Terminal equipment control method and device, electronic equipment and readable storage medium

Abstract

The embodiment of the invention provides a terminal equipment control method and device, electronic equipment and a readable storage medium, and the method comprises the steps: deploying terminal equipment in a first designated space region, and obtaining the particle parameters of particles in the first designated space region; wherein the particulate matters comprise microorganisms; acquiring environmental parameters in the first specified space region; determining microorganism information of microorganisms in the first specified space area according to the particulate matter parameters and the environmental parameters; and generating a control instruction according to the microorganism information, and sending the control instruction to a corresponding terminal device in the first specified space area, so that the terminal device executes the control instruction. According to the embodiment of the invention, the air quality of the air environment in the first specified space area can be ensured, and thus the body health of a user is ensured.

Description

Technical Field

[0001] Embodiments of the present invention relate to the field of terminal technology, and in particular, to a terminal device control method, a terminal device control device, an electronic device, and a computer-readable storage medium. Background Art

[0002] In daily life, the number of microorganisms such as bacteria (such as Streptococcus and Bacillus) and fungal spores (such as Penicillium) in outdoor air increases. In addition, microorganisms such as actinomycetes and fungi in the soil become suspended in the air along with dust. This concentration increases especially when soil is turned over or cleaned. Large numbers of microorganisms can enter indoor environments through gaps in building doors and windows. Stagnant water in humid areas such as bathrooms and kitchens can also breed microorganisms such as Legionella and Escherichia coli, which can evaporate and float into the home air.

[0003] Under temperature and humidity conditions suitable for the reproduction of microorganisms such as fungi (such as Aspergillus, Candida, etc.), Aspergillus will also multiply in large numbers. Air-conditioning systems, carpets, fabric furniture, or enclosed spaces also provide an ideal growth environment for Aspergillus, causing a large amount of mold to float in the air environment, resulting in poor air quality in the air environment, which in turn affects the health of users. Summary of the Invention

[0004] In view of the above problems, a terminal device control method and apparatus are proposed to overcome the above problems or at least partially solve the above problems. The specific technical solution is as follows:

[0005] An embodiment of the present invention discloses a terminal device control method, wherein a terminal device is deployed in a first designated spatial area, the method comprising:

[0006] Acquiring particulate matter parameters of particulate matter in the first designated spatial area; wherein the particulate matter includes microorganisms;

[0007] Acquire environmental parameters in the first designated spatial area;

[0008] determining microbial information of the microorganisms in the first designated spatial area according to the particulate matter parameters and the environmental parameters;

[0009] A control instruction is generated according to the microorganism information, and the control instruction is sent to the corresponding terminal device in the first designated space area, so that the terminal device executes the control instruction.

[0010] In one embodiment of the present invention, before obtaining the particle parameters of the particles in the first designated spatial area, the method further includes:

[0011] Acquire first sample data in the second designated spatial area; the first sample data at least including historical particulate matter parameters, historical pollution sources, and historical health risk levels;

[0012] The prediction model to be trained is trained using the first sample data, and when the prediction model reaches a preset convergence condition, the trained prediction model is obtained.

[0013] In one embodiment of the present invention, before obtaining the particle parameters of the particles in the first designated spatial area, the method further includes:

[0014] Acquire second sample data in a third designated spatial area; the second sample data at least includes historical particulate matter parameters, historical environmental parameters, and historical microbial species;

[0015] The association model to be trained is trained using the second sample data, and when the association model reaches a preset convergence condition, the trained association model is obtained.

[0016] In one embodiment of the present invention, determining the microbial information of the microorganisms in the first designated spatial area according to the particulate matter parameter and the environmental parameter includes:

[0017] Inputting the particle parameters and the environmental parameters into a correlation model to obtain microbial species output by the correlation model;

[0018] Obtaining a standard proliferation curve corresponding to the microbial species;

[0019] generating a real-time proliferation curve according to the particle parameters;

[0020] When determining and correcting the particle parameters according to the standard proliferation curve and the real-time proliferation curve, obtaining a standard proliferation rate corresponding to the environmental parameters and the microbial species to correct the particle parameters;

[0021] The corrected particulate matter parameters are input into a prediction model to obtain microbial information of the microorganisms in the first designated spatial area; the microbial information at least includes a predicted pollution source and a health risk level.

[0022] In one embodiment of the present invention, the method further comprises:

[0023] When the standard proliferation curve matches the real-time proliferation curve, determining that the microorganisms in the first designated spatial area are naturally proliferating;

[0024] When the standard proliferation curve and the real-time proliferation curve do not match, determining that the microorganisms in the first designated spatial area are non-naturally proliferating;

[0025] When the microorganisms in the first designated spatial area are naturally proliferating, it is determined that the particle parameter needs to be corrected.

[0026] In one embodiment of the present invention, generating a control instruction based on the microbial information and sending the control instruction to the corresponding terminal device in the first designated spatial area so that the terminal device executes the control instruction includes:

[0027] When the health risk level reaches a preset health risk level, a control instruction is generated according to the predicted pollution source, and the control instruction is sent to the corresponding terminal device in the first designated spatial area, so that the terminal device executes the control instruction.

[0028] In one embodiment of the present invention, an intelligent host and a central control device are deployed in the first designated space area, and the central control device is deployed with at least a display screen, a microphone, a particle counter, a particle laser sensor, a temperature sensor and a humidity sensor. The particle counter and the particle laser sensor are used to detect the particulate matter parameters in the first designated space area; the temperature sensor and the humidity sensor are used to detect the environmental parameters in the first designated space; the environmental parameters include at least temperature data and humidity data.

[0029] In one embodiment of the present invention, sending the control instruction to the corresponding terminal device in the first designated spatial area so that the terminal device executes the control instruction includes:

[0030] Displaying warning information on the display screen; the warning information at least includes the predicted pollution source and health risk level, as well as the control instruction and the terminal device corresponding to the control instruction;

[0031] In response to a confirmation indication submitted by the user through the microphone or the display screen, the control instruction is sent to the corresponding terminal device in the first designated spatial area, so that the terminal device executes the control instruction.

