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

Abstract

Embodiments of the present application provide a kind of control method, device, electronic equipment and storage medium of air conditioner, related to smart home technical field, the method comprises: in response to user equipment has sent temperature control instruction to air conditioner, network signal parameter corresponding to network equipment is collected, temperature control instruction is used to indicate air conditioner to execute corresponding temperature control operation;Network signal parameter is extracted, and corresponding signal feature is obtained;According to signal feature, temperature analysis is carried out to smart home environment, and the corresponding environment temperature of smart home environment in target time period after current time point is obtained, and the change of environment temperature changes or remains unchanged with time;Whether temperature control is carried out to air conditioner according to environment temperature, to reduce the control cost of air conditioner, improve control flexibility and real-time performance.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of smart home, and in particular to a control method of an air conditioner, a control device of an air conditioner, an electronic device and a computer readable storage medium. BACKGROUND

[0002] With the rapid development of smart home technology, home environment monitoring and automatic control have become key factors to improve living comfort and energy efficiency. Existing environment temperature detection mainly relies on physical sensors such as thermometers, thermocouples, etc. These sensors usually need to be installed in a specific location, involving wiring, power supply, etc. and are relatively high in cost. At the same time, in the process of temperature control of the air conditioner, it depends on manual operation of the user or simple preset program, which lacks flexibility and real-time performance. SUMMARY

[0003] The embodiments of the present application provide a control method and device of an air conditioner, an electronic device and a computer readable storage medium 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] The embodiments of the present application disclose a control method of an air conditioner, applied to a control system, the control system is in communication connection with a network device, an air conditioner and a user device respectively, the control system, the network device, the air conditioner and the user device are located in a smart home environment, and the method comprises:

[0005] In response to the user device sending a temperature control instruction to the air conditioner, collecting network signal parameters corresponding to the network device, the temperature control instruction being used to instruct the air conditioner to execute corresponding temperature control operation;

[0006] Feature extraction is performed on the network signal parameters to obtain corresponding signal features;

[0007] According to the signal features, temperature analysis is performed on the smart home environment to obtain corresponding environment temperature of the smart home environment in a target time period after a current time point, and the environment temperature changes or remains unchanged with time;

[0008] According to the environment temperature, it is judged whether to perform temperature control on the air conditioner.

[0009] In some possible implementation manners, according to the environment temperature, it is judged whether to perform temperature control on the air conditioner, comprising:

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

[0011] The ambient temperature is compared with the temperature control range, and it is determined whether to control the air conditioner according to a comparison result.

[0012] In some possible implementation manners, the determining whether to control the air conditioner according to the comparison result includes:

[0013] If the ambient temperature is in the temperature control range, the temperature control instruction is maintained;

[0014] If the ambient temperature is out of 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 a corresponding temperature control operation.

[0015] In some possible implementation manners, the generating the temperature adjustment instruction for the air conditioner if the ambient temperature is out of the temperature control range includes:

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

[0018] In some possible implementation manners, the method further includes:

[0019] In response to generating the temperature adjustment instruction, a confirmation request corresponding to the temperature adjustment instruction is generated, and the confirmation request is sent to the user equipment, and the confirmation request is used to prompt a 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 possible implementation manners, the signal feature at least includes one of a signal strength, a signal phase, channel state information, and frequency drift, and the temperature analysis on the smart home environment according to the signal feature includes:

[0022] A temperature prediction model for the air conditioner is determined;

[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 a corresponding environment temperature of the smart home environment in a target time period after a current time point.

[0024] In some possible implementation manners, the collecting the network signal parameter corresponding to the network device comprises:

[0025] The first network signal parameter between the network device and the air conditioner is collected.

[0026] And / or, the second network signal parameter between the network device and the user device is collected.

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

[0028] The embodiment of the application further discloses a control device of an air conditioner, which is applied to a control system, and the control system, a network device, an air conditioner and a user device are in communication connection, the control system, the network device, the air conditioner and the user device are located in a smart home environment, and the device comprises:

[0029] A signal parameter collection module is configured to collect a network signal parameter corresponding to the network device in response to the user device sending a temperature control instruction to the air conditioner, and the temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation.

[0030] A feature extraction module is configured to perform feature extraction on the network signal parameter to obtain a corresponding signal feature.

