determining whether to perform temperature adjustment based on the predicted ambient temperature can effectively reduce manual adjustments and improve the flexibility of temperature control of the air conditioner.

[0073] Step 102, extracting features of the network signal parameters to obtain corresponding signal features;

[0074] In an embodiment of the present invention, after the corresponding network signal parameters are collected, the control system can input the network signal parameters into a pre-trained temperature prediction model for feature extraction, so as to perform temperature analysis based on the extracted signal features. The temperature prediction model can be a model trained based on the historically collected network signal parameters and the corresponding temperature data.

[0075] In some feasible implementations, network signal parameters may include signal strength, signal phase, channel state information, and frequency offset, among which, for signal strength (RSSI), temperature changes affect air density, resulting in changes in signal propagation path loss, manifested as RSSI fluctuations; for signal phase, temperature changes propagation speed, causing signal phase drift; for channel state information (CSI), temperature affects the amplitude and phase of subcarriers, especially multipath reflection characteristics (such as the strength of scattered signals); for frequency drift, temperature changes cause small frequency offsets in wireless signal propagation, etc. It should be noted that these changes are usually weak, and accurate data collection and processing methods are required to extract significant features that can characterize the essential information of the data.

[0076] In a specific implementation, a WiFi device that supports RSSI and CSI data collection (such as a wireless network card that supports the 802.11n / ac standard) can be used for data collection. The collected data can be used as training data for the temperature prediction model. During the data collection process, for signal strength, the received signal strength can be used as an indicator of signal path loss, for example:

[0077] RSSI(dB)=P t -L p

[0078] Among them, P t is the transmit power, L pis the path loss, which is affected by temperature

[0079] As for the channel state information, it may be fine-grained subcarrier channel information, including amplitude and phase.

[0080]

[0081] Among them, A i is the amplitude, θ i It's the phase.

[0082] In addition, it also includes the timestamp corresponding to the data collection, which is used to record the data time so as to perform timing analysis based on the timestamp.

[0083] Furthermore, corresponding data preprocessing can be performed on the collected raw data:

[0084] Use a filter (such as a low-pass filter) to remove high-frequency noise from the signal.

[0085] y[n]=α·x[n]+(1-α)·y[n-1]

[0086] Where x[n] is the input signal, y[n] is the filtered signal, and α is the filter coefficient.

[0087] And, by analyzing the subcarrier phase changes through phase unwrapping technology, capturing the phase drift caused by temperature

[0088] Δθ i =mod(θ i -θ i-1 +π,2π)-π

[0089] Next, combine the signal change characteristics to extract temperature-related features, including:

[0090] ①RSSI change characteristics:

[0091] Time series analysis: Calculate the moving average and change rate of RSSI, and record the RSSI change curve over time.

[0092] Fluctuation amplitude and frequency: Analyze the frequency and amplitude changes of RSSI fluctuations, and evaluate the impact of temperature changes on RSSI through statistical methods (such as standard deviation and extreme value difference).

[0093] ②Signal phase characteristics:

[0094] Phase change sequence: Use the phase information provided by the WiFi chip to solve the phase drift and analyze its change rate.

[0095] Phase difference analysis: Calculate the phase difference at different time points and extract the subtle phase drift characteristics caused by temperature changes.

[0096] ③CSI features:

[0097] Subcarrier Amplitude: Extract the amplitude values ​​of all subcarriers and analyze their sensitivity to temperature changes.

[0098] Frequency correlation: Analyze the changes in spectral characteristics between multiple subcarriers and extract the frequency distribution characteristics affected by temperature.

[0099] ④Frequency drift:

[0100] The signal is spectrally analyzed using a fast Fourier transform (FFT) to monitor the drift trend of the signal's main frequency. Specifically, the drift rate can be extracted as an indirect indicator of temperature change.

[0101] After the corresponding signal features are extracted through the above process, a relationship model between the signal features and the temperature can be constructed. Specifically, the model can be constructed through the following process:

[0102] ①Modeling method

[0103] Linear regression: In simple scenarios, there may be a linear relationship between RSSI or CSI changes and temperature changes.