[0032] In one embodiment of the present invention, the central control device is deployed in each room in the first designated space area, and the method further includes:

[0033] determining a frequency of use of each of the rooms by users;

[0034] Determine the detection cycle of the central control device corresponding to each of the rooms according to the user's usage frequency;

[0035] According to the detection cycle, the central control device corresponding to each of the rooms is controlled to obtain particulate matter parameters and environmental parameters.

[0036] An embodiment of the present invention further discloses a terminal device control device, wherein a terminal device is deployed in a first designated spatial area, and the device includes:

[0037] a particle parameter acquisition module, configured to acquire particle parameters of the particles in the first designated spatial area; wherein the particles include microorganisms;

[0038] An environmental parameter acquisition module, configured to acquire environmental parameters in the first designated spatial area;

[0039] a microbial information acquisition module, configured to determine the microbial information of the microorganisms in the first designated spatial area according to the particulate matter parameters and the environmental parameters;

[0040] The terminal device control module is used to generate a control instruction according to the microorganism information, and send the control instruction to the corresponding terminal device in the first designated space area, so that the terminal device executes the control instruction.

[0041] An 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;

[0042] The memory is used to store computer programs;

[0043] The processor is configured to implement the method described in the embodiment of the present invention when executing the program stored in the memory.

[0044] An embodiment of the present invention further discloses a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the method described in the embodiment of the present invention.

[0045] An embodiment of the present invention further discloses a computer-readable storage medium having instructions stored thereon. When executed by one or more processors, the processors are enabled to execute the method according to the embodiment of the present invention.

[0046] The embodiments of the present invention include the following advantages:

[0047] In an embodiment of the present invention, a terminal device is deployed in a first designated spatial area. When detecting microorganisms in the first designated spatial area, the particle parameters and environmental parameters of the particulate matter in the first designated spatial area can be obtained. The microbial information of the microorganisms in the first designated spatial area can be determined based on the particle parameters and environmental parameters. A control instruction can then be generated based on the microbial information and sent to a corresponding terminal device in the first designated spatial area so that the terminal device executes the control instruction to clean the microorganisms in the designated spatial area. In this embodiment of the present invention, the particle parameters and environmental parameters in the first designated spatial area can be obtained to determine the microbial information, and the terminal device in the first designated spatial area can be controlled based on the microbial information to clean the microorganisms, thereby ensuring the air quality of the air environment in the first designated spatial area and, in turn, ensuring the health of the user. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a flowchart of a terminal device control method provided in an embodiment of the present invention;

[0049] Figure 2 This is a schematic diagram of the hardware structure of a central control device provided in an embodiment of the present invention;

[0050] Figure 3 This is a schematic diagram of the structural layout of various sensors on a PCB multilayer board provided in an embodiment of the present invention;

[0051] Figure 4 This is a schematic diagram of the structural layout of various sensors on a PCB multilayer board provided in an embodiment of the present invention;

[0052] Figure 5 This is a diagram showing the structure and appearance of a 4-inch central control device provided in an embodiment of the present invention;

[0053] Figure 6 This is a diagram showing the internal details of the structure of a 4-inch central control device provided in an embodiment of the present invention;

[0054] Figure 7 This is a diagram showing the overall structure of a 4-inch central control device provided in an embodiment of the present invention;

[0055] Figure 8 This is a schematic diagram of the detection work of a 4-inch central control device provided in an embodiment of the present invention.

[0056] Figure 9 It is a three-dimensional microbial heat map provided in an embodiment of the present invention;

[0057] Figure 10 is a structural block diagram of a terminal device control device provided in an embodiment of the present invention;

[0058] Figure 11 It is a schematic diagram of the hardware structure of an electronic device for implementing various embodiments of the present invention. DETAILED DESCRIPTION

[0059] 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.

[0060] Reference Figure 1 , shows a flowchart of a terminal device control method provided in an embodiment of the present invention, wherein a terminal device is deployed in a first designated spatial area, and specifically may include the following steps:

[0061] Step 101: Obtain particle parameters of particles in the first designated spatial area; wherein the particles include microorganisms, and wherein the particle parameters include at least particle concentration.

[0062] Step 102: Acquire environmental parameters in the first designated spatial area.

[0063] In a specific implementation, the first designated spatial area can be a spatial area such as a house, and the terminal device can be a smart home device deployed in the house. For example, the smart home device can include but is not limited to air conditioning equipment, air purifiers, sweepers, disinfectors, dehumidifiers, and sensor devices.

[0064] In an embodiment of the present invention, a smart host and a central control device may be deployed in a first designated spatial area. The smart host serves as the intelligent brain within the first designated spatial area, controlling the central control device and terminal devices within the first designated spatial area. For example, in a smart home layout, a house may be equipped with at least one smart host and one central control device. If a house has multiple rooms, a central control device may be installed in each room. Based on the smart host and central control device, predictions can be made regarding which room has the most severe microbial contamination, the highest concentration of microbial particulate matter, or the poorest air quality.

[0065] In one embodiment of the present invention, referring to Figure 2, is a schematic diagram of the hardware structure of a central control device provided in an embodiment of the present invention. The central control device is equipped with at least a main control unit, a display screen, a microphone, a speaker, a particle counter, a particle laser sensor (such as a PM2.5 laser sensor), a temperature sensor, a humidity sensor, a PCB (Printed Circuit Board) multilayer board, a light sensing module, an infrared module, a microphone, a communication module and a display screen, etc., to realize the real-time particle parameter collection and monitoring of particulate matter (such as microorganisms such as bacteria and fungi, and dust, etc., wherein non-microorganisms such as dust may also carry microorganisms). Specifically, the particle counter is used to detect the particle size of the particulate matter in the first designated spatial area; the particle laser sensor is used to detect the particle concentration of the particulate matter in the first designated spatial area; the temperature sensor and the humidity sensor (temperature and humidity sensor) are used to detect the environmental parameters in the first designated space; the communication module can effectively realize the linkage of devices, and upload the data such as the particulate matter parameters and environmental parameters detected by the central control device to the cloud management platform to realize cloud data synchronization. Among them, the central control device can be a 4-inch device, which is a small device.