[0031] A temperature analysis module is configured to perform temperature analysis on the smart home environment according to the signal feature to obtain a corresponding environment temperature of the smart home environment in a target time period after a current time point, and the environment temperature changes or remains unchanged with time.

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

[0033] In some possible implementation manners, the control module is specifically configured to:

[0034] Determine a temperature control range corresponding to the temperature control instruction.

[0035] Compare the environment temperature with the temperature control range, and determine whether to perform temperature control on the air conditioner according to a comparison result.

[0036] In some possible implementation manners, the control module is specifically configured to:

[0037] If the ambient temperature is within the temperature control range, the temperature control instruction is maintained.

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

[0039] In some possible implementation manners, the control module is specifically configured to:

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

[0042] In some possible implementation manners, the method further includes:

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

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

[0045] In some possible implementation manners, the signal feature at least includes one of a signal strength, a signal phase, channel state information, and frequency drift, and the temperature analysis module is specifically configured to:

[0046] determine 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 a corresponding ambient temperature of the smart home environment in a target time period after a current time point.

[0048] In some possible implementation manners, the signal parameter acquisition module is specifically configured to:

[0049] acquire a first network signal parameter between the network equipment and the air conditioner;

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

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

[0052] The embodiment of the application further discloses an electronic device, including a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory complete mutual communication through the communication bus.

[0053] The memory is used for storing a computer program.

[0054] The processor is used for executing the program stored on the memory, and realizes the method as described in the embodiment of the application.

[0055] The embodiment of the application further discloses a computer readable storage medium, which stores instructions, and when executed by one or more processors, causes the processor to execute the method as described in the embodiment of the application.

[0056] The embodiment of the application has the following advantages:

[0057] In the embodiment of the application, the control system can be applied to a control system, the control system can be connected 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. During operation of the air conditioner, the control system can collect a network signal parameter corresponding to the network device in response to the user device sending a temperature control instruction to the air conditioner. The temperature control instruction is used to instruct the air conditioner to perform a corresponding temperature control operation. Then, the network signal parameter is subjected to feature extraction to obtain a corresponding signal feature. Then, the smart home environment is subjected to temperature analysis according to the signal feature to obtain an environment temperature corresponding to the smart home environment in a target time period after a current time point. The environment temperature changes or remains unchanged with time. Then, whether to perform temperature control on the air conditioner is determined according to the environment temperature. Therefore, after the user performs temperature control on the air conditioner through the user device, the control system can determine whether to perform further temperature control on the air conditioner based on the features of the network signal parameter. On one hand, temperature detection is performed based on the network signal, temperature prediction is performed by using the existing device, and the hardware cost and maintenance cost can be effectively reduced. On the other hand, whether to perform temperature control is determined based on the signal feature, the frequency of manual adjustment of the user can be effectively reduced, the flexibility of device control is improved, the real-time performance of device control is ensured, the control of the air conditioner can be adaptively adjusted according to the change of the environment temperature, and the automation and intelligence of device control are improved. BRIEF DESCRIPTION OF DRAWINGS

[0058] Figure 1 is a step flow chart of a control method of an air conditioner provided in an embodiment of the present application;

[0059] Figure 2 is a flow chart of air conditioner control provided in an embodiment of the present application;

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

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

[0062] In order to make the above-mentioned objectives, features and advantages of the present application more apparent, comprehensible and easily understood, the present application will be 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 automatic control have become key factors to improve living comfort and energy efficiency. Existing environmental temperature detection mainly relies on physical sensors such as thermometers, thermocouples, etc. These sensors usually need to be installed in a specific location, involving wiring, power supply and other issues, and the cost is relatively high. At the same time, in the process of temperature control of the air conditioner, it depends on manual operation of the user or simple preset program, lacking flexibility and real-time performance.

[0064] In this invention, a control system is applied that can communicate with network devices, air conditioners, and user devices. These devices are located within a smart home environment. During air conditioner operation, the control system responds to temperature control commands sent by user devices to the air conditioner, collects network signal parameters from the network devices, and uses the temperature control commands to instruct the air conditioner to perform corresponding temperature control operations. Then, feature extraction is performed on the network signal parameters to obtain corresponding signal features. Based on these features, temperature analysis of the smart home environment is conducted to obtain the ambient temperature for a target time period following the current time point. The ambient temperature may change or remain constant over time. The system changes the ambient temperature and then determines whether to adjust the air conditioner's temperature accordingly. Thus, after the user adjusts the air conditioner's temperature using their device, the control system can determine whether further temperature control is needed based on the characteristics of the network signal parameters. On one hand, temperature detection based on network signals and temperature prediction using existing equipment effectively reduces hardware and maintenance costs. On the other hand, determining the need for temperature control based on signal characteristics effectively reduces the frequency of manual adjustments by the user, improving the flexibility of equipment control while ensuring real-time performance. Furthermore, it allows the air conditioner's control to adaptively adjust to changes in ambient temperature, enhancing the automation and intelligence of the equipment control.