[0104] Nonlinear model: In complex scenarios, machine learning methods such as support vector machine (SVM), neural network or decision tree are used to establish mapping models.

[0105] Time series analysis: For continuous changes in temperature, use time series models (such as ARIMA or LSTM) to capture dynamic relationships.

[0106] ②Calibration and training

[0107] Data calibration: Collect signal data under different temperature conditions to establish a basic training set.

[0108] Feature selection: Through feature importance analysis, signal features that are strongly correlated with temperature changes (such as the CSI amplitude of a specific subcarrier) are selected.

[0109] Through the above process, after the corresponding temperature prediction model is constructed, the control system can predict the temperature change based on the temperature prediction model, so as to control the air conditioner to perform corresponding equipment operations based on the prediction results.

[0110] For example, assume that the historical data shown in Table 1 below is collected:

[0111]

[0112] Table 1

[0113] Next, the signal strength, signal phase, CSI, frequency drift and temperature data can be normalized to the range of [0,1] so as to be input into the model for processing. The normalized data is shown in Table 2 below:

[0114]

[0115] Table 2

[0116] Furthermore, signal strength, signal phase, CSI and frequency drift can be extracted as input features, and temperature can be used as the output label. Then a simple linear regression model is selected for training. The linear regression model fits the relationship between the input features (signal strength, signal phase, CSI, frequency drift) and the output label (temperature) to obtain the corresponding temperature prediction model.

[0117] Step 103, performing temperature analysis on the smart home environment according to the signal characteristics to obtain the ambient temperature of the smart home environment corresponding to a target time period after the current time point, wherein the ambient temperature changes or remains unchanged over time;

[0118] After the control system inputs the network signal parameters into the temperature prediction model to extract the corresponding signal features, it can further perform temperature analysis on the smart home environment based on the extracted signal features to obtain the corresponding ambient temperature of the smart home environment in the target time period after the current time point, and the ambient temperature changes or remains unchanged over time. For example, assuming that the current analysis time point is T1, the control system can predict the ambient temperature in the smart home environment during the period of T1+ΔT based on the signal features, such as dividing T1+ΔT into three sub-time periods, T2, T3 and T4, corresponding to ambient temperatures of 22°C, 22°C and 21°C, respectively, so that temperature detection based on network signals and temperature prediction using existing equipment can effectively reduce hardware costs and maintenance costs.

[0119] In some feasible implementations, such as the above embodiments, the signal characteristics include at least one of signal strength, signal phase, channel state information and frequency drift. The control system can first determine a temperature prediction model that has been trained for the air conditioner, and then input at least one of the signal strength, signal phase, channel state information and frequency drift into the temperature prediction model to perform temperature analysis on the smart home environment, and obtain the corresponding ambient temperature of the smart home environment in the target time period after the current time point, thereby performing temperature detection based on the network signal and using existing equipment to perform temperature prediction, which can effectively reduce hardware costs and maintenance costs.

[0120] For example, assuming that the network signal parameters collected by the control system are signal strength: -51dBm, signal phase: 0.31rad, CSI: 0.81 and frequency drift: 0.011Hz, these signal parameters can be normalized and then input into the temperature prediction model to obtain the ambient temperature within a certain period of time after the current time point, such as the ambient temperature in the next 10 minutes is 24.9°C, etc., thereby performing temperature detection based on network signals and using existing equipment for temperature prediction, which can effectively reduce hardware costs and maintenance costs.

[0121] Step 104: determine whether to perform temperature control on the air conditioner according to the ambient temperature.

[0122] In an embodiment of the present invention, since the user has already performed temperature control on the air conditioner through the user device, the control system can first determine the temperature control range corresponding to the air conditioner control instruction, and then compare the environmental change range with the temperature control range, and determine whether to perform temperature control on the air conditioner according to the comparison result. Thus, after the user performs temperature control on the air conditioner through the user device, the control system can determine whether further temperature control of the air conditioner is required based on the characteristics corresponding to the network signal parameters. On the one hand, temperature detection based on network signals and temperature prediction using existing equipment can effectively reduce hardware and maintenance costs. On the other hand, determining whether temperature control is required based on signal characteristics can effectively reduce the frequency of manual adjustment by users, thereby improving the flexibility of device control, while ensuring the real-time nature of device control, and enabling the control of the air conditioner to be adaptively adjusted as the ambient temperature changes, thereby improving the automation and intelligence of device control.