[0066] Reference Figure 3 , is a schematic diagram of the structural layout of various sensors on a PCB multilayer board provided in an embodiment of the present invention, Figure 3 The front view shows the device, with sensors such as the light sensor module, microphone, and infrared module located above the multi-layer PCB. The light sensor module is mainly used to adjust the screen brightness, the microphone is used for voice wake-up and issuing control commands, and the infrared module is used for cross-platform terminal device linkage.

[0067] Reference Figure 4 , is a schematic diagram of the structural layout of various sensors on a PCB multilayer board provided in an embodiment of the present invention, Figure 4 The back side is shown, which contains the module fixing screws, program debugging interface, power pin connector, temperature and humidity sensor, particle counter and PM2.5 laser sensor air vents. The environmental parameters and particulate matter parameters in the first designated space area can be collected through the temperature and humidity sensor, particle counter and PM2.5 laser sensor air vents.

[0068] Reference Figure 5 , is a structural appearance display diagram of a 4-inch central control device provided in an embodiment of the present invention, which includes the position layout of various sensors, specifically, the setting direction of the detection ports (air vents) of the temperature and humidity sensor, particle counter and PM2.5 laser sensor, as well as the layout of dual microphones (left and right microphones) and dual speakers (left and right speakers).

[0069] Reference Figure 6, is a diagram showing the internal details of the structure of a 4-inch central control device provided in an embodiment of the present invention, including the fixing method of sensors such as the microphone and infrared module (fixing screws of the fixing bracket), the sensor connection socket, and the connection direction of the FPC (Flexible Printed Circuit) cables of all sensors.

[0070] Reference Figure 7 , is a diagram showing the overall structure of a 4-inch central control device provided in an embodiment of the present invention. It includes a front shell assembly and a rear shell assembly, and further illustrates the assembly method of the front shell assembly (formed by the front shell, sealing silicone, and the front shell back cover). Sealing strips are installed on the structure of the 4-inch central control device to ensure the space is sealed and the accuracy of microbial detection is guaranteed. The rear shell of the 4-inch central control device includes the high-voltage controller PCB motherboard and the rear shell structural components.

[0071] Reference Figure 8 , is a schematic diagram of the detection work of a 4-inch central control device provided in an embodiment of the present invention, Figure 8 The working status and position direction of the three major microbial detection sensors, namely temperature and humidity sensors, particle counters and PM2.5 laser sensors, are demonstrated. The particle parameters and environmental parameters of particulate matter such as fungi can be collected through the air outlets of the temperature and humidity sensors, particle counters and PM2.5 laser sensors.

[0072] Reference Figure 9 , is a three-dimensional microbial heat map provided in an embodiment of the present invention. The 4-inch central control device in an embodiment of the present invention generates a three-dimensional microbial heat map by integrating hardware matching, sensor layout and software algorithm. It generates a three-dimensional microbial heat map by real-time monitoring of the microbial concentration (particulate matter concentration) in the air, showing the dynamic changes of the microbial community, and combined with the early warning threshold, it can link the terminal device to detect and kill molds and other microorganisms in the environment, realize closed-loop management of environmental health data, improve the air quality of the living environment, and ensure the health of users. Among them, CFU / m3 represents colony-forming units per cubic meter, and the microbial concentration warning can be divided into: Safety level (<100CFU / m3): The screen can display a green icon, and the microbial concentration is safe. Warning level (100-500CFU / m3): The screen can display a yellow icon, and the biological concentration warning. Dangerous level (500CFU / m3): The screen can display a red icon, and the microbial concentration is dangerous.

[0073] Particulate matter parameters include at least particle concentration and particle density, and environmental parameters include at least temperature and humidity data. In an embodiment of the present invention, the particulate matter parameters and environmental parameters of particulate matter in the first designated spatial area can be collected by the central control device. Specifically, these parameters are obtained through the central control device's temperature and humidity sensors, particle counters, and PM2.5 laser sensors. Specifically, the laser particle counter is used to collect air samples, detect the concentration of particulate matter in the air, which can include both microbial and non-microbial particles, monitor the particle concentration in real time, and generate a three-dimensional microbial heat map to display the dynamic changes in the microbial community. However, laser particle counters are generally unable to distinguish between microbial and non-microbial particles. The PM2.5 laser sensor is used to detect particulate matter of different sizes in the air environment, including microbial and non-microbial particles. The particle size range of particulate matter is generally between 0.5 microns and 10 microns. By adjusting the wavelength and algorithm, it can distinguish between microbial and non-microbial particles (such as dust in the air). It can also be used to perform correlation analysis between particulate matter concentration and microbial load, and automatically identify areas with high microbial contamination rates through machine learning. The temperature and humidity sensor is used to monitor environmental parameters in real time, collecting temperature and humidity change data, etc.

[0074] Step 103: Determine microbial information of the microorganisms in the first designated spatial area according to the particulate matter parameters and the environmental parameters.

[0075] In an embodiment of the present invention, the intelligent host can determine microbial information of microorganisms in the first designated spatial area based on the particulate matter concentration, particle size, and environmental parameters reported by the central control device. This microbial information can at least predict the source of contamination and the health risk level. For example, the predicted contamination source can include the area in the first designated spatial area where the microorganisms originated, such as the air conditioning unit, a corner, or the kitchen sink. The health risk level can be categorized into multiple levels, such as safe, dangerous, and warning.

[0076] Step 104: Generate a control instruction based on the microbial information, and send the control instruction to the corresponding terminal device in the first designated space area, so that the terminal device executes the control instruction.

[0077] In an embodiment of the present invention, after obtaining microbial information of microorganisms in a first designated spatial area, the intelligent host can generate corresponding control instructions based on the microbial information and send the control instructions to the corresponding terminal device in the first designated spatial area, thereby causing the terminal device to execute the control instructions to reduce the concentration of particulate matter in the first designated spatial area, thereby improving the air quality in the first designated spatial area. For example, if the pollution source is predicted to be an air conditioning device and the health risk level is dangerous, control instructions can be generated for the air conditioning device and the air purifier to control the air conditioning device to perform a cleaning operation and the air purifier to control the air purification operation.

[0078] In the above-mentioned terminal device control method, a terminal device is deployed in a first designated spatial area. When detecting microorganisms in the first designated spatial area, the particle parameters and environmental parameters of the particulate matter in the first designated spatial area can be obtained. The microbial information of the microorganisms in the first designated spatial area can be determined based on the particle parameters and environmental parameters. Then, a control instruction can be generated based on the microbial information and sent to the corresponding terminal device in the first designated spatial area so that the terminal device executes the control instruction to clean the microorganisms in the designated spatial area. In this embodiment of the present invention, the particle parameters and environmental parameters in the first designated spatial area can be obtained to determine the microbial information, and the terminal device in the first designated spatial area can be controlled based on the microbial information to clean the microorganisms, thereby ensuring the air quality of the air environment in the first designated spatial area and, in turn, ensuring the health of the user.

[0079] In one embodiment of the present invention, before step 101 of obtaining the particle parameters of the particles in the first designated spatial area, the method may further include:

[0080] Acquire first sample data in the second designated spatial area; the first sample data at least including historical particulate matter parameters, historical pollution sources, and historical health risk levels;

[0081] The prediction model to be trained is trained using the first sample data, and when the prediction model reaches a preset convergence condition, the trained prediction model is obtained.

[0082] Wherein, the second designated spatial area can be a spatial area such as a house. In an embodiment of the present invention, first sample data in the second designated spatial area can be obtained, wherein the first sample data can at least include historical particulate matter parameters, historical pollution sources, and historical health risk levels, etc., wherein the historical particulate matter parameters can at least include historical particulate matter concentrations, and the first sample data is used to iteratively train the prediction model to be trained (neural network model), and when the prediction model reaches the preset convergence condition, a trained prediction model can be obtained. Exemplarily, when the number of iterations of the prediction model reaches a preset number of iterations, or the loss value calculated between the predicted pollution source and health risk level output by the prediction model and the historical pollution source and historical health risk level obtains a preset loss value, it can be determined that the prediction model has reached the preset convergence condition. Wherein, the trained prediction model can predict the predicted pollution source and health risk level in the designated spatial area.

[0083] In the above embodiment, the first sample data in the second designated spatial area can be used to iteratively train the prediction model to be trained to obtain a trained prediction model. Based on the prediction model, the predicted pollution sources and health risk levels of the designated spatial area can be accurately predicted, and then the terminal equipment in the designated spatial area can be accurately controlled according to the predicted pollution sources and health risk levels to ensure the air environment quality of the designated spatial area.

[0084] In one embodiment of the present invention, before step 101 of obtaining the particle parameters of the particles in the first designated spatial area, the method may further include:

[0085] Acquire second sample data in a third designated spatial area; the second sample data at least includes historical particulate matter parameters, historical environmental parameters, and historical microbial species;

[0086] The association model to be trained is trained using the second sample data, and when the association model reaches a preset convergence condition, the trained association model is obtained.

[0087] Among them, the third designated spatial area can be a spatial area such as a house. In an embodiment of the present invention, second sample data in the third designated spatial area can be obtained, wherein the second sample data can at least include historical particulate matter parameters, historical environmental parameters and historical microbial species, wherein the historical particulate matter parameters can at least include historical particulate matter concentrations, and the second sample data is used to iteratively train the association model to be trained. When the association model reaches the preset convergence condition, a trained association model can be obtained. Exemplarily, when the number of iterations of the association model reaches a preset number of iterations, or the loss value calculated between the microbial species output by the association model and the historical microbial species obtains a preset loss value, it can be determined that the association model has reached the preset convergence condition. Among them, the trained association model can predict the microbial species in the designated spatial area.

[0088] In the above embodiment, the second sample data in the third designated spatial area can be used to iteratively train the association model to be trained to obtain a trained association model. Based on the association model, the types of microorganisms in the designated spatial area can be accurately predicted, and the particulate matter parameters can be corrected according to the types of microorganisms. The corrected particulate matter parameters can be input into the prediction model to obtain accurate predictions of pollution sources and health risk levels, so as to accurately control the terminal equipment in the designated spatial area to ensure the air environment quality of the designated spatial area.

[0089] In one embodiment of the present invention, the step 103 of determining the microbial information of the microorganisms in the first designated spatial area according to the particulate matter parameters and the environmental parameters may include:

[0090] Inputting the particle parameters and the environmental parameters into a correlation model to obtain microbial species output by the correlation model;

[0091] Obtaining a standard proliferation curve corresponding to the microbial species;

[0092] generating a real-time proliferation curve according to the particle parameters;

[0093] When determining and correcting the particle parameters according to the standard proliferation curve and the real-time proliferation curve, obtaining a standard proliferation rate corresponding to the environmental parameters and the microbial species to correct the particle parameters;

[0094] The corrected particulate matter parameters are input into a prediction model to obtain microbial information of the microorganisms in the first designated spatial area; the microbial information at least includes a predicted pollution source and a health risk level.

[0095] In an embodiment of the present invention, particulate matter parameters and environmental parameters can be input into a correlation model to obtain the microbial species output by the correlation model, wherein different microbial species have corresponding standard proliferation curves. At the same time, a real-time proliferation curve of the microorganism is generated according to the particulate matter parameters (such as particulate matter concentration). Then, the standard proliferation curve and the real-time proliferation curve can be used to determine whether it is natural proliferation or unnatural proliferation to determine the corrected particulate matter parameters. When determining the corrected particulate matter parameters, the standard proliferation rate corresponding to the environmental parameters and the microbial species predicted by the correlation model can be obtained to correct the particulate matter parameters. Specifically, according to the standard proliferation rate, the proliferation amount of the microbial species within the detection time corresponding to the particulate matter parameters and environmental parameters obtained by the central control device and under the environmental parameters can be calculated. Then, the proliferation amount can be removed from the particulate matter parameters (particulate matter concentration). Since the environmental parameters are not taken into account during the training of the prediction model, in real life, the number of microbial proliferations will be affected by environmental parameters such as temperature and humidity, that is, it will affect the particulate matter parameters collected by the central control device. Therefore, after the corrected particulate matter parameters and environmental parameters are input into the prediction model, the embodiment of the present invention can obtain an accurate prediction of the pollution source and health risk level after separating the environmental factors.

[0096] In the above embodiment, the microbial species can be predicted based on the association model, and then the particulate matter parameters can be determined whether to be corrected by comparing the standard proliferation curve corresponding to the microbial species and the real-time proliferation curve generated according to the particulate matter parameters. In this way, accurate particulate matter parameters can be input into the prediction model to obtain accurate predictions of pollution sources and health risk levels, thereby accurately controlling the terminal equipment in the specified spatial area to ensure the air environment quality in the specified spatial area.

[0097] In one embodiment of the present invention, the method may further include:

[0098] When the standard proliferation curve matches the real-time proliferation curve, determining that the microorganisms in the first designated spatial area are naturally proliferating;

[0099] When the standard proliferation curve and the real-time proliferation curve do not match, determining that the microorganisms in the first designated spatial area are non-naturally proliferating;

[0100] When the microorganisms in the first designated spatial area are naturally proliferating, it is determined that the particle parameter needs to be corrected.

[0101] In an embodiment of the present invention, a standard proliferation curve and a real-time proliferation curve may be matched. If the standard proliferation curve and the real-time proliferation curve match, it can be determined that the microorganisms in the first designated spatial area are naturally proliferating. Conversely, if the standard proliferation curve and the real-time proliferation curve do not match, it can be determined that the microorganisms in the first designated spatial area are unnaturally proliferating. The occurrence of unnatural proliferation may be caused by the presence of some sudden pollutants in the first designated spatial area, such as external dirty water or insects. In this case, the amount of microbial proliferation will be affected by environmental parameters such as temperature and humidity and sudden pollutants, that is, it will affect the particulate matter parameters collected by the central control device. In an embodiment of the present invention, when it is determined that the microorganisms in the first designated spatial area are naturally proliferating, a standard proliferation rate corresponding to the microorganism species predicted by the environmental parameters and the correlation model is obtained to correct the particulate matter parameters. When it is determined that the microorganisms in the first designated spatial area are unnaturally proliferating, there is no need to correct the particulate matter parameters, thereby maintaining the original particulate matter parameters. The original particulate matter parameters can reflect the actual environmental conditions of the first designated spatial area. Therefore, in the case of unnatural proliferation, after the original particulate matter parameters and environmental parameters are input into the prediction model, an accurate prediction of pollution sources and health risk levels reflecting the actual environmental conditions can be obtained.

[0102] In the above embodiment, by comparing whether the standard proliferation curve corresponding to the microbial species and the real-time proliferation curve generated according to the particulate matter parameters match, it is determined whether it is natural proliferation or unnatural proliferation, and the particulate matter parameters are corrected in the case of natural proliferation. In this way, the accurately corrected particulate matter parameters can be input into the prediction model to obtain accurate predicted pollution sources and health risk levels, and then accurately control the terminal equipment in the designated spatial area to ensure the air environment quality of the designated spatial area, and retain the original particulate matter parameters in the case of unnatural proliferation, so that the original particulate matter parameters can reflect the actual environmental conditions. Therefore, the original particulate matter parameters can be input into the prediction model to obtain predicted pollution sources and health risk levels that reflect the actual environmental conditions.

[0103] In one embodiment of the present invention, step 104, generating a control instruction based on the microbial information and sending the control instruction to the corresponding terminal device in the first designated spatial area so that the terminal device executes the control instruction, may include:

[0104] When the health risk level reaches a preset health risk level, a control instruction is generated according to the predicted pollution source, and the control instruction is sent to the corresponding terminal device in the first designated spatial area, so that the terminal device executes the control instruction.

[0105] Among them, health risk levels can be divided into multiple health risk levels such as safe, dangerous, and warning; predicted pollution sources can include areas such as air-conditioning equipment, corners or kitchen sinks.

[0106] In an embodiment of the present invention, only when the health risk level reaches a preset health risk level can a control instruction be generated based on the predicted pollution source, thereby controlling the corresponding terminal device to clean the air quality of the first designated space area and reducing unnecessary cleaning operations. For example, the preset health risk level may be dangerous. If the predicted pollution source is in the air-conditioning equipment, and the health risk level is dangerous, control instructions for the air-conditioning equipment and the air purifier can be generated to control the air-conditioning equipment to perform a cleaning operation, and to control the air purifier to perform an air purification operation. In addition, when the health risk level is safe, no operation is required. When the health risk level is a warning, a warning can be issued to the user through the central control device.

[0107] In the above embodiment, a control instruction may be generated to control the corresponding terminal device only when the health risk level reaches a preset health risk level, so as to reduce the concentration of particulate matter in the first designated spatial area to improve the air quality.

[0108] In one embodiment of the present invention, sending the control instruction to the corresponding terminal device in the first designated spatial area so that the terminal device executes the control instruction includes:

[0109] Displaying warning information on the display screen; the warning information at least includes the predicted pollution source and health risk level, as well as the control instruction and the terminal device corresponding to the control instruction;

[0110] In response to a confirmation indication submitted by the user through the microphone or the display screen, the control instruction is sent to the corresponding terminal device in the first designated spatial area, so that the terminal device executes the control instruction.

[0111] In an embodiment of the present invention, a warning message can be displayed to the user via the display screen of the central control device. The warning message may include at least the predicted pollution source and health risk level, as well as control instructions and the terminal device corresponding to the control instructions. The user can then choose whether to have the terminal device perform the corresponding cleaning operation based on their needs, thereby improving air quality. Specifically, the user can submit a confirmation instruction to the smart host via the microphone or display screen of the central control device. In response to the confirmation instruction, the smart host transmits the control instruction to the corresponding terminal device in the first designated spatial area, causing the terminal device to perform the cleaning operation according to the control instruction.

[0112] In the above embodiment, the warning information can be displayed through the central control device, and the user can determine whether to allow the terminal device to perform cleaning operations according to the control instructions based on his or her own needs, such as the need for quietness or the permission of a certain amount of noise, thereby better meeting the user's personalized needs.

[0113] In one embodiment of the present invention, the central control device is deployed in each room in the first designated space area, and the method further includes:

[0114] determining a frequency of use of each of the rooms by users;

[0115] Determine the detection cycle of the central control device corresponding to each of the rooms according to the user's usage frequency;

[0116] According to the detection cycle, the central control device corresponding to each of the rooms is controlled to obtain particulate matter parameters and environmental parameters.