[0065] Reference Figure 1 This diagram illustrates a flowchart of the steps of an air conditioner control method provided in an embodiment of the present invention. The method is applied to a control system, which establishes communication connections with a network device, an air conditioner, and a user device. The control system, the network device, the air conditioner, and the user device are located in a smart home environment. Specifically, the method may include the following steps:

[0066] Step 101: In response to the user equipment sending a temperature control command to the air conditioner, the network signal parameters corresponding to the network device are collected. The temperature control command is used to instruct the air conditioner to perform the corresponding temperature control operation.

[0067] In this embodiment of the invention, the control system 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 to receive and send instructions. The network devices can be responsible for transmitting data and signals in the smart home environment and can act as a communication bridge between the control system, air conditioners, and user devices to transmit instructions and data. The air conditioner can be a device for temperature regulation in the smart home environment. The user device 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 application, or receive the corresponding operating status and ambient temperature information of the air conditioner.

[0068] Optionally, the control system can be a central control device or application software running on the corresponding device, and the present invention does not limit it.

[0069] In practice, users can input temperature control operations for the air conditioner on their user devices, such as setting the air conditioner's temperature, air volume, and air outlet direction. After the user device generates the temperature control command corresponding to the temperature control operation, it can send the temperature control command to the air conditioner. After receiving the temperature control command, the air conditioner can execute 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 user-set temperature control command, 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 in order to analyze the ambient temperature of the smart home environment through the network signal parameters.

[0071] It should be noted that the network signal parameters can be the signal parameters corresponding to the WiFi signal. The control system can perform temperature detection based on WiFi Sensing technology. Specifically, WiFi signals are affected by temperature changes when propagating in the environment. Therefore, the ambient temperature of the smart home environment can be predicted by analyzing the changes in the propagation characteristics of the network signal, and then the temperature adjustment can be determined based on the prediction results.

[0072] In some feasible implementations, the control system can collect first network signal parameters between the network device and the air conditioner; and / or, collect second network signal parameters between the network device and the user equipment; and / or, collect third network signal parameters between the network device and the control system. Based on the collected network signal parameters, the control system can predict the ambient temperature and determine whether to adjust the temperature based on the prediction results. This approach enriches the data types based on network signal parameters from multiple devices, improving the accuracy of subsequent temperature predictions. Furthermore, determining whether to adjust the temperature based on the predicted ambient temperature effectively reduces manual adjustments and enhances the flexibility of air conditioner temperature control.

[0073] Step 102: Extract features from the network signal parameters to obtain the corresponding signal features;

[0074] In this embodiment of the invention, after acquiring the corresponding network signal parameters, 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 historically acquired network signal parameters and corresponding temperature data.

[0075] In some feasible implementations, network signal parameters can include signal strength, signal phase, channel state information (CSI), and frequency offset. For signal strength (RSSI), temperature changes affect air density, leading to variations in signal propagation path loss, manifesting as RSSI fluctuations. For signal phase, temperature alters propagation speed, causing phase drift. For CSI, temperature affects the amplitude and phase of subcarriers, particularly multipath reflection characteristics (such as the strength of scattered signals). For frequency drift, temperature changes cause minute frequency shifts in wireless signal propagation. It should be noted that these changes are usually subtle, requiring precise data acquisition and processing methods to extract salient features that characterize the essential information of the data.

[0076] In practical implementation, WiFi devices that support RSSI and CSI data acquisition (such as wireless network cards supporting the 802.11n / ac standard) can be used for data collection. The collected data is then used as training data for the temperature prediction model. During the data acquisition process, the received signal strength can be used as an indicator of signal path loss, for example:

[0077]

[0078] in, It's the transmission power. It is path loss, and path loss is affected by temperature.

[0079] Channel state information can be fine-grained subcarrier channel information, including amplitude and phase.