[0123] In a specific implementation, if the ambient temperature is within the temperature control range, the air conditioning control instruction is maintained; if the ambient temperature is outside the temperature control range, a temperature adjustment instruction for the air conditioner is generated, and the temperature adjustment instruction is used to instruct the air conditioner to perform corresponding temperature control operations.

[0124] Specifically, if the ambient temperature is greater than the temperature control range, a temperature reduction instruction for the air conditioner is generated and sent to the air conditioner, and the temperature reduction instruction is used to instruct the air conditioner to perform the corresponding temperature reduction operation; if the ambient temperature is less than the temperature control range, a temperature increase instruction for the air conditioner is generated and sent to the air conditioner, and the temperature increase instruction is used to instruct the air conditioner to perform the corresponding temperature increase operation. Further, when it is determined that the air conditioner needs to be temperature controlled, the control system can also generate a confirmation request corresponding to the temperature adjustment instruction in response to the generation of the temperature adjustment instruction, and send the confirmation request to the user device, the confirmation request is used to prompt the user whether to execute the temperature adjustment instruction, and in response to receiving a confirmation message for the confirmation request, the temperature adjustment instruction is sent to the air conditioner, so that when it is detected that the temperature of the air conditioner needs to be adjusted, a confirmation request is initiated to the user first, while respecting the user's wishes, providing the user with good intelligent services, ensuring that the smart home environment is always within a comfortable range, and reducing the frequency of manual adjustment by the user.

[0125] In one example, for a temperature drop scenario:

[0126] Predicted temperature: 25.2℃

[0127] Judgment: 25.2℃>25℃

[0128] The control system generates the corresponding generation instructions:

[0129] Instruction type: Temperature reduction

[0130] Target temperature: 24℃

[0131] After confirmation by the user, the control system sends the command to the air conditioner. After receiving the command, the air conditioner performs the temperature reduction operation and adjusts the temperature to 24℃.

[0132] In another example, for a scenario with rising temperatures:

[0133] Predicted temperature: 22.8℃

[0134] Judgment: 22.8℃<23℃

[0135] The control system generates the corresponding generation instructions:

[0136] Instruction Type: Temperature Increase

[0137] Target temperature: 24℃

[0138] After confirmation by the user, the control system sends the command to the air conditioner. After receiving the command, the air conditioner performs the temperature increase operation and adjusts the temperature to 24℃.

[0139] It should be noted that the embodiments of the present invention include but are not limited to the above examples. It is understandable that those skilled in the art can also make settings according to actual needs under the guidance of the ideas of the embodiments of the present invention, and the present invention is not limited to this.

[0140] In an embodiment of the present invention, it can be applied to a control system, and the control system can be communicatively connected with a network device, an air conditioner, and a user device, etc. The control system, the network device, the air conditioner, and the user device are located in a smart home environment. During the operation of the air conditioner, the control system can respond to the user device sending a temperature control instruction to the air conditioner, collect network signal parameters corresponding to the network device, and the temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation, and then perform feature extraction on the network signal parameters to obtain corresponding signal features, and then perform temperature analysis on the smart home environment according to the signal features to obtain the corresponding ambient temperature of the smart home environment in a target time period after the current time point, and whether the ambient temperature changes or remains constant over time. unchanged, and then determine whether to control the temperature of the air conditioner according to the ambient temperature. Therefore, after the user controls the temperature of the air conditioner through the user device, the control system can determine whether the air conditioner needs further temperature control based on the characteristics corresponding to the network signal parameters. On the one hand, temperature detection based on network signals and temperature prediction using existing equipment can effectively reduce hardware and maintenance costs. On the other hand, determining whether temperature control is needed based on signal characteristics can effectively reduce the frequency of manual adjustment by users, improve the flexibility of device control, and at the same time ensure the real-time nature of device control. It also enables the air conditioner control to be adaptively adjusted as the ambient temperature changes, thereby improving the automation and intelligence of device control.