[0117] In a specific implementation, the central control devices can be distributed and deployed in each room in the first designated spatial area. However, if the central control devices are constantly detecting particle size parameters and environmental parameters, a certain amount of electricity will be consumed. In real life, different rooms have different usage frequencies. For example, users usually use the kitchen and bedroom more frequently, so the kitchen and bedroom need to maintain a higher air quality to better ensure the health of the users. Therefore, the embodiment of the present invention can count the usage frequencies of users in each room, and then determine the detection cycle of the central control devices corresponding to each room based on the usage frequencies of users. For example, the detection cycle of the kitchen and bedroom is higher than that of the living room. Then, the central control devices corresponding to each room are controlled according to the detection cycle to obtain the particle parameters and environmental parameters, which are used to determine whether it is necessary to control the terminal device to perform a cleaning operation.

[0118] In the above embodiment, the detection cycle of the central control device corresponding to each room can be determined according to the frequency of use of users in each room, so as to control the central control device corresponding to each room to obtain particulate matter parameters and environmental parameters based on the detection cycle, so as to reduce the energy consumption of the central control device.

[0119] In related technologies, microbial detection equipment is large in size, mainly industrial-grade, and mainly used in high-demand environments such as medical and industrial environments, making it difficult to integrate into home environments. Although some household products (such as purifiers with integrated microbial detection) involve air environment monitoring, the microbial detection function has not yet become mainstream, and there are disputes over accuracy. Miniaturized products have reduced performance due to technical limitations and low market recognition. Consumers believe that the microbial detection function is of little significance and it is better to take direct intuitive measures such as ventilation and disinfection. Existing smart home products (terminal devices) lack microbial detection modules, making it impossible to achieve closed-loop management of environmental health data and unable to solve the problem of integrating microbial detection accuracy with user interaction experience. In response to the above problems, the present invention provides a method for a 4-inch central control voice smart screen based on microbial detection in the home air environment, especially a real-time detection method for home air particulate matter based on a laser particle counter, a PM2.5 laser sensor and a temperature and humidity sensor. The particulate matter may include microorganisms. Through multi-sensor data fusion and dynamic algorithms, accurate identification of microbial pollution, risk grading and linkage purification of smart devices in the whole house are achieved, which solves the problem of microbial detection in the human home environment, links smart home products to remove microorganisms in the home environment, realizes closed-loop management of environmental health data, and improves the air quality problem in the living environment.

[0120] It should be noted that for the sake of simplicity, the method embodiments are described as a series of actions. However, 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 this specification are all preferred embodiments, and the actions involved are not necessarily required for the embodiments of the present invention.

[0121] Reference Figure 10 , shows a structural block diagram of a terminal device control device provided in an embodiment of the present invention. Terminal devices are deployed in a first designated spatial area. The device may specifically include the following modules:

[0122] The particle parameter acquisition module 1001 is used to obtain the particle parameters of the particles in the first designated space area; wherein the particles include microorganisms

[0123] An environmental parameter acquisition module 1002 is used to acquire environmental parameters in the first designated spatial area;

[0124] A microbial information acquisition module 1003 is configured to determine the microbial information of the microorganisms in the first designated spatial area according to the particulate matter parameters and the environmental parameters;

[0125] The terminal device control module 1004 is configured to generate a control instruction according to the microorganism information, and send the control instruction to the corresponding terminal device in the first designated spatial area, so that the terminal device executes the control instruction.

[0126] In one embodiment of the present invention, the apparatus further comprises: a prediction model training module, configured to:

[0127] Acquire first sample data in the second designated spatial area; the first sample data at least including historical particulate matter parameters, historical pollution sources, and historical health risk levels;

[0128] The prediction model to be trained is trained using the first sample data, and when the prediction model reaches a preset convergence condition, the trained prediction model is obtained.

[0129] In one embodiment of the present invention, the apparatus further comprises: an association model training module, configured to:

[0130] Acquire second sample data in a third designated spatial area; the second sample data at least includes historical particulate matter parameters, historical environmental parameters, and historical microbial species;

[0131] The association model to be trained is trained using the second sample data, and when the association model reaches a preset convergence condition, the trained association model is obtained.

[0132] In one embodiment of the present invention, the microbial information acquisition module 1003 is used to:

[0133] Inputting the particle parameters and the environmental parameters into a correlation model to obtain microbial species output by the correlation model;

[0134] Obtaining a standard proliferation curve corresponding to the microbial species;

[0135] generating a real-time proliferation curve according to the particle parameters;

[0136] When determining and correcting the particle parameters according to the standard proliferation curve and the real-time proliferation curve, obtaining a standard proliferation rate corresponding to the environmental parameters and the microbial species to correct the particle parameters;

[0137] The corrected particulate matter parameters are input into a prediction model to obtain microbial information of the microorganisms in the first designated spatial area; the microbial information at least includes a predicted pollution source and a health risk level.

[0138] In one embodiment of the present invention, the microbial information acquisition module 1003 is used to:

[0139] When the standard proliferation curve matches the real-time proliferation curve, determining that the microorganisms in the first designated spatial area are naturally proliferating;

[0140] When the standard proliferation curve and the real-time proliferation curve do not match, determining that the microorganisms in the first designated spatial area are non-naturally proliferating;

[0141] When the microorganisms in the first designated spatial area are naturally proliferating, it is determined that the particle parameter needs to be corrected.

[0142] In one embodiment of the present invention, s is a terminal device control module 1004, which is used to:

[0143] When the health risk level reaches a preset health risk level, a control instruction is generated according to the predicted pollution source, and the control instruction is sent to the corresponding terminal device in the first designated spatial area, so that the terminal device executes the control instruction.

[0144] In one embodiment of the present invention, an intelligent host and a central control device are deployed in the first designated space area, and the central control device is deployed with at least a display screen, a microphone, a particle counter, a particle laser sensor, a temperature sensor and a humidity sensor. The particle counter and the particle laser sensor are used to detect the particulate matter parameters in the first designated space area; the temperature sensor and the humidity sensor are used to detect the environmental parameters in the first designated space; the environmental parameters include at least temperature data and humidity data.

[0145] In one embodiment of the present invention, the terminal device control module 1004 is configured to:

[0146] Displaying warning information on the display screen; the warning information at least includes the predicted pollution source and health risk level, as well as the control instruction and the terminal device corresponding to the control instruction;

[0147] In response to a confirmation indication submitted by the user through the microphone or the display screen, the control instruction is sent to the corresponding terminal device in the first designated spatial area, so that the terminal device executes the control instruction.

[0148] In one embodiment of the present invention, the apparatus further includes: a detection period determination module, configured to:

[0149] determining a frequency of use of each of the rooms by users;

[0150] Determine the detection cycle of the central control device corresponding to each of the rooms according to the user's usage frequency;

[0151] According to the detection cycle, the central control device corresponding to each of the rooms is controlled to obtain particulate matter parameters and environmental parameters.

[0152] 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.

[0153] In addition, an embodiment of the present invention also provides an electronic device, including: a processor, a memory, and a computer program stored in the memory and runnable on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned terminal device control method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0154] The present invention also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the various processes of the terminal device control method embodiment described above are implemented, and the same technical effects are achieved. To avoid repetition, the details are not described here. The computer-readable storage medium may be, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0155] An embodiment of the present invention also provides a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the various processes of the above-mentioned terminal device control method embodiment and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0156] Figure 11 A schematic diagram of the hardware structure of an electronic device for implementing various embodiments of the present invention.

[0157] The electronic device 1100 includes but is not limited to: a radio frequency unit 1101, a network module 1102, an audio output unit 1103, an input unit 1104, a sensor 1105, a display unit 1106, a user input unit 1107, an interface unit 1108, a memory 1109, a processor 1110, and a power supply 1111. It will be understood by those skilled in the art that Figure 11 The electronic device structure shown in the figure does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or arrange the components differently. In the embodiments of the present invention, the electronic device includes but is not limited to mobile phones, tablet computers, laptop computers, PDAs, vehicle-mounted terminals, wearable devices, and pedometers.

[0158] It should be understood that in this embodiment of the present invention, RF unit 1101 can be used to receive and transmit signals during information transmission or calls. Specifically, it receives downlink data from the base station and transmits it to processor 1110 for processing; in addition, it transmits uplink data to the base station. Generally, RF unit 1101 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low-noise amplifier, a duplexer, and the like. Furthermore, RF unit 1101 can communicate with the network and other devices via a wireless communication system.

[0159] The electronic device provides users with wireless broadband Internet access through the network module 1102, such as helping users to send and receive emails, browse web pages, and access streaming media.

[0160] The audio output unit 1103 can convert audio data received by the RF unit 1101 or the network module 1102 or stored in the memory 1109 into an audio signal and output it as sound. In addition, the audio output unit 1103 can also provide audio output related to a specific function performed by the electronic device 1100 (for example, a call signal reception sound, a message reception sound, etc.). The audio output unit 1103 includes a speaker, a buzzer, a receiver, etc.

[0161] The input unit 1104 is used to receive audio or video signals. The input unit 1104 may include a graphics processing unit (GPU) 11041 and a microphone 11042. The graphics processor 11041 processes image data of a still 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 frames can be displayed on the display unit 1106. The image frames processed by the graphics processor 11041 can be stored in the memory 1109 (or other storage medium) or transmitted via the radio frequency unit 1101 or the network module 1102. The microphone 11042 can receive sound and process such sound into audio data. In the case of a telephone call mode, the processed audio data can be converted into a format that can be sent to a mobile communication base station via the radio frequency unit 1101 for output.

[0162] The electronic device 1100 also includes at least one sensor 1105, 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 11061 according to the brightness of the ambient light, and the proximity sensor can turn off the display panel 11061 and / or the backlight when the electronic device 1100 is moved to the ear. As a type of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in all directions (generally three axes), and can detect the magnitude and direction of gravity when stationary. It 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 1105 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.

[0163] The display unit 1106 is used to display information input by the user or information provided to the user. The display unit 1106 may include a display panel 11061, which may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.

[0164] The user input unit 1107 can be used to receive input digital or character information, and to generate key signal input related to the user settings and function control of the electronic device. Specifically, the user input unit 1107 includes a touch panel 11071 and other input devices 11072. The touch panel 11071, also known as a touch screen, can collect user touch operations on or near it (such as operations performed by the user using any suitable object or accessory such as a finger, stylus, etc. on or near the touch panel 11071). The touch panel 11071 may include two parts: a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch direction, detects the signal caused by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device and converts it into contact point coordinates, which are then sent to the processor 1110, which receives the command sent by the processor 1110 and executes it. In addition, the touch panel 11071 can be implemented using various types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 11071, the user input unit 1107 may further include other input devices 11072. Specifically, the other input devices 11072 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 an operating stick, which will not be described in detail here.

[0165] Furthermore, the touch panel 11071 may be overlaid on the display panel 11061. When the touch panel 11071 detects a touch operation on or near it, it transmits the information to the processor 1110 to determine the type of touch event. Subsequently, the processor 1110 provides corresponding visual output on the display panel 11061 according to the type of touch event. Figure 11 In the figure, the touch panel 11071 and the display panel 11061 are two independent components to realize the input and output functions of the electronic device. However, in some embodiments, the touch panel 11071 and the display panel 11061 can be integrated to realize the input and output functions of the electronic device, which is not limited here.

[0166] The interface unit 1108 is an interface for connecting external devices to the electronic device 1100. For example, the external devices 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 1108 may be used to receive input (e.g., data information, power, etc.) from the external device and transmit the received input to one or more elements within the electronic device 1100, or may be used to transmit data between the electronic device 1100 and the external device.

[0167] Memory 1109 can be used to store software programs and various data. Memory 1109 may primarily include a program storage area and a data storage area. The program storage area may store an operating system and at least one application required for a function (such as a sound playback function or an image playback function); the data storage area may store data generated based on the use of the phone (such as audio data, a phone book, etc.). Furthermore, memory 1109 may include high-speed random access memory and non-volatile memory, such as at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0168] Processor 1110 is the control center of the electronic device. It connects all parts of the electronic device using various interfaces and circuits. By running or executing software programs and / or modules stored in memory 1109 and accessing data stored in memory 1109, it performs various functions of the electronic device and processes data, thereby providing overall monitoring of the electronic device. Processor 1110 may include one or more processing units; preferably, processor 1110 may integrate an application processor and a modem processor. The application processor primarily handles the operating system, user interface, and application programs, while the modem processor primarily handles wireless communications. It is understood that the modem processor may not be integrated into processor 1110.