[0080]

[0081] in, It's the amplitude. It is a phase.

[0082] In addition, it includes the timestamp corresponding to the time of data collection, which is used to record the data time so that time-series analysis can be performed based on the timestamp.

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

[0084] High-frequency noise in a signal can be eliminated by using filters (such as low-pass filters).

[0085]

[0086] in It is the input signal. It is the filtered signal. These are the filter coefficients.

[0087] Furthermore, phase unwrapping techniques are used to analyze subcarrier phase changes and capture temperature-induced phase drift.

[0088]

[0089] Next, based on the signal change characteristics, temperature-related features are extracted, including:

[0090] ① RSSI variation characteristics:

[0091] Time series analysis: Calculate the moving average and rate of change 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 using statistical methods (such as standard deviation and extreme value difference).

[0093] ②Signal phase characteristics:

[0094] Phase change sequence: Using the phase information provided by the WiFi chip, the phase drift is calculated and its rate of change is analyzed.

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

[0096] ③CSI characteristics:

[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 among multiple subcarriers and extract the frequency distribution characteristics affected by temperature.

[0099] ④ Frequency drift:

[0100] The Fast Fourier Transform (FFT) is used to perform spectral analysis on the signal to monitor the drift trend of the signal's dominant frequency. Specifically, the drift rate can be extracted as an indirect indicator of temperature change.

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

[0102] ① Modeling methods

[0103] Linear regression: In simple scenarios, changes in RSSI or CSI may have a linear relationship with changes in temperature.

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

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

[0106] ② Calibration 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] After constructing the corresponding temperature prediction model through the above process, the control system can predict temperature changes 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, suppose the historical data shown in Table 1 below was collected:

[0111]

[0112] Table 1

[0113] Next, the signal strength, signal phase, CSI, frequency drift, and temperature data can be normalized to the range [0, 1] for input into the model for processing. The normalized data are 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 as the output label. Then, a simple linear regression model is selected for training. The linear regression model obtains the corresponding temperature prediction model by fitting the relationship between the input features (signal strength, signal phase, CSI, frequency drift) and the output label (temperature).

[0117] Step 103: Perform temperature analysis on the smart home environment based on the signal characteristics to obtain the ambient temperature of the smart home environment in the target time period after the current time point. The ambient temperature may change or remain unchanged over time.

[0118] After the control system inputs network signal parameters into the temperature prediction model to extract the corresponding signal features, it can further analyze the temperature of the smart home environment based on the extracted signal features. This allows it to obtain the ambient temperature of the smart home environment within a target time period after the current time point, where the ambient temperature may change or remain constant over time. For example, assuming the current analysis time point is T1, the control system can predict the ambient temperature in the smart home environment during the time period T1+ΔT based on the signal features. If T1+ΔT is divided into three sub-time periods, T2, T3, and T4, the corresponding ambient temperatures are 22℃, 22℃, and 21℃, respectively. Therefore, by using network signals for temperature detection and existing equipment for temperature prediction, hardware and maintenance costs can be effectively reduced.

[0119] In some feasible implementations, such as the above embodiment, the signal characteristics include at least one of signal strength, signal phase, channel state information, and frequency drift. The control system can first determine the already trained temperature prediction model for the air conditioner, and then use at least one of the signal strength, signal phase, channel state information, and frequency drift as input to the temperature prediction model to analyze the temperature of the smart home environment, and obtain the ambient temperature of the smart home environment in the target time period after the current time point. Thus, temperature detection is performed based on network signals, and temperature prediction is performed using existing equipment, which can effectively reduce hardware costs and maintenance costs.

[0120] For example, assuming 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 time period after the current time point, such as the ambient temperature within the next 10 minutes being 24.9℃. Thus, temperature detection can be performed based on network signals, and temperature prediction can be performed using existing equipment, which can effectively reduce hardware and maintenance costs.

[0121] Step 104: Determine whether to control the temperature of the air conditioner based on the ambient temperature.

[0122] In this embodiment of the invention, since the user has already controlled the temperature of the air conditioner through the user device, the control system can first determine the temperature control range corresponding to the temperature control command, then compare the ambient temperature with the temperature control range, and determine whether to control the temperature of the air conditioner based on the comparison result. Thus, after the user controls the temperature of the air conditioner through the user device, the control system can determine whether further temperature control of the air conditioner is needed 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 the user, improve the flexibility of equipment control, ensure the real-time performance of equipment control, and enable the air conditioner control to adaptively adjust with changes in ambient temperature, thereby improving the automation and intelligence of equipment control.

[0123] In practice, if the ambient temperature is within the temperature control range, the temperature control command is maintained; if the ambient temperature is outside the temperature control range, a temperature adjustment command for the air conditioner is generated, which instructs the air conditioner to perform the corresponding temperature control operation.

[0124] Specifically, if the ambient temperature is higher than the temperature control range, a temperature reduction command is generated for the air conditioner and sent to it, instructing the air conditioner to perform the corresponding temperature reduction operation. If the ambient temperature is lower than the temperature control range, a temperature increase command is generated for the air conditioner and sent to it, instructing it to perform the corresponding temperature increase operation. Furthermore, when it is determined that temperature control of the air conditioner is required, the control system can also generate a confirmation request corresponding to the temperature adjustment command and send the confirmation request to the user device. The confirmation request prompts the user whether to execute the temperature adjustment command. Upon receiving a confirmation message for the confirmation request, the control system sends the temperature adjustment command to the air conditioner. Thus, when it detects that the air conditioner temperature needs adjustment, it prioritizes initiating a confirmation request to the user, respecting the user's wishes while providing excellent intelligent services, ensuring that the smart home environment is always within a comfortable range, and reducing the frequency of manual adjustments by the user.

[0125] In one example, for a scenario where the temperature decreases:

[0126] Predicted temperature: 25.2℃

[0127] Judgment: 25.2℃>25℃

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

[0129] Command type: Temperature reduction

[0130] Target temperature: 24℃

[0131] After user confirmation, the control system sends a command to the air conditioner. Upon receiving the command, the air conditioner performs a temperature reduction operation, adjusting the temperature to 24°C.

[0132] In another example, for a scenario where the temperature rises:

[0133] Predicted temperature: 22.8℃

[0134] Judgment: 22.8℃<23℃

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

[0136] Command type: Temperature increase

[0137] Target temperature: 24℃

[0138] After user confirmation, the control system sends a command to the air conditioner. Upon receiving the command, the air conditioner performs a temperature increase operation, adjusting the temperature to 24°C.

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

[0140] In this embodiment of the invention, it can be applied to a control system. The control system can communicate 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 command to the air conditioner, collect the network signal parameters corresponding to the network device, and use the temperature control command to instruct the air conditioner to perform the corresponding temperature control operation. Then, feature extraction is performed on the network signal parameters to obtain the corresponding signal features. Then, temperature analysis is performed on the smart home environment based on the signal features to obtain the ambient temperature of the smart home environment within a target time period after the current time point. The ambient temperature changes or remains constant over time. The system remains unchanged, and then determines whether to control the air conditioner's temperature based on the ambient temperature. Thus, after the user controls the air conditioner's temperature through their device, the control system can determine whether further temperature control is needed based on the characteristics of 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 adjustments by the user, improve the flexibility of equipment control, ensure the real-time performance of equipment control, and enable the air conditioner's control to adaptively adjust to changes in ambient temperature, thereby improving the automation and intelligence of equipment control.

[0141] To enable those skilled in the art to better understand the technical solutions in the embodiments of the present invention, the following examples are provided for illustrative purposes:

[0142] Reference Figure 2 The diagram illustrates a flow chart 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 (such as smartphones, tablets, and smart speakers) in the home environment. WiFi signals are affected by temperature changes when propagating in the environment, resulting in minute changes in signal strength, phase, and frequency. These changes can be recorded by the receiving device.

[0145] Step 2: Signal Processing and Feature Extraction

[0146] The collected WiFi signal data needs to undergo preprocessing, such as noise filtering and signal enhancement. Then, the system uses feature extraction algorithms (such as Fourier transform and time-domain feature extraction) to extract key features from the signal in order to capture information about changes related to ambient temperature.

[0147] Step 3: Temperature detection model training:

[0148] The system matches historical WiFi signal characteristics with corresponding temperature data and trains a temperature detection model using machine learning algorithms (such as support vector machines and neural networks). Once trained, the model can predict ambient temperature in real time.

