Internet of Things equipment control method and device and related equipment

Abstract

The invention provides an Internet of Things equipment control method and device and related equipment, and the method comprises the steps that first equipment determines physical control parameters of second equipment according to detection data from the second equipment; the detection data comprises physical parameters and power, and the physical control parameters are used for controlling the physical parameters of the second equipment; and sending a power feedback signal to the second device according to the physical control parameter, the power feedback signal being used for indicating the physical control parameter. Correspondingly, the second equipment receives a power feedback signal from the first equipment; physical control parameters are determined according to the power feedback signals, and physical parameters are controlled according to the physical control parameters.

Description

Technical Field

[0001] The present disclosure relates to the technical field of Internet of Things, and in particular to an Internet of Things device control method, device and related equipment. Background Art

[0002] The Internet of Things (IoT) is one of the hot topics in today's science and technology field. Through information sensing devices, devices are connected to the network according to standard protocols, and information is exchanged and communicated through information dissemination media, thereby realizing functions such as intelligent identification, positioning, tracking and supervision. With the continuous upgrading and acceleration of the domestic Internet, the number and stability of connected devices in the Internet of Things have also been greatly improved, allowing more devices to transmit data efficiently and in real time. With the continuous development of electronic devices, the cost of IoT devices has continued to decrease, which has promoted the widespread application of IoT in various fields, such as smart homes, smart car networking, smart transportation, smart industrial control, etc. How to improve the management efficiency of the Internet of Things system is one of the problems that need to be solved at present. Summary of the invention

[0003] The present disclosure provides an Internet of Things device control method, device, electronic device and storage medium to at least solve the above technical problems existing in the prior art.

[0004] In a first aspect, an embodiment of the present disclosure provides an Internet of Things device control method, which is applied to a first device, and the method includes:

[0005] Determine a physical control parameter of the second device according to detection data from the second device; the detection data includes a physