An internet of things device control method, apparatus and related device

Abstract

The present disclosure provides an Internet of Things device control method, device and related equipment, the method comprising: a first device determines a physical control parameter of a second device according to detection data from the second device; the detection data comprises a physical parameter and power, and the physical control parameter is used to control the physical parameter of the second device; according to the physical control parameter, a power feedback signal is sent to the second device, and the power feedback signal is used to indicate the physical control parameter. Correspondingly, the second device receives the power feedback signal from the first device; determines the physical control parameter according to the power feedback signal, and controls the physical parameter according to the physical control parameter.

Description

Technical Field

[0001] This disclosure relates to the field of Internet of Things (IoT) technology, and in particular to an IoT device control method, apparatus, and related equipment. Background Technology

[0002] The Internet of Things (IoT) is one of the hottest topics in the technology field today. Through information sensing devices, devices are connected to networks according to standard protocols, exchanging and communicating information through information transmission media, thereby achieving functions such as intelligent identification, positioning, tracking, and monitoring. With the continuous upgrading and acceleration of the domestic internet, the number and stability of connected devices within the IoT have also increased significantly, enabling more devices to transmit data efficiently and in real time. With the continuous development of electronic devices, the cost of IoT devices is constantly decreasing, driving the widespread application of IoT in various fields, such as smart homes, intelligent connected vehicles, smart transportation, and intelligent industrial control. How to improve the management efficiency of IoT systems is one of the problems that needs to be solved. Summary of the Invention

[0003] This disclosure provides a method, apparatus, electronic device, and storage medium for controlling Internet of Things (IoT) devices, in order to at least solve the above-mentioned technical problems existing in the prior art.

[0004] In a first aspect, embodiments of this disclosure provide an Internet of Things (IoT) device control method, applied to a first device, the method comprising:

[0005] Based on the detection data from the second device, the physical control parameters of the second device are determined; the detection data includes physical parameters and power, and the physical control parameters are used to control the physical parameters of the second device.

[0006] Based on the physical control parameters, a power feedback signal is sent to the second device, the power feedback signal being used to indicate the physical control parameters.

[0007] Secondly, embodiments of this disclosure provide an Internet of Things (IoT) device control method, applied to a second device, the method comprising:

[0008] Receive power feedback signal from the first device;

[0009] The physical control parameters are determined based on the power feedback signal, and the physical parameters are controlled based on the physical control parameters.

[0010] Thirdly, embodiments of this disclosure provide an Internet of Things (IoT) device control apparatus, which is applied to a first device, and the apparatus includes:

[0011] A first processing module is configured to determine the physical control parameters of the second device based on detection data from the second device; the detection data includes physical parameters and power, and the physical control parameters are used to control the physical parameters of the second device.

[0012] The first communication module is used to send a power feedback signal to the second device according to the physical control parameters, the power feedback signal being used to indicate the physical control parameters.

[0013] Fourthly, embodiments of this disclosure provide an Internet of Things (IoT) device control apparatus, which is applied to a second device, and the apparatus includes:

[0014] The second communication module is used to receive power feedback signals from the first device;

[0015] The second processing module is used to determine physical control parameters based on the power feedback signal, and to control the physical parameters based on the physical control parameters.

[0016] Fifthly, embodiments of this disclosure provide an electronic device, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to execute an IoT device control method on a first device side; or to enable the at least one processor to execute an IoT device control method on a second device side.

[0017] In a sixth aspect, embodiments of this disclosure provide a non-transitory computer-readable storage medium storing computer instructions, the computer instructions being configured to cause a computer to execute an IoT device control method on the first device side; or, the computer instructions being configured to cause a computer to execute an IoT device control method on the second device side.

[0018] This disclosure provides an IoT device control method, apparatus, electronic device, and storage medium. The method includes: a first device determining physical control parameters of a second device based on detection data from a second device; the detection data includes physical parameters and power, and the physical control parameters are used to control the physical parameters of the second device; and a power feedback signal being sent to the second device based on the physical control parameters, the power feedback signal indicating the physical control parameters. Correspondingly, the second device receives the power feedback signal from the first device; determines the physical control parameters based on the power feedback signal; and controls the physical parameters based on the physical control parameters. Thus, the first device, by receiving the detection data from the second device, can acquire the physical parameters and power information of the second device in real time, thereby calculating and determining the corresponding physical control parameters, achieving intelligent control of the second device, and improving the management efficiency of the IoT system.

[0019] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of this disclosure, nor is it intended to limit the scope of this disclosure. Other features of this disclosure will become readily apparent from the following description. Attached Figure Description

[0020] Figure 1 A flowchart illustrating an Internet of Things (IoT) device control method provided in an embodiment of this disclosure;

[0021] Figure 2 This is a schematic diagram of the structure of an Internet of Things (IoT) system provided in an embodiment of the present disclosure;

[0022] Figure 3 A flowchart illustrating another IoT device control method provided in this embodiment of the disclosure;

[0023] Figure 4 A schematic diagram of the structure of a network access device provided in an embodiment of this disclosure;

[0024] Figure 5 A schematic diagram of the structure of a smart router provided in an embodiment of this disclosure;

[0025] Figure 6 A schematic diagram of the structure of a power processing module provided in an embodiment of this disclosure;

[0026] Figure 7 A schematic flowchart illustrating a power intelligent control IoT method provided in an embodiment of this disclosure;

[0027] Figure 8 This is a schematic diagram of the structure of an Internet of Things (IoT) device control device provided in an embodiment of the present disclosure;

[0028] Figure 9This is a schematic diagram of another IoT device control device provided in an embodiment of the present disclosure;

[0029] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0030] To make the objectives, features, and advantages of this disclosure more apparent and understandable, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this disclosure, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort are within the scope of protection of this disclosure.

[0031] Before providing a further detailed description of the embodiments of this disclosure, the relevant technologies involved in the embodiments of this disclosure will be described.

[0032] The Internet of Things (IoT) primarily refers to a system that shares the physical parameters of various devices via the internet, enabling intelligent scheduling and collaborative work between these devices. The key technologies involved include the following:

[0033] Sensor technology enables the monitoring of various physical parameters of devices connected to the Internet of Things (IoT) system, thereby understanding the status of these devices; and it can also convert relevant physical parameters into electrical signals and feed them back to the control center of the IoT system.

[0034] Communication network technology is essential for the data transmission and interconnection between the various devices connected to the Internet of Things (IoT) system and the control center. Improving the communication network technology in the IoT can effectively enhance the real-time performance and stability of the IoT system.

[0035] Data processing and analysis technologies enable the control center in an IoT system to collect, store, process, and analyze data generated by network-connected devices, extracting valuable information to optimize the operation of the IoT system and support decision-making.

[0036] Security and privacy protection technologies are crucial. IoT systems generate a large amount of data interaction during operation, making the protection of the security and privacy of connected devices within the IoT system a critical consideration during data transmission.

[0037] Edge computing and distributed system technologies are essential for IoT systems. With a large number of connected devices and a large amount of data, the data processing workload of the control center will be significantly increased. By distributing computing and data processing functions to various connected devices or network nodes, it will help improve the system's data processing efficiency, reduce network latency, and increase the system's security and stability.

[0038] The Internet of Things (IoT) is a network based on information carriers such as the Internet and traditional telecommunications networks, enabling all networkable devices to interconnect through the collection of physical information. Currently, the IoT primarily monitors various physical parameters of network-connected devices, such as temperature, voltage, current, air pressure, and humidity.

[0039] However, due to the diverse range of physical parameters collected by sensors within IoT devices, the data acquisition process generates a substantial amount of data over long-term use of the IoT system. Secondly, traditional IoT relies on remote monitoring and control of connected devices via a network, lacking a certain level of intelligence; furthermore, the increasing number of connected devices poses significant challenges for administrators in monitoring these devices. In summary, the increased data volume and the lack of intelligent monitoring of connected devices both contribute to insufficient management efficiency.

[0040] Based on this, embodiments of the present disclosure provide an Internet of Things (IoT) device management method, apparatus, and related equipment.

[0041] like Figure 1 As shown, Figure 1 This is a flowchart illustrating an IoT device control method provided in an embodiment of the present disclosure; the method can be applied to a first device, and the method includes:

[0042] Step 101: Determine the physical control parameters of the second device based on the detection data from the second device; the detection data includes physical parameters and power, and the physical control parameters are used to control the physical parameters of the second device;

[0043] Step 102: Send a power feedback signal to the second device according to the physical control parameters. The power feedback signal is used to indicate the physical control parameters.

[0044] In some embodiments, the first device and the second device may be devices in an Internet of Things (IoT) system.

[0045] The first device can connect to at least one second device. The first device can be a gateway device, smart router, or control center in the Internet of Things (IoT) system. It can acquire the detection data collected by the second device, calculate and determine the corresponding physical control parameters, and intelligently control the second device based on these parameters. The second device can be a managed device added to the IoT, also known simply as a network-connected device.

[0046] For example, such as Figure 2 As shown, the first device is a smart router that connects home appliances, industrial control equipment, smart transportation equipment, vehicle networking equipment, etc. Each of these home appliances, industrial control equipment, smart transportation equipment, and vehicle networking equipment serves as a second device in an Internet of Things (IoT) system.

[0047] exist Figure 2 In the illustrated IoT system, the first device acts as the core connector of the network, connecting and managing different types of second devices to ensure they can communicate and collaborate efficiently and securely within the network. These second devices connect to the network and achieve interconnection through a smart router. Furthermore, the first device can analyze and process the detection data collected by the second devices, enabling intelligent control over them.

[0048] In some embodiments, determining the physical control parameters of the second device based on the detection data sent by the second device includes:

[0049] A power-time sample set is determined based on the detection data. The power-time sample set includes at least one sample pair, and each sample pair includes a power curve and the time corresponding to the power curve.

[0050] Based on the at least one sample pair, determine at least one user habit for a first time period;

[0051] Based on the user habits of at least one first time period, determine the physical control parameters corresponding to each first time period.

[0052] Specifically, the detection data includes the collected power and time. Based on the detection data, a power curve can be determined, which reflects the process of power change, such as the power consumption of a certain network-connected device over a period of time. Since the power changes, this can be reflected by the power curve.

[0053] Each sample pair includes a power curve and the corresponding time of the power curve, indicating that the power curve can correspond to the start time and end time of the power curve; and / or, can correspond to the time corresponding to each power value in the power curve; and / or, can correspond to the time of abrupt power values ​​in the power curve.

[0054] Furthermore, this time can be specified as a specific day and time, allowing the sample pairs to help identify users' periodic behavioral patterns. That is, the detection data can not only reflect changes in device power but also record when these changes occur on a specific day (e.g., Monday evening at 8 PM) or at a specific time (e.g., every morning at 7 AM). In this way, the sample pairs can reveal user habits, such as certain behaviors occurring at fixed times each day or week, thereby analyzing users' periodic habits.

[0055] It should be understood that, since the power curve reflects how power changes over time, the power curve corresponds to a specific time; that is, each data point on the power curve can be associated with a specific time. In other words, each power value corresponds one-to-one with the time it was measured. This allows for more accurate data analysis.

[0056] Specifically, by using a power-time sample set (i.e., at least one sample pair), user habits or behavioral patterns within certain specific time periods can be analyzed (i.e., user habits in the first time period). These habits can be user activity patterns or specific usage patterns. Based on the analyzed user habits, the required physical control parameters for each time period (i.e., the first time period) can be further inferred. These physical control parameters can be used to adjust device behavior, optimize power usage, and improve performance.

[0057] For example, if a second device is a smart light fixture, the specific power-time sample set may include:

[0058] Time 18:00, power 0W (light off); Time 18:05, power 60W (light on);

[0059] Time 19:00, power 0W (lights off); Time 20:00, power 60W (lights on);

[0060] If this pattern continues for several cycles, such as every day, data analysis can identify the user's lighting habits during specific time periods. For example, if the user typically turns on the lights between 6:05 PM and 7:00 PM, the generated physical control parameters can be used to control the smart lights to automatically turn on at 6:05 PM.

[0061] Specifically, the range of each of the at least one first time period can be the same or different. Here, defining user habits for at least one first time period represents different user habits within the same or different first time periods. For example, a first time period from 18:05 to 19:00 can have different user habits, such as turning on lights or turning on the air conditioner. Another example: one first time period could be from 18:05 to 19:00, with the corresponding user habit being turning on lights; another first time period could be from 18:30 to 19:00, with the corresponding user habit being turning on the air conditioner and setting it to 26 degrees Celsius. The generated physical control parameters can then be used to control the smart lights to automatically turn on at 18:05 and to control the air conditioner to start and set it to 26 degrees Celsius at 18:30.

[0062] In this way, by inferring users' habits at different time periods (i.e., each first time period), and adjusting or optimizing the control parameters of the device based on these habits, intelligent control can be achieved, improving the efficiency of IoT management and enhancing the user experience.

[0063] In some embodiments, sending a power feedback signal to the second device according to the physical control parameters includes:

[0064] For each user habit in the first time period, the minimum execution time of each user habit in the first time period is determined based on the detection data, and is taken as the execution time of the user habit;

[0065] Based on the power curve corresponding to the execution time and the physical control parameters, a power feedback signal is sent to the second device.

[0066] Specifically, considering that the execution time of user habits may vary, such as the time for turning on the lights in the example above, which could be any time between 18:00 and 18:10, we can analyze the minimum execution time (i.e., the earliest duration of the user habit) of each user habit within the first time period and use it as the execution time of that user habit.

[0067] After determining the execution time according to user habits, a power feedback signal is sent to the second device based on the power curve corresponding to the execution time and physical control parameters. This power feedback signal instructs the second device to perform intelligent control according to the physical control parameters corresponding to the power curve during the execution time. In other words, after receiving the power feedback signal, the second device determines the execution time and power curve, and then determines the corresponding physical control parameters based on the power curve. In this way, intelligent control can be performed according to the physical control parameters during the execution time.

[0068] Of course, this is just one example of determining the execution time. In practical applications, other rules can also be used. For example, if there is a time point with the most operations, then that time point can be selected as the execution time. For instance, if user habit analysis shows that the lights are turned on at 18:05 on 20 days within a month, then that time point can also be selected as the execution time.

[0069] In this way, by selecting the specific execution time based on user habits, more precise intelligent control can be achieved.

[0070] In some embodiments, the method further includes:

[0071] Receive a power curve from a second device, the power curve being used to characterize physical parameters;

[0072] If it is determined that the power curve meets the first condition, stop controlling the second device until the user habits of at least one second time period are re-determined;

[0073] Based on the user habits of at least one second time period, the physical control parameters corresponding to each second time period are redefined.

[0074] Specifically, the power curve is used to characterize physical parameters. The power curve can reflect physical parameters related to equipment operation, such as light switching, motor speed, pressure, temperature, and intelligent driving speed.

[0075] By checking whether the power curve meets a specific first condition, if the power curve meets the first condition, the control of the second device is stopped, which means that no more intelligent adjustments will be made until the user's habits are redefined.

[0076] Specifically, considering that user habits may change, if user habits change but intelligent control is still performed according to the original habits, it will not only fail to improve the user experience, but will also increase user confusion. Therefore, a judgment is proposed here on whether the power curve meets the first condition. This judgment can reflect whether user habits have changed. If they have changed, the user habits are redefined, and the corresponding physical control parameters are redefined based on the redefined user habits, and the control strategy of the second device is adjusted.

[0077] The at least one second time period may be the same as or different from the at least one first time period. It should be understood that the first time period and the second time period are not specific divisions of time ranges, but may be distinctions between user habits before the change and user habits after the change.

[0078] In some embodiments, determining that the power curve satisfies a first condition includes:

[0079] Based on the power curve within the first application cycle, determine the power curve and time for each first time period within the first application cycle;

[0080] The standard deviation is determined based on the power curve and time of each first time period within the first application cycle;

[0081] If the standard deviation exceeds the preset standard deviation, the power curve is determined to meet the first condition.

[0082] Specifically, the power collected in real time by the second device can be discretized according to time Δt to establish a power time sample set of the second device. This power time sample set can be denoted as: {(P1,t1),(P2,t2),...(P n ,t n P represents power, and t represents time.

[0083] After obtaining a power time sample set at fixed intervals of d days, the following calculations are performed:

[0084]

[0085] Where μ represents the average power at the same time within d days;

[0086] σ represents the standard deviation of the power sample over a fixed time interval of d.

[0087] Indicates day d. n The power at time t, here, t n It can be a single time value or a time range, such as a ten-minute interval before and after a specific time point. If it's a time range... This represents the maximum power fluctuation within this time range, i.e., the maximum fluctuation in the power curve, which reflects changes in the equipment's state.

[0088] Specifically, the preset standard deviation is a judgment threshold, denoted as .

[0089] The standard deviation over a fixed period of d days Then, within d days, t n The device power P at time 1 n According to d days t n The minimum value (i.e., the minimum time point, or execution time) is sent to the second device to achieve intelligent control; the corresponding second device translates the power feedback signal into corresponding physical parameters (such as temperature, light intensity, humidity, and the on / off status of the device) to perform intelligent control on the second device.

[0090] The standard deviation over a fixed period of d days When the physical parameters and power sent from the second device to the first device deviate significantly from previous values, the physical parameters, power, and date at that moment are stored in the power deviation value memory. Simultaneously, the first device ceases prediction activities until the value stored in the power mean square error memory meets the requirements within d days. At that time, the power P generated within d days is reused. n and t n The minimum value is sent to the second device for intelligent control. Here, the value stored in the power mean square error memory satisfies the condition within d days. This indicates that, based on the collected detection data, user habits can be redefined and meet the following criteria.

[0091] In practical applications, the first device can have a power deviation value memory to record large power deviation values ​​and times for different months, quarters, or other time periods. Whenever a significant power difference occurs at the same time on a given day within a certain period of the year, the date (year, month, and day) will be stored in the power deviation value memory. This is for analysis purposes, including considering user habits and whether those habits have changed.

[0092] In practical applications, the first device can also have a power mean square error memory to store the standard deviation of power time samples within a certain interval of days d. This standard deviation can change as the detection data increases or changes.

[0093] In some embodiments, the method further includes:

[0094] Receive detection data from the second device; the detection data also includes: the acquisition time corresponding to the physical parameters and the acquisition time corresponding to the power.

[0095] Here, physical parameters (such as temperature, pressure, humidity, etc.) and power may change over time. Determining the changing acquisition time means that the physical parameters and power at each moment correspond to a timestamp, forming a time series data.

[0096] When a physical parameter changes, it usually leads to a change in power consumption. For example, an increase in equipment temperature may cause its power consumption to increase.

[0097] A power curve essentially records how power changes over time, and these changes are caused by variations in physical parameters. Therefore, a power curve can serve as a tool to reflect changes in physical parameters. By analyzing power curves, the changing trends of physical parameters can be indirectly inferred. This facilitates the establishment of management data based on physical parameters and power.

[0098] In some embodiments, the method further includes:

[0099] Based on the detection data sent by the second device, the management data of the second device is determined, and the management data includes: physical parameters and power curves characterizing the physical parameters;

[0100] The management data is sent to the second device.

[0101] Here, the first device can send physical parameters and a power curve representing the physical parameters to the second device. Later, the first device can send only a power feedback signal, and realize intelligent control of the second device through the power curve indicated by the power feedback signal.

[0102] In some embodiments, determining the management data of the second device based on the detection data sent by the second device includes:

[0103] Based on the detection data, determine the power curve corresponding to the change in physical parameters;

[0104] The management data of the second device is determined based on the changing physical parameters and the power curve.

[0105] Specifically, the first device can establish the relationship between power and time based on the detection data, and draw a power-time waveform to obtain a power curve; it can also establish the relationship between physical parameters and time. Based on the correspondence between physical parameters and power curves, machine learning can be performed to obtain management data, which can be used to indicate which physical parameter change a particular power curve represents.

[0106] Of course, techniques such as neural network models can also be used to learn and determine the correspondence between changes in physical parameters and changes in the power curve, that is, to establish a correspondence between physical parameters and the power curve. No specific techniques or methods are limited here.

[0107] Specifically, a power curve refers to the change in power over a specific period of time, depicting how power (the rate of energy output or consumption) changes with time or a certain variable.

[0108] Considering that changes in physical parameters will lead to changes in power, such as when switching from a light-off state to a light-on state, the power may change suddenly or fluctuate sharply. Therefore, the power curve here can be understood as a power mutation curve. This mutation represents a sudden increase or decrease in the power value, which also represents a change in physical parameters.

[0109] Thus, characterizing changes in physical parameters using power curves effectively reduces data storage requirements. Subsequent changes in physical parameters can be inferred from power variations based on the power curve, eliminating the need to record detailed data for each physical parameter individually, thereby reducing data volume. Furthermore, power curves are concise and direct, facilitating analysis and management, improving system efficiency, and reducing the burden of redundant data storage.

[0110] In some embodiments, the method further includes:

[0111] Receive update data from the second device, and update the management data and / or power feedback signal according to the update data;

[0112] The updated data includes at least one of the following:

[0113] Physical parameters, power, and acquisition time not included in the management data;

[0114] The management data already includes the power curves and acquisition time of the physical parameters.

[0115] Specifically, with the use of the second device, the second device may collect new detection data, such as physical parameters not included in the previously established management data, or power not included; it can send this updated data to the first device for analysis in order to update the management data.

[0116] To facilitate intelligent control of the second device, the first device can continuously receive detection data from the second device. To reduce data volume, for physical parameters with corresponding power curves, only the power curve itself needs to be sent. The first device can then determine the corresponding physical parameters based on the power curve and, combined with time, further optimize user habits by updating the power feedback signal to update the intelligent control operation. This approach not only enables intelligent control through user habit analysis but also reduces data volume and alleviates the burden of redundant data storage.

[0117] In some embodiments, sending a power feedback signal to the second device includes:

[0118] The power feedback signal is encrypted based on an encryption algorithm, and the encrypted power feedback signal is sent to the second device.

[0119] Here, the encryption algorithm is used to encrypt the power feedback signal, primarily to protect data security and privacy. The encrypted data becomes unreadable unless the correct decryption key is used.

[0120] Any encryption algorithm can be used, such as symmetric encryption algorithms, asymmetric encryption algorithms, hash algorithms, etc.

[0121] Of course, the data sent from the second device to the first device, such as detection data and update data, can also be encrypted before transmission.

[0122] The first and second devices each have encryption and / or decryption algorithms to improve the security and privacy of data transmission.

[0123] Figure 3 A flowchart illustrating another IoT device control method provided in this disclosure embodiment; as shown Figure 3 As shown, the method can be applied to a second device, and the method includes:

[0124] Step 301: Receive the power feedback signal from the first device;

[0125] Step 302: Determine the physical control parameters based on the power feedback signal, and control the physical parameters based on the physical control parameters.

[0126] In some embodiments, the first device and the second device may be devices in an Internet of Things (IoT) system.

[0127] The first device can connect to at least one second device. The first device can be a gateway device, smart router, or control center in the Internet of Things (IoT) system. It can acquire the detection data collected by the second device, calculate and determine the corresponding physical control parameters, and intelligently control the second device based on these parameters. The second device can be a managed device added to the IoT, referred to as a network-connected device.

[0128] For example, such as Figure 2 As shown, the first device is a smart router that connects home appliances, industrial control equipment, smart transportation equipment, vehicle networking equipment, etc. Each of these home appliances, industrial control equipment, smart transportation equipment, and vehicle networking equipment serves as a second device in an Internet of Things (IoT) system.

[0129] exist Figure 2 In the illustrated IoT system, the first device acts as the core connector of the network, connecting and managing different types of second devices to ensure they can communicate and collaborate efficiently and securely within the network. These second devices connect to the network and achieve interconnection through a smart router. Furthermore, the first device can analyze and process the detection data collected by the second devices, enabling intelligent control over them.

[0130] In some embodiments, determining physical control parameters based on the power feedback signal includes:

[0131] The management data is queried based on the power feedback signal to determine the physical parameters corresponding to the power feedback signal; the management data includes: physical parameters and power curves characterizing the physical parameters.

[0132] Here, the management data includes: physical parameters and power curves characterizing the physical parameters; power feedback signals can be used to indicate the power curves, and by determining the physical parameters corresponding to the power curves, it can be determined which physical parameters need to be controlled, thus realizing intelligent control of the second device.

[0133] For example, the second device is a heating device, such as an electric water heater or industrial heating equipment. There is a relationship between the temperature (a physical parameter) and the power of the device. After learning from the preliminary test data, management data is determined, such as a certain temperature corresponding to a certain power curve, specifically: temperature 1 corresponds to power curve 1, temperature 2 corresponds to power curve 2.

[0134] During application, a power feedback signal is received. Based on this power feedback signal, the indicated or carried power curve 1 can be determined, and the corresponding physical parameter, temperature 1, can then be determined. Furthermore, the physical control parameter can be set to adjust to temperature 1.

[0135] In some embodiments, the method further includes:

[0136] The system receives management data from the first device, which is obtained by analyzing detection data from the second device.

[0137] Here, management data can be obtained by the first device through analysis of detection data from the second device, specifically as described in [the following text is missing]. Figure 1 The method is explained in the diagram and will not be repeated here.

[0138] In some embodiments, the method further includes:

[0139] Physical parameters are collected using at least one physical parameter sensor;

[0140] Power is collected using a power acquisition device;

[0141] The detection data is determined based on the physical parameters, the acquisition time corresponding to the physical parameters, the power, and the acquisition time corresponding to the power, and the acquired detection data is sent to the first device.

[0142] Here, the second device may have or be connected to at least one physical parameter sensor and a power acquisition unit to acquire the corresponding physical parameters and power, respectively. During acquisition, timestamp information is added to the physical parameters and power based on the acquisition time.

[0143] For example, physical parameter sensors include temperature sensors, pressure sensors, proximity sensors, Hall effect sensors, gas sensors, etc., which collect physical parameters such as temperature, pressure, whether the switch is activated, and current gas concentration.

[0144] In some embodiments, the method further includes:

[0145] Power and / or physical parameters are identified based on the collected detection data to determine updated data;

[0146] The update data is sent to the first device, the update data being used by the first device to update management data and / or power feedback signals; the update data includes at least one of the following:

[0147] Physical parameters, power, and acquisition time not included in the management data;

[0148] The management data already includes the power curves and acquisition time of the physical parameters.

[0149] Specifically, with the use of the second device, it may collect new detection data, such as physical parameters not included in the previously established management data, or power data not included in the existing data. It can send this updated data to the first device for analysis to update the management data. Specifically, after collecting power and / or physical parameters, the second device can compare the collected power and / or physical parameters with the management data to determine whether they already exist in the management data, thus determining whether they are updated data.

[0150] To facilitate intelligent control of the second device, the first device can continuously receive detection data from the second device. To reduce data volume, for physical parameters with corresponding power curves, only the power curve itself needs to be sent. The first device can then determine the corresponding physical parameters based on the power curve and, combined with time, further optimize user habits by updating the power feedback signal to update the intelligent control operation. This approach not only enables intelligent control through user habit analysis but also reduces data volume and alleviates the burden of redundant data storage.

[0151] In some embodiments, receiving a power feedback signal from a first device includes: receiving an encrypted power feedback signal from the first device;

[0152] Accordingly, physical control parameters are determined based on the power feedback signal, including:

[0153] Based on the decryption algorithm, the power feedback signal is decrypted, and the physical control parameters are determined based on the decrypted power feedback signal.

[0154] Here, the encryption algorithm is used to encrypt the power feedback signal, primarily to protect data security and privacy. The encrypted data becomes unreadable unless the correct decryption key is used.

[0155] Any encryption algorithm can be used, such as symmetric encryption algorithms, asymmetric encryption algorithms, hash algorithms, etc.

[0156] After receiving the encrypted data, the second device uses the corresponding decryption algorithm to decrypt it, thus obtaining the original data. In this way, both the first and second devices possess encryption and / or decryption algorithms, improving the security and privacy of data transmission.

[0157] Of course, the data sent from the second device to the first device, such as detection data and update data, can also be encrypted before transmission.

[0158] In this embodiment of the disclosure, the IoT system enables information interaction between the second device and the first device in the IoT through routing. The first device, by receiving detection data from the second device, can obtain the physical parameters and power information of the second device in real time, thereby calculating and determining the corresponding physical control parameters to achieve intelligent control of the second device and improve the management efficiency of the IoT system. Furthermore, by learning the relationship between the power curve and physical parameters, and using the power curve to represent changes in physical parameters, the waste of data transmission and processing resources caused by the massive data generated during the information transmission of multiple physical parameters in traditional IoT can be avoided, effectively reducing data transmission and processing requirements. Moreover, both the first and second devices can subsequently infer changes in physical parameters from power changes based on the power curve, without needing to record detailed data for each physical parameter separately, greatly reducing data storage and transmission, and alleviating the burden of redundant data storage.

[0159] Figure 4 A schematic diagram of the structure of a network access device provided in an embodiment of this disclosure; as shown Figure 4 As shown, the network access device (equivalent to an example of a second device) has or is connected to physical parameter sensors, a power acquisition module (which may be a power acquisition device or a power sensor or other device capable of acquiring power), a microcontroller, a processor, a routing device, etc.

[0160] Once a device enters the Internet of Things (IoT), physical parameter sensors can collect the physical parameters of the device in real time, and power acquisition modules can collect the power of the device in real time.

[0161] The collected data is encoded by the processor and formed into data packets, which are then transmitted to the routing device, and sent by the routing device to the smart router (equivalent to a first device example).

[0162] If the smart router generates the data that needs to be fed back (such as power feedback signal) after data analysis, it can encode the relevant data into data packets and send them to the routing device of the network-connected device. The routing device of the network-connected device then receives the data and transmits it to the processor. The processor decodes the data to form relevant physical control parameters, and then transmits the physical control parameters to the microcontroller to complete the intelligent control of the network-connected device.

[0163] Of course, a smart router can also send management data to the routing device of the network-connected device, which will receive and transmit the data to the processor of the network-connected device for later intelligent control.

[0164] Figure 5 A schematic diagram of the structure of a smart router provided in an embodiment of this disclosure; as shown Figure 5As shown, a smart router may include: a routing module, a processor, a physical power modeling module, and a power processing module.

[0165] The routing module is responsible for exchanging information with the network-connected devices in the Internet of Things (IoT), such as collecting physical parameters and power, and sending intelligent control signals.

[0166] The processor provides computational capabilities for the physical power modeling module and the power processing module. The physical power modeling module collects real-time signals of physical parameters and power, analyzes the signal data using the processor, and stores relevant modeling information.

[0167] The processor modeling process can include: when the physical parameters of a network-connected device change, the physical power modeling module records and stores the current power change curve (i.e., the power curve mentioned above), forming a library of power change curves corresponding to the physical parameters. After all power change parameters are stored, the processor can perform artificial intelligence recognition based on the power change curves to determine the physical parameters of the current network-connected device.

[0168] The structure of the power processing module is as follows: Figure 6 As shown, it can specifically include: memory 1, memory 2, and memory 3. When the real-time collected power is transmitted to the processor, after data processing, the predicted power value, power mean square value, and power deviation value are obtained and stored in the three memories respectively.

[0169] For example, memory 1 is used to store the predicted power value, which may refer to the power mutation curve corresponding to the predicted user habits.

[0170] Memory 2 is used to store the power mean square value, such as the standard deviation of a fixed-time power sample within a certain interval of days d; the calculation of the standard deviation is as follows:

[0171]

[0172] Where μ represents the average power at the same time within d days;

[0173] σ represents the standard deviation of the power sample over a fixed time interval of d.

[0174] Indicates day d. n The power at time t, here, t n It can be a single time value or a time range, such as a ten-minute interval before and after a specific time point. If it's a time range... This represents the maximum power fluctuation within this time range, i.e., the maximum fluctuation in the power curve, which reflects changes in the equipment's state.

[0175] Memory 3 is used to store power deviation values, specifically to record large power deviation values ​​and times for different months, quarters, or other time periods. Whenever a large power deviation occurs at the same time on a certain day within a certain period of the year, the year, month, and day of that time will be stored in the power deviation value memory. This allows for the analysis of user habits and the determination of whether user habits have changed.

[0176] For example, the fixed time standard deviation over d days Then, within d days, t n The device power P at time 1 n According to d days t n The minimum value (i.e., the minimum time point, or execution time) is sent to the second device to achieve intelligent control; the corresponding second device translates the power feedback signal into corresponding physical parameters (such as temperature, light intensity, humidity, and the on / off status of the device) to perform intelligent control on the second device.

[0177] The standard deviation over a fixed period of d days When the physical parameters and power sent from the second device to the first device deviate significantly from previous values, the physical parameters, power, and date at that moment are stored in the power deviation value memory. Simultaneously, the first device ceases prediction activities until the value stored in the power mean square error memory meets the requirements within d days. At that time, the power P generated within d days is reused. n and t n The minimum value is sent to the second device for intelligent control. Here, the value stored in the power mean square error memory satisfies the condition within d days. This indicates that, based on the collected detection data, user habits can be redefined and meet the following criteria.

[0178] Figure 7 A flowchart illustrating a power intelligent control IoT method provided in an embodiment of this disclosure is shown below. Figure 7 As shown, the method includes:

[0179] Step 701: The network access device collects signals;

[0180] Step 702: Encrypt the signal and upload it to the network;

[0181] Specifically, the system collects signals from network-connected devices using sensors and power acquisition devices, including various physical parameters and power; and feeds the collected signals back to the smart router via routing devices.

[0182] Step 703: The intelligent router separates the signal and performs machine learning to obtain the power feedback signal;

[0183] Step 704: The smart router performs intelligent management of network-connected devices through power feedback signals.

[0184] Specifically, the intelligent router analyzes the physical parameters and power of the network-connected devices and establishes a correspondence between these parameters. It can also establish a time-power function, use a support vector machine algorithm to learn the power-time function, and generate a power feedback signal. This power feedback signal is sent by the intelligent router to the network-connected devices, and the microcontrollers of these devices enable intelligent control of the network-connected devices.

[0185] It should be noted that network access devices are primarily controlled manually. Each manual control generates relevant physical and power signals that are fed back to the smart router. The smart router then uses a support vector machine algorithm to correct the deviation of the feedback signals, thereby achieving more precise intelligent control of network access devices.

[0186] Using the methods described above, the smart router can monitor the status of all connected devices through power detection and achieve intelligent control of these devices by transmitting power feedback signals. This method avoids the waste of data transmission and processing resources caused by the massive amounts of data generated during the transmission of information from multiple physical parameters in traditional IoT. Simultaneously, by using artificial intelligence processing methods to learn and feed back the time-sensitive operating modes of devices into the device operation, it achieves intelligent device management.

[0187] Figure 8 This is a schematic diagram of the structure of an Internet of Things (IoT) device control device provided in an embodiment of this disclosure; as shown below. Figure 8 As shown, the device is applied to a first apparatus, and the device includes:

[0188] A first processing module is configured to determine the physical control parameters of the second device based on detection data from the second device; the detection data includes physical parameters and power, and the physical control parameters are used to control the physical parameters of the second device.

[0189] The first communication module is used to send a power feedback signal to the second device according to the physical control parameters, the power feedback signal being used to indicate the physical control parameters.

[0190] In some embodiments, the first processing module is configured to determine a power time sample set based on the detection data, the power time sample set including at least one sample pair, each sample pair including a power curve and a time corresponding to the power curve; determine user habits for at least one first time period based on the at least one sample pair; and determine physical control parameters corresponding to each first time period based on the user habits for the at least one first time period.

[0191] In some embodiments, the first communication module is configured to determine, based on the detection data, the minimum execution time of each user habit within the first time period, as the execution time of the user habit;

[0192] The first communication module is further configured to send a power feedback signal to the second device based on the power curve corresponding to the execution time and the physical control parameters.

[0193] In some embodiments, the first communication module is configured to receive a power curve from a second device, the power curve being used to characterize physical parameters;

[0194] The first processing module is further configured to, if it is determined that the power curve meets the first condition, stop controlling the second device until the user habits of at least one second time period are redefined; and, based on the user habits of the at least one second time period, redetermine the physical control parameters corresponding to each second time period.

[0195] In some embodiments, the first processing module is configured to determine the power curve and time of each first time period within the first application cycle based on the power curve within the first application cycle; determine the standard deviation based on the power curve and time of each first time period within the first application cycle; and determine that the power curve satisfies a first condition if the standard deviation exceeds a preset standard deviation.

[0196] In some embodiments, the first processing module is further configured to determine management data of the second device based on the detection data sent by the second device, the management data including: physical parameters and power curves characterizing the physical parameters;

[0197] The first communication module is also used to send the management data to the second device.

[0198] In some embodiments, the first communication module is further configured to receive detection data from the second device; the detection data further includes: the acquisition time corresponding to the physical parameters and the acquisition time corresponding to the power.

[0199] In some embodiments, the first communication module is further configured to receive update data from the second device;

[0200] The first processing module is further configured to update the management data and / or power feedback signal according to the updated data;

[0201] The updated data includes at least one of the following:

[0202] Physical parameters, power, and acquisition time not included in the management data;

[0203] The management data already includes the power curves and acquisition time of the physical parameters.

[0204] In some embodiments, the first processing module is configured to determine the power curve corresponding to the change in physical parameters based on the detection data; and to determine the management data of the second device based on the physical parameters and the power curve at the time of change.

[0205] In some embodiments, the first processing module is used to encrypt the power feedback signal based on an encryption algorithm; the first communication module is used to send the encrypted power feedback signal to the second device.

[0206] It is understood that, when implementing the corresponding IoT device control method on the first device side, the IoT device control device provided in the above embodiments can allocate the above processing to different program modules as needed to complete all or part of the processing described above. Furthermore, the embodiments of the device and the corresponding method provided in the above embodiments belong to the same concept, and their specific implementation process is detailed in the method embodiments, which will not be repeated here.

[0207] Figure 9 This is a schematic diagram of another IoT device control device provided in an embodiment of this disclosure; as shown below. Figure 9 As shown, the device is applied to a second device, and the device includes:

[0208] The second communication module is used to receive power feedback signals from the first device;

[0209] The second processing module is used to determine physical control parameters based on the power feedback signal, and to control the physical parameters based on the physical control parameters.

[0210] In some embodiments, the second processing module is configured to query management data based on the power feedback signal to determine the physical parameters corresponding to the power feedback signal; the management data includes: physical parameters and power curves characterizing the physical parameters.

[0211] In some embodiments, the second communication module is configured to receive management data from the first device, the management data being obtained by the first device from analysis of detection data from the second device.

[0212] In some embodiments, the apparatus further includes: a data acquisition module for acquiring physical parameters using at least one physical parameter sensor; and acquiring power using a power acquisition device;

[0213] The second communication module is used to determine the detection data based on the physical parameters, the acquisition time corresponding to the physical parameters, the power, and the acquisition time corresponding to the power, and to send the acquired detection data to the first device.

[0214] In some embodiments, the second processing module is further configured to identify power and / or physical parameters based on the collected detection data, and determine updated data;

[0215] The second communication module is further configured to send the update data to the first device, the update data being used by the first device to update management data and / or power feedback signals; the update data includes at least one of the following:

[0216] Physical parameters, power, and acquisition time not included in the management data;

[0217] The management data already includes the power curves and acquisition time of the physical parameters.

[0218] In some embodiments, the second communication module is configured to receive an encrypted power feedback signal from the first device;

[0219] Correspondingly, the second processing module is used to decrypt the power feedback signal based on the decryption algorithm, and determine the physical control parameters based on the decrypted power feedback signal.

[0220] It is understood that, when implementing the corresponding IoT device control method on the second device side, the IoT device control device provided in the above embodiments can allocate the above processing to different program modules as needed to complete all or part of the processing described above. Furthermore, the embodiments of the device and the corresponding methods provided in the above embodiments belong to the same concept, and their specific implementation process is detailed in the method embodiments, which will not be repeated here.

[0221] This disclosure provides a computer-readable storage medium storing executable instructions, wherein the executable instructions, when executed by a processor, will trigger the processor to execute a routing method on a first device side or a routing method on a second device side provided in this disclosure.

[0222] According to embodiments of this disclosure, this disclosure also provides an electronic device and a readable storage medium.

[0223] Figure 10 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure; as shown below. Figure 10 As shown, the electronic device 100 includes: a processor 1001, and a memory 1002 communicatively connected to the processor 1001; the memory 1002 stores instructions that can be executed by the processor 1001.

[0224] If the electronic device is a first device, the instruction is executed by the processor 1001 to enable the processor 1001 to perform: determining physical control parameters of the second device based on detection data from the second device; the detection data includes physical parameters and power, and the physical control parameters are used to control the physical parameters of the second device; and sending a power feedback signal to the second device based on the physical control parameters, the power feedback signal being used to indicate the physical control parameters.

[0225] If the electronic device is a second device, the instruction is executed by the processor 1001 to enable the processor 1001 to perform: receiving a power feedback signal from the first device; determining physical control parameters based on the power feedback signal; and controlling the physical parameters based on the physical control parameters.

[0226] Of course, the electronic devices and corresponding method embodiments provided in the above embodiments belong to the same concept. The processor 1001 can also execute any of the above IoT device control methods. For details of its implementation process, please refer to the method embodiments, which will not be repeated here.

[0227] In practical applications, the electronic device 100 may further include at least one network interface 1003. The various components in the electronic device 100 are coupled together via a bus system 1004. It is understood that the bus system 1004 is used to implement communication between these components. In addition to a data bus, the bus system 1004 also includes a power bus, a control bus, and a status signal bus. However, for clarity, in... Figure 10 All buses are labeled as bus system 1004. The number of processors 1001 can be at least one, and the number of memories 1002 can be at least one. Network interface 1003 is used for wired or wireless communication between electronic device 100 and other devices.

[0228] The memory 1002 in this embodiment is used to store various types of data to support the operation of the electronic device 100.

[0229] The methods disclosed in the above embodiments of this disclosure can be applied to or implemented by the processor 1001. The processor 1001 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit of the hardware in the processor 1001 or by instructions in the form of software. The processor 1001 may be a general-purpose processor, a digital signal processor (DSP), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 1001 can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this disclosure. The general-purpose processor may be a microprocessor or any conventional processor, etc. The steps of the methods disclosed in the embodiments of this disclosure can be directly manifested as being executed by a hardware decoding processor, or being executed by a combination of hardware and software modules in the decoding processor. The software modules may be located in a storage medium, which is located in the memory 1002. The processor 1001 reads the information in the memory 1002 and completes the steps of the aforementioned method in conjunction with its hardware.

[0230] In some embodiments, the electronic device 100 may be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field-programmable gate arrays (FPGAs), general-purpose processors, controllers, microcontrollers (MCUs), microprocessors, or other electronic components to perform the aforementioned methods.

[0231] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0232] In the above description, the term "some embodiments" refers to a subset of all possible embodiments. However, it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0233] Unless otherwise defined, all technical and scientific terms used in this disclosure have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. The terminology used in this disclosure is for the purpose of describing embodiments of this disclosure only and is not intended to be limiting of this disclosure.

[0234] It should be understood that in the various embodiments of this disclosure, the sequence number of each implementation process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this disclosure.

[0235] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this disclosure, "a plurality of" means two or more, unless otherwise explicitly specified.

[0236] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for controlling an Internet of Things (IoT) device, characterized in that, Applied to a first device, the method includes: Based on the detection data from the second device, the physical control parameters of the second device are determined; the detection data includes physical parameters and power, and the physical control parameters are used to control the physical parameters of the second device. According to the physical control parameters, a power feedback signal is sent to the second device, the power feedback signal being used to indicate the physical control parameters; The step of determining the physical control parameters of the second device based on the detection data sent by the second device includes: A power-time sample set is determined based on the detection data. The power-time sample set includes at least one sample pair, and each sample pair includes a power curve and the time corresponding to the power curve. Based on the at least one sample pair, determine at least one user habit for a first time period; Based on the user habits of at least one first time period, determine the physical control parameters corresponding to each first time period; Based on the physical control parameters, a power feedback signal is sent to the second device, including: For each user habit in the first time period, the minimum execution time of each user habit in the first time period is determined based on the detection data, and is taken as the execution time of the user habit; Based on the power curve corresponding to the execution time and the physical control parameters, a power feedback signal is sent to the second device; The method further includes: Receive a power curve from a second device, the power curve being used to characterize physical parameters; If it is determined that the power curve meets the first condition, stop controlling the second device until the user habits of at least one second time period are re-determined; Based on the user habits of at least one second time period, redetermine the physical control parameters corresponding to each second time period; The method further includes: Based on the detection data sent by the second device, determine the management data of the second device, the management data including: physical parameters and power curves characterizing the physical parameters; send the management data to the second device; The step of determining the management data of the second device based on the detection data sent by the second device includes: determining the power curve corresponding to the change of physical parameters based on the detection data; and determining the management data of the second device based on the physical parameters and the power curve at the time of change.

2. The method according to claim 1, characterized in that, Determining that the power curve satisfies the first condition includes: Based on the power curve within the first application cycle, determine the power curve and time for each first time period within the first application cycle; The standard deviation is determined based on the power curve and time of each first time period within the first application cycle; If the standard deviation exceeds the preset standard deviation, the power curve is determined to meet the first condition.

3. The method according to claim 1, characterized in that, The method further includes: Receive detection data from the second device; the detection data also includes: the acquisition time corresponding to the physical parameters and the acquisition time corresponding to the power.

4. The method according to claim 1 or 3, characterized in that, The method further includes: Receive update data from the second device, and update the management data and / or power feedback signal according to the update data; The updated data includes at least one of the following: Physical parameters, power, and acquisition time not included in the management data; The management data already includes the power curves and acquisition time of the physical parameters.

5. The method according to claim 1, characterized in that, Sending the power feedback signal to the second device includes: The power feedback signal is encrypted based on an encryption algorithm, and the encrypted power feedback signal is sent to the second device.

6. An Internet of Things (IoT) device control device, characterized in that, The device is applied to the first apparatus, the device comprising: A first processing module is configured to determine the physical control parameters of the second device based on detection data from the second device; the detection data includes physical parameters and power, and the physical control parameters are used to control the physical parameters of the second device. The first communication module is configured to send a power feedback signal to the second device according to the physical control parameters, wherein the power feedback signal is used to indicate the physical control parameters; The first processing module is configured to determine a power time sample set based on the detection data, the power time sample set including at least one sample pair, each sample pair including a power curve and a time corresponding to the power curve; determine user habits for at least one first time period based on the at least one sample pair; and determine physical control parameters corresponding to each first time period based on the user habits for the at least one first time period. The first communication module is configured to determine, based on the detection data, the minimum execution time of each user habit within the first time period, as the execution time of the user habit; the first communication module is also configured to send a power feedback signal to the second device based on the execution time and the power curve corresponding to the physical control parameters. The first communication module is used to receive a power curve from the second device, the power curve being used to characterize physical parameters; The first processing module is further configured to, if it is determined that the power curve meets the first condition, stop controlling the second device until the user habits of at least one second time period are redefined; and, based on the user habits of the at least one second time period, redetermine the physical control parameters corresponding to each second time period. The first processing module is further configured to determine management data of the second device based on the detection data sent by the second device, the management data including: physical parameters and power curves characterizing the physical parameters; the first communication module is further configured to send the management data to the second device; The first processing module is used to determine the power curve corresponding to the change of physical parameters based on the detection data; and to determine the management data of the second device based on the physical parameters and the power curve at the time of change.

7. An electronic device, characterized in that, include: At least one processor; And, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 5.

8. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to perform the method according to any one of claims 1 to 5.

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