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

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

[0151] Step 5: Automatic temperature control by the air conditioner:

[0152] The system compares the real-time detected ambient temperature with the user-defined target temperature range to determine whether the air conditioner's temperature setting needs adjustment. When the ambient temperature exceeds the set range, the system automatically adjusts the air conditioner's operating status via a control interface (such as an infrared transmitter or Bluetooth module). For example, when the system detects an increase in room temperature, it automatically lowers the air conditioner's temperature setting; conversely, when it detects a decrease in room temperature, it raises the air conditioner's temperature setting accordingly.

[0153] Step 6: User Interaction and Data Feedback

[0154] The system provides users with an interactive interface (such as a mobile application or smart home control center) through which they can view the current ambient temperature, air conditioning status, and historical temperature trends. Simultaneously, the system supports user-defined temperature control strategies, such as setting target temperature ranges, adjusting control sensitivity, and selecting options to prioritize energy saving or comfort.

[0155] It should be noted that, for the sake of simplicity, the method embodiments are all described as a series of actions. However, those skilled in the art should understand that the embodiments of the present invention are not limited to the described order of actions, because according to the embodiments of the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions involved are not necessarily essential to the embodiments of the present invention.

[0156] Reference Figure 3This diagram illustrates a structural block diagram of an air conditioner control device provided in an embodiment of the present invention. The device is applied to a control system, which establishes communication connections with a network device, an air conditioner, and a user device. The control system, the network device, the air conditioner, and the user device are located in a smart home environment, and the device may specifically include the following modules:

[0157] The signal parameter acquisition module 301 is used to acquire network signal parameters corresponding to the network device in response to the user equipment sending a temperature control command to the air conditioner. The temperature control command is used to instruct the air conditioner to perform the corresponding temperature control operation.

[0158] Feature extraction module 302 is used to extract features from the network signal parameters to obtain corresponding signal features;

[0159] Temperature analysis module 303 is used to perform temperature analysis on the smart home environment based on the signal characteristics, and obtain the ambient temperature of the smart home environment in a target time period after the current time point, wherein the ambient temperature changes or remains unchanged over time.

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

[0161] In some feasible implementations, the control module 304 is specifically used for:

[0162] Determine the temperature control range corresponding to the temperature control command;

[0163] The ambient temperature is compared with the temperature control range, and a decision is made based on the comparison result as to whether to control the temperature of the air conditioner.

[0164] In some feasible implementations, the control module 304 is specifically used for:

[0165] If the ambient temperature is within the temperature control range, then the temperature control command is maintained;

[0166] If the ambient temperature is outside the temperature control range, a temperature adjustment command is generated for the air conditioner, which instructs the air conditioner to perform the corresponding temperature control operation.

[0167] In some feasible implementations, the control module 304 is specifically used for:

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

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

[0170] Among some feasible implementation methods are:

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

[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 characteristics include 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] Determine the temperature prediction model for the air conditioner;

[0175] The temperature prediction model is input with at least one of the signal strength, signal phase, channel state information, and frequency drift to perform temperature analysis on the smart home environment, thereby obtaining the ambient temperature of the smart home environment within 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] Collect the first network signal parameters between the network device and the air conditioner;

[0178] And / or, collect second network signal parameters between the network device and the user equipment;

[0179] And / or, acquire third network signal parameters between the network device and the control system.

[0180] As the device embodiment is basically similar to the method embodiment, the description is relatively simple, and relevant parts can be found in the description of the method embodiment.

[0181] In addition, this invention also 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, it implements the various processes of the above-described air conditioner control method embodiments and achieves the same technical effect. To avoid repetition, it will not be described again here.

[0182] This invention also provides a computer-readable storage medium storing a computer program. When executed by a processor, the computer program implements the various processes of the above-described air conditioner control method embodiments and achieves the same technical effects. To avoid repetition, it will not be described again here. The computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[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, components such as: 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 understand that the electronic device structure involved in the embodiments of the present invention does not constitute a limitation on the electronic device. An electronic device may include more or fewer components than illustrated, or combine certain components, or have different component arrangements. In the embodiments of the present invention, the electronic device includes, but is not limited to, mobile phones, tablet computers, laptop computers, PDAs, in-vehicle terminals, wearable devices, and pedometers.

[0185] It should be understood that, in this embodiment of the invention, the radio frequency unit 401 can be used for receiving and transmitting signals during information transmission or calls. Specifically, it receives downlink data from the base station and processes it with the processor 410; additionally, it transmits uplink data to the base station. Typically, 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. Furthermore, the radio frequency unit 401 can also communicate with networks and other devices through a wireless communication system.

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

[0187] The audio output unit 403 can convert audio data received by the radio frequency unit 401 or the network module 402 or stored in the memory 409 into audio signals and output them as sound. Furthermore, the audio output unit 403 can also provide audio output related to specific functions performed by the electronic device 400 (e.g., call signal reception sound, message reception sound, etc.). The audio output unit 403 includes a speaker, a buzzer, and a receiver, etc.

[0188] Input unit 404 is used to receive audio or video signals. Input unit 404 may include a graphics processing unit (GPU) 4041 and a microphone 4042. The GPU 4041 processes image data of still images or videos acquired by an image capture device (such as a camera) in video capture mode or image capture mode. The processed image frames can be displayed on display unit 406. The image frames processed by GPU 4041 can be stored in memory 409 (or other storage media) or transmitted via radio frequency unit 401 or network module 402. Microphone 4042 can receive sound and process such sound into audio data. The processed audio data can be converted into a format that can be transmitted to a mobile communication base station via radio frequency unit 401 in 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. The ambient light sensor can adjust the brightness of the display panel 4061 according to the ambient light level, and the proximity sensor can turn off the display panel 4061 and / or backlight when the electronic device 400 is moved to the ear. As a type of motion sensor, an accelerometer sensor can detect the magnitude of acceleration in various directions (generally three axes). When stationary, it can detect the magnitude and direction of gravity and can be used to identify the posture of the electronic device (such as landscape / portrait switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc. The sensor 405 may also include a fingerprint sensor, pressure sensor, iris sensor, molecular sensor, gyroscope, barometer, hygrometer, thermometer, infrared sensor, etc., which will not be described in detail 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] User input unit 407 can be used to receive input numerical or character information, and to generate key signal inputs related to user settings and function control of electronic devices. Specifically, user input unit 407 includes a touch panel 4071 and other input devices 4072. Touch panel 4071, also known as a touch screen, can collect touch operations performed by the user on or near it (such as operations performed by the user using a finger, stylus, or any suitable object or accessory on or near touch panel 4071). Touch panel 4071 may include two parts: a touch detection device and a touch controller. The touch detection device detects the user's touch position and the signal generated by the touch operation, and transmits the signal to the touch controller; the touch controller receives touch information from the touch detection device, converts it into touch point coordinates, and sends it to the processor 410, which receives and executes commands from the processor 410. In addition, touch panel 4071 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. Besides touch panel 4071, user input unit 407 may also include other input devices 4072. Specifically, other input devices 4072 may include, but are not limited to, physical keyboards, function keys (such as volume control buttons, power buttons, etc.), trackballs, mice, joysticks, etc., which will not be described in detail here.

[0192] Furthermore, the touch panel 4071 can cover the display panel 4061. When the touch panel 4071 detects a touch operation on or near it, it transmits the information to the processor 410 to determine the type of touch event. Subsequently, the processor 410 provides corresponding visual output on the display panel 4061 according to the type of touch event. It is understood that in one embodiment, the touch panel 4071 and the display panel 4061 are implemented as two independent components to realize the input and output functions of the electronic device. However, in some embodiments, the touch panel 4071 and the display panel 4061 can be integrated to realize the input and output functions of the electronic device. The specific implementation is not limited here.

[0193] Interface unit 408 serves as an interface for connecting external devices to electronic device 400. For example, external devices may include a wired or wireless headphone 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, and so on. Interface unit 408 can be used to receive input from external devices (e.g., data, power, etc.) and transmit the received input to one or more components within electronic device 400, or it can be used to transmit data between electronic device 400 and external devices.

[0194] The memory 409 can be used to store software programs and various data. The memory 409 may primarily include a program storage area and a data storage area. The program storage area may store the operating system, applications required for at least one function (such as sound playback, image playback, etc.), etc.; the data storage area may store data created based on the use of the mobile phone (such as audio data, phonebook, etc.). Furthermore, the memory 409 may include high-speed random access memory, and may also include non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0195] The processor 410 is the control center of the electronic device. It connects various parts of the electronic device via various interfaces and lines. By running or executing software programs and / or modules stored in the memory 409, and by calling data stored in the memory 409, it performs various functions and processes data, thereby providing overall monitoring of the electronic device. The processor 410 may include one or more processing units; preferably, the processor 410 may integrate an application processor and a modem processor. The application processor mainly handles the operating system, user interface, and applications, while the modem processor mainly handles wireless communication. It is understood that the 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) that supplies power to various components. Preferably, the power supply 411 can be logically connected to the processor 410 through a power management system, thereby enabling functions such as managing charging, discharging, and power consumption 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 document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0199] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0200] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