[0169] The electronic device 1100 may also include a power supply 1111 (such as a battery) to supply power to each component. Preferably, the power supply 1111 may be logically connected to the processor 1110 through a power management system, thereby managing functions such as charging, discharging, and power consumption through the power management system.

[0170] In addition, the electronic device 1100 includes some functional modules not shown, which will not be described here.

[0171] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0172] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better embodiment. 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, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present invention.

[0173] 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 methods. The above-mentioned specific implementation methods are merely illustrative and not 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 protected by the present invention.

[0174] Those skilled 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.

[0175] Those skilled in the art will 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.

[0176] In the embodiments provided in this 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 merely schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, 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.

[0177] The units described as separate components may or may not be physically separate, and 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 these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0178] 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.

[0179] 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 part 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 for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute 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 code, such as a USB flash drive, a mobile hard drive, ROM, RAM, a magnetic disk, or an optical disk.

[0180] 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 modifications or substitutions that can be easily conceived by a person 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 based on the scope of protection of the claims.

Claims

1. A terminal device control method, characterized in that: A terminal device is deployed in a first designated spatial area, and the method includes: Acquiring particulate matter parameters of particulate matter in the first designated spatial area; wherein the particulate matter includes microorganisms; Acquire environmental parameters in the first designated spatial area; determining microbial information of the microorganisms in the first designated spatial area according to the particulate matter parameters and the environmental parameters; A control instruction is generated according to the microorganism information, and the control instruction is sent to the corresponding terminal device in the first designated space area, so that the terminal device executes the control instruction.

2. The method according to claim 1, characterized in that Before obtaining the particle parameters of the particles in the first designated spatial area, the method further includes: Acquire first sample data in the second designated spatial area; the first sample data at least including historical particulate matter parameters, historical pollution sources, and historical health risk levels; The prediction model to be trained is trained using the first sample data, and when the prediction model reaches a preset convergence condition, the trained prediction model is obtained.

3. The method according to claim 1, characterized in that Before obtaining the particle parameters of the particles in the first designated spatial area, the method further includes: Acquire second sample data in a third designated spatial area; the second sample data at least includes historical particulate matter parameters, historical environmental parameters, and historical microbial species; The association model to be trained is trained using the second sample data, and when the association model reaches a preset convergence condition, the trained association model is obtained.

4. The method according to claim 1, wherein The particulate matter parameter includes at least a particulate matter concentration; and determining the microbial information of the microorganisms in the first designated spatial area based on the particulate matter parameter and the environmental parameter includes: Inputting the particle parameters and the environmental parameters into a correlation model to obtain microbial species output by the correlation model; Obtaining a standard proliferation curve corresponding to the microbial species; generating a real-time proliferation curve according to the particle parameters; When determining and correcting the particle parameters according to the standard proliferation curve and the real-time proliferation curve, obtaining a standard proliferation rate corresponding to the environmental parameters and the microbial species to correct the particle parameters; The corrected particulate matter parameters are input into a prediction model to obtain microbial information of the microorganisms in the first designated spatial area; the microbial information at least includes a predicted pollution source and a health risk level.

5. The method according to claim 4, characterized in that The method further comprises: When the standard proliferation curve matches the real-time proliferation curve, determining that the microorganisms in the first designated spatial area are naturally proliferating; When the standard proliferation curve and the real-time proliferation curve do not match, determining that the microorganisms in the first designated spatial area are non-naturally proliferating; When the microorganisms in the first designated spatial area are naturally proliferating, it is determined that the particle parameter needs to be corrected.

6. The method according to claim 4, characterized in that Generating a control instruction according to the microorganism information, and sending the control instruction to the corresponding terminal device in the first designated space area so that the terminal device executes the control instruction, including: When the health risk level reaches a preset health risk level, a control instruction is generated according to the predicted pollution source, and the control instruction is sent to the corresponding terminal device in the first designated spatial area, so that the terminal device executes the control instruction.

7. The method according to claim 1, characterized in that An intelligent host and a central control device are deployed in the first designated space area. The central control device is equipped with at least a display screen, a microphone, a particle counter, a particle laser sensor, a temperature sensor and a humidity sensor. The particle counter and the particle laser sensor are used to detect the particulate matter parameters in the first designated space area; the temperature sensor and the humidity sensor are used to detect the environmental parameters in the first designated space; the environmental parameters include at least temperature data and humidity data.

8. The method according to claim 7, characterized in that The sending the control instruction to the corresponding terminal device in the first designated spatial area so that the terminal device executes the control instruction includes: Displaying warning information on the display screen; the warning information at least includes the predicted pollution source and health risk level, as well as the control instruction and the terminal device corresponding to the control instruction; In response to a confirmation indication submitted by the user through the microphone or the display screen, the control instruction is sent to the corresponding terminal device in the first designated spatial area, so that the terminal device executes the control instruction.

9. The method according to claim 7, characterized in that The central control device is deployed in each room in the first designated space area, and the method further includes: determining a frequency of use of each of the rooms by users; Determine the detection cycle of the central control device corresponding to each of the rooms according to the user's usage frequency; According to the detection cycle, the central control device corresponding to each of the rooms is controlled to obtain particulate matter parameters and environmental parameters.

10. A terminal device control device, characterized in that: A terminal device is deployed in a first designated spatial area, and the apparatus includes: a particle parameter acquisition module, configured to acquire particle parameters of the particles in the first designated spatial area; wherein the particles include microorganisms; An environmental parameter acquisition module, configured to acquire environmental parameters in the first designated spatial area; a microbial information acquisition module, configured to determine the microbial information of the microorganisms in the first designated spatial area according to the particulate matter parameters and the environmental parameters; The terminal device control module is used to generate a control instruction according to the microorganism information, and send the control instruction to the corresponding terminal device in the first designated space area, so that the terminal device executes the control instruction.

11. An electronic device, characterized in that: 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; The memory is used to store computer programs; The processor is configured to implement the method according to any one of claims 1 to 9 when executing a program stored in the memory.

12. 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 9.

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