[0141] In order to enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the following examples are used for exemplary description:

[0142] Reference Figure 2 , shows a schematic diagram of the process of air conditioning control provided in an embodiment of the present invention, including:

[0143] Step 1: WiFi signal acquisition:

[0144] The system collects WiFi signal data through WiFi routers and receiving devices in the home environment (such as smartphones, tablets, smart speakers, etc.). When WiFi signals propagate in the environment, they are affected by temperature changes, such as slight changes in signal strength, phase, and frequency, which can be recorded by the receiving device.

[0145] Step 2: Signal processing and feature extraction:

[0146] The collected WiFi signal data needs to be pre-processed, such as noise filtering, signal enhancement, etc. Then, the system extracts the key features in the signal through feature extraction algorithms (such as Fourier transform, time domain feature extraction, etc.) to capture the change information related to the ambient temperature.

[0147] Step 3: Temperature detection model training:

[0148] The system matches historical WiFi signal features with corresponding temperature data and trains the temperature detection model through machine learning algorithms (such as support vector machines, neural networks, etc.). After training, the model can predict the ambient temperature in real time.

[0149] Step 4: Real-time temperature monitoring:

[0150] The system uses the trained model to analyze the real-time collected WiFi signals to obtain the current ambient temperature data. The temperature data can be updated at a certain frequency to ensure sensitive response to environmental changes.

[0151] Step 5: Automatic air conditioning temperature control:

[0152] The system compares the ambient temperature detected in real time with the target temperature range set by the user to determine whether the temperature setting of the air conditioner needs to be adjusted. When the ambient temperature exceeds the set range, the system will automatically adjust the operating status of the air conditioner through the control interface (such as infrared transmitter, Bluetooth module, etc.). For example, when the room temperature is detected to be rising, the system will automatically lower the temperature setting of the air conditioner; conversely, when the room temperature is detected to be falling, the system will increase the temperature setting of the air conditioner accordingly.

[0153] Step 6: User interaction and data feedback:

[0154] The system provides users with an interactive interface (such as a mobile app or smart home control center) through which users can view the current ambient temperature, air conditioning status, and historical temperature trends. At the same time, the system supports users to customize temperature control strategies, such as setting target temperature ranges, adjusting control sensitivity, and choosing to prioritize energy saving or comfort.

[0155] It should be noted that, for the sake of simplicity, the method embodiments are described as a series of action combinations, but those skilled in the art should be aware that the embodiments of the present invention are not limited by the order of the actions described, because according to the embodiments of the present invention, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily required by the embodiments of the present invention.

[0156] Reference Figure 3, shows a structural block diagram of an air conditioner control device provided in an embodiment of the present invention, which is applied to a control system, wherein the control system is communicatively connected to a network device, an air conditioner, and a user device, and the control system, the network device, the air conditioner, and the user device are located in a smart home environment, and may specifically include the following modules:

[0157] A signal parameter collection module 301, configured to collect network signal parameters corresponding to the network device in response to the user device sending a temperature control instruction to the air conditioner, wherein the temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation;

[0158] A feature extraction module 302 is used to extract features of the network signal parameters to obtain corresponding signal features;

[0159] The temperature analysis module 303 is used to perform temperature analysis on the smart home environment according to the signal characteristics, and obtain the corresponding ambient temperature of the smart home environment in a target time period after the current time point, and the ambient temperature changes or remains unchanged with time;

[0160] The control module 304 is used to determine whether to perform temperature control on the air conditioner according to the ambient temperature.

[0161] In some feasible implementations, the control module 304 is specifically configured to:

[0162] Determining a temperature control range corresponding to the air conditioning control instruction;

[0163] The environmental change range is compared with the temperature control range, and whether to perform temperature control on the air conditioner is determined according to the comparison result.

[0164] In some feasible implementations, the control module 304 is specifically configured to:

[0165] If the ambient temperature is within the temperature control range, maintaining the air conditioning control instruction;

[0166] If the ambient temperature is outside the temperature control range, a temperature adjustment instruction for the air conditioner is generated, where the temperature adjustment instruction is used to instruct the air conditioner to perform a corresponding temperature control operation.