[0201] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

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

[0203] In the embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

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

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

[0206] If the aforementioned functions are implemented as 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 this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0207] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for controlling an air conditioner, characterized in that, An application is made in 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: In response to the user equipment sending a temperature control command to the air conditioner, the network signal parameters corresponding to the network device are collected, and the temperature control command is used to instruct the air conditioner to perform the corresponding temperature control operation; Feature extraction is performed on the network signal parameters to obtain the corresponding signal features; Based on the signal characteristics, the temperature of the smart home environment is analyzed to obtain the ambient temperature of the smart home environment within a target time period after the current time point. The ambient temperature may change or remain unchanged over time. Determine whether to control the temperature of the air conditioner based on the ambient temperature. The signal characteristics include at least one of signal strength, signal phase, channel state information, and frequency drift. The step of performing temperature analysis on the smart home environment based on the signal characteristics to obtain the ambient temperature of the smart home environment within a target time period after the current time point includes: Determine the temperature prediction model for the air conditioner; The temperature prediction model is input with at least one of the signal strength, signal phase, channel state information, and frequency drift to perform temperature analysis on the smart home environment, thereby obtaining the ambient temperature of the smart home environment within a target time period after the current time point.

2. The method according to claim 1, characterized in that, The step of determining whether to control the temperature of the air conditioner based on the ambient temperature includes: Determine the temperature control range corresponding to the temperature control command; The ambient temperature is compared with the temperature control range, and a decision is made based on the comparison result as to whether to control the temperature of the air conditioner.

3. The method according to claim 2, characterized in that, The step of determining whether to control the temperature of the air conditioner based on the comparison result includes: If the ambient temperature is within the temperature control range, then the temperature control command is maintained; If the ambient temperature is outside the temperature control range, a temperature adjustment command is generated for the air conditioner, which instructs the air conditioner to perform the corresponding temperature control operation.

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

5. The method according to claim 3 or 4, characterized in that, Also includes: In response to generating the temperature adjustment command, a confirmation request corresponding to the temperature adjustment command is generated and sent to the user equipment. The confirmation request is used to prompt the user whether to execute the temperature adjustment command. In response to receiving a confirmation message for the confirmation request, the temperature adjustment command is sent to the air conditioner.

6. The method according to claim 1, characterized in that, The collection of network signal parameters corresponding to the network device includes: Collect the first network signal parameters between the network device and the air conditioner; And / or, collect second network signal parameters between the network device and the user equipment; And / or, acquire third network signal parameters between the network device and the control system.

7. A control device for an air conditioner, characterized in that, An application in a control system, wherein the control system is communicatively connected to a network device, an air conditioner, and a user device, wherein the control system, the network device, the air conditioner, and the user device are located in a smart home environment, the device comprising: The signal parameter acquisition module is used to acquire network signal parameters corresponding to the network device in response to the user equipment sending a temperature control command to the air conditioner. The temperature control command is used to instruct the air conditioner to perform the corresponding temperature control operation. The feature extraction module is used to extract features from the network signal parameters to obtain the corresponding signal features; The temperature analysis module is used to perform temperature analysis on the smart home environment based on the signal characteristics, and obtain the ambient temperature of the smart home environment in a target time period after the current time point. The ambient temperature may change or remain unchanged over time. The control module is used to determine whether to control the temperature of the air conditioner based on the ambient temperature. The signal characteristics include at least one of signal strength, signal phase, channel state information, and frequency drift. The temperature analysis module is specifically used for: Determine the temperature prediction model for the air conditioner; The temperature prediction model is input with at least one of the signal strength, signal phase, channel state information, and frequency drift to perform temperature analysis on the smart home environment, thereby obtaining the ambient temperature of the smart home environment within a target time period after the current time point.

8. 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; When the processor executes a program stored in the memory, it implements the method as described in any one of claims 1-6.

9. A computer-readable storage medium having instructions stored thereon that, when executed by one or more processors, cause the processors to perform the method as described in any one of claims 1-6.

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