[0167] In some feasible implementations, the control module 304 is specifically configured to:

[0168] If the ambient temperature is greater than the temperature control range, a temperature reduction instruction for the air conditioner is generated and sent to the air conditioner, wherein the temperature reduction instruction is used to instruct the air conditioner to perform a corresponding temperature reduction operation;

[0169] If the ambient temperature is less than the temperature control range, a temperature increase instruction for the air conditioner is generated and sent to the air conditioner, wherein the temperature increase instruction is used to instruct the air conditioner to perform a corresponding temperature increase operation.

[0170] Some possible implementations also include:

[0171] a request sending module, configured to generate a confirmation request corresponding to the temperature adjustment instruction in response to generating the temperature adjustment instruction, and send the confirmation request to the user device, wherein the confirmation request is used to prompt the user whether to execute the temperature adjustment instruction;

[0172] The instruction sending module is used to send the temperature adjustment instruction to the air conditioner in response to receiving a confirmation message for the confirmation request.

[0173] In some feasible implementations, the signal feature includes at least one of signal strength, signal phase, channel state information, and frequency drift, and the temperature analysis module 303 is specifically used for:

[0174] determining a temperature prediction model for the air conditioner;

[0175] Input at least one of the signal strength, the signal phase, the channel state information, and the frequency drift into the temperature prediction model to perform temperature analysis on the smart home environment to obtain the corresponding ambient temperature of the smart home environment in a target time period after the current time point.

[0176] In some feasible implementations, the signal parameter acquisition module 301 is specifically used for:

[0177] collecting a first network signal parameter between the network device and the air conditioner;

[0178] and / or, collecting a second network signal parameter between the network device and the user equipment;

[0179] And / or, collecting a third network signal parameter between the network device and the control system.

[0180] As for the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0181] In addition, an embodiment of the present invention further provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned air conditioner control method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0182] The embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each process of the above-mentioned air conditioner control method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0183] Figure 4 A schematic diagram of the hardware structure of an electronic device for implementing various embodiments of the present invention.

[0184] The electronic device 400 includes but is not limited to: a radio frequency unit 401, a network module 402, an audio output unit 403, an input unit 404, a sensor 405, a display unit 406, a user input unit 407, an interface unit 408, a memory 409, a processor 410, and a power supply 411. Those skilled in the art will appreciate that the electronic device structure involved in the embodiments of the present invention does not constitute a limitation on the electronic device, and the electronic device may include more or fewer components than shown in the figure, or combine certain components, or arrange components differently. In the embodiments of the present invention, the electronic device includes but is not limited to a mobile phone, a tablet computer, a laptop computer, a PDA, a vehicle-mounted terminal, a wearable device, and a pedometer.

[0185] It should be understood that in the embodiment of the present invention, the radio frequency unit 401 can be used for receiving and sending signals during information transmission or communication. Specifically, after receiving downlink data from the base station, it is sent to the processor 410 for processing; in addition, uplink data is sent to the base station. Generally, the radio frequency unit 401 includes but is not limited to an antenna, at least one amplifier, a transceiver, a coupler, a low noise amplifier, a duplexer, etc. In addition, the radio frequency unit 401 can also communicate with the network and other devices through a wireless communication system.

[0186] The electronic device provides users with wireless broadband Internet access through the network module 402, such as helping users to send and receive emails, browse web pages, and access streaming media.

[0187] The audio output unit 403 can convert the audio data received by the RF unit 401 or the network module 402 or stored in the memory 409 into an audio signal and output it as sound. Moreover, the audio output unit 403 can also provide audio output related to a specific function performed by the electronic device 400 (for example, a call signal reception sound, a message reception sound, etc.). The audio output unit 403 includes a speaker, a buzzer, a receiver, etc.

[0188] The input unit 404 is used to receive audio or video signals. The input unit 404 may include a graphics processor (GPU) 4041 and a microphone 4042, and the graphics processor 4041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The processed image frame can be displayed on the display unit 406. The image frame processed by the graphics processor 4041 can be stored in the memory 409 (or other storage medium) or sent via the radio frequency unit 401 or the network module 402. The microphone 4042 can receive sound and can process such sound into audio data. The processed audio data can be converted into a format output that can be sent to a mobile communication base station via the radio frequency unit 401 in the case of a telephone call mode.

[0189] The electronic device 400 also includes at least one sensor 405, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor and a proximity sensor, wherein the ambient light sensor can adjust the brightness of the display panel 4061 according to the brightness of the ambient light, and the proximity sensor can turn off the display panel 4061 and / or the backlight when the electronic device 400 is moved to the ear. As a type of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in each direction (generally three axes), and can detect the magnitude and direction of gravity when stationary, which can be used to identify the posture of the electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; the sensor 405 can also include a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, etc., which will not be repeated here.

[0190] The display unit 406 is used to display information input by the user or information provided to the user. The display unit 406 may include a display panel 4061, which may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0191] The user input unit 407 can be used to receive input digital or character information, and to generate key signal input related to user settings and function control of the electronic device. Specifically, the user input unit 407 includes a touch panel 4071 and other input devices 4072. The touch panel 4071, also known as a touch screen, can collect the user's touch operation on or near it (such as the user's operation on the touch panel 4071 or near the touch panel 4071 using any suitable object or accessory such as a finger, stylus, etc.). The touch panel 4071 may include two parts: a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch orientation, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into the contact point coordinates, and then sends it to the processor 410, receives the command sent by the processor 410 and executes it. In addition, the touch panel 4071 can be implemented using various types such as resistive, capacitive, infrared and surface acoustic waves. In addition to the touch panel 4071, the user input unit 407 may also include other input devices 4072. Specifically, other input devices 4072 may include but are not limited to a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and a joystick, which are not described in detail here.

[0192] Further, the touch panel 4071 may be covered on the display panel 4061. When the touch panel 4071 detects a touch operation on or near it, it is transmitted to the processor 410 to determine the type of the touch event, and then the processor 410 provides a corresponding visual output on the display panel 4061 according to the type of the touch event. It can be understood that in one embodiment, the touch panel 4071 and the display panel 4061 are used as two independent components to implement the input and output functions of the electronic device, but in some embodiments, the touch panel 4071 and the display panel 4061 can be integrated to implement the input and output functions of the electronic device, which is not limited here.

[0193] The interface unit 408 is an interface for connecting an external device to the electronic device 400. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device with an identification module, an audio input / output (I / O) port, a video I / O port, a headphone port, etc. The interface unit 408 may be used to receive input (e.g., data information, power, etc.) from an external device and transmit the received input to one or more elements within the electronic device 400 or may be used to transmit data between the electronic device 400 and an external device.

[0194] The memory 409 can be used to store software programs and various data. The memory 409 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function (such as a sound playback function, an image playback function, etc.), etc.; the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.), etc. In addition, the memory 409 can include a high-speed random access memory, and can also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0195] The processor 410 is the control center of the electronic device. It uses various interfaces and lines to connect various parts of the entire electronic device. It executes various functions of the electronic device and processes data by running or executing software programs and / or modules stored in the memory 409, and calling data stored in the memory 409, so as to monitor the electronic device as a whole. The processor 410 may include one or more processing units; preferably, the processor 410 may integrate an application processor and a modem processor, wherein the application processor mainly processes the operating system, user interface, and application programs, etc., and the modem processor mainly processes wireless communications. It is understandable that the above-mentioned modem processor may not be integrated into the processor 410.

[0196] The electronic device 400 may also include a power supply 411 (such as a battery) for supplying power to each component. Preferably, the power supply 411 may be logically connected to the processor 410 through a power management system, thereby implementing functions such as charging, discharging, and power consumption management through the power management system.

[0197] In addition, the electronic device 400 includes some functional modules not shown, which will not be described in detail here.

[0198] 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 device 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 device. 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 device including the element.

[0199] 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 ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present invention.

[0200] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation modes, which are merely illustrative rather than restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims, all of which are within the protection of the present invention.

[0201] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the embodiments of the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0202] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0203] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0204] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0205] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0206] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical disks.

[0207] The above is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for controlling an air conditioner, characterized in that: Applied to a control system, the control system is respectively connected to a network device, an air conditioner and a user device for communication, the control system, the network device, the air conditioner and the user device are located in a smart home environment, and the method comprises: In response to the user device sending a temperature control instruction to the air conditioner, collecting a network signal parameter corresponding to the network device, wherein the temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation; Performing feature extraction on the network signal parameters to obtain corresponding signal features; Performing temperature analysis on the smart home environment according to the signal characteristics to obtain the corresponding ambient temperature of the smart home environment in a target time period after a current time point, wherein the ambient temperature changes or remains unchanged over time; Determine whether to perform temperature control on the air conditioner according to the ambient temperature.

2. The method according to claim 1, characterized in that The determining whether to perform temperature control on the air conditioner according to the ambient temperature includes: Determining a temperature control range corresponding to the air conditioning control instruction; The environmental change range is compared with the temperature control range, and whether to perform temperature control on the air conditioner is determined according to the comparison result.

3. The method according to claim 2, characterized in that The step of judging whether to perform temperature control on the air conditioner according to the comparison result includes: If the ambient temperature is within the temperature control range, maintaining the air conditioning control instruction; If the ambient temperature is outside the temperature control range, a temperature adjustment instruction for the air conditioner is generated, where the temperature adjustment instruction is used to instruct the air conditioner to perform a corresponding temperature control operation.

4. The method according to claim 3, characterized in that If the ambient temperature is outside the temperature control range, generating a temperature adjustment instruction for the air conditioner includes: If the ambient temperature is greater than the temperature control range, a temperature reduction instruction for the air conditioner is generated and sent to the air conditioner, wherein the temperature reduction instruction is used to instruct the air conditioner to perform a corresponding temperature reduction operation; If the ambient temperature is less than the temperature control range, a temperature increase instruction for the air conditioner is generated and sent to the air conditioner, wherein the temperature increase instruction is used to instruct the air conditioner to perform a corresponding temperature increase operation.

5. The method according to any one of claims 1 to 4, characterized in that: Also includes: In response to generating the temperature adjustment instruction, generating a confirmation request corresponding to the temperature adjustment instruction, and sending the confirmation request to the user device, the confirmation request being used to prompt the user whether to execute the temperature adjustment instruction; In response to receiving a confirmation message for the confirmation request, the temperature adjustment instruction is sent to the air conditioner.

6. The method according to claim 1, characterized in that The signal feature includes at least one of signal strength, signal phase, channel state information, and frequency drift, and performing temperature analysis on the smart home environment according to the signal feature to obtain an ambient temperature corresponding to the smart home environment in a target time period after a current time point includes: determining a temperature prediction model for the air conditioner; Input at least one of the signal strength, the signal phase, the channel state information, and the frequency drift into the temperature prediction model to perform temperature analysis on the smart home environment to obtain the corresponding ambient temperature of the smart home environment in a target time period after the current time point.

7. The method according to claim 1, characterized in that The collecting of network signal parameters corresponding to the network device includes: collecting a first network signal parameter between the network device and the air conditioner; and / or, collecting a second network signal parameter between the network device and the user equipment; And / or, collecting a third network signal parameter between the network device and the control system.

8. A control device for an air conditioner, characterized in that: Applied to a control system, the control system is respectively connected to a network device, an air conditioner and a user device for communication, the control system, the network device, the air conditioner and the user device are located in a smart home environment, and the device comprises: a signal parameter acquisition module, configured to acquire network signal parameters corresponding to the network device in response to the user device sending a temperature control instruction to the air conditioner, wherein the temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation; A feature extraction module, used to extract features of the network signal parameters to obtain corresponding signal features; A temperature analysis module, used to perform temperature analysis on the smart home environment according to the signal characteristics, to obtain the ambient temperature of the smart home environment corresponding to a target time period after a current time point, wherein the ambient temperature changes or remains unchanged over time; A control module is used to determine whether to perform temperature control on the air conditioner according to the ambient temperature.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; The memory is used to store computer programs; The processor is used to implement the method according to any one of claims 1 to 7 when executing the program stored in the memory.

10. A computer-readable storage medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform the method according to any one of claims 1 to 7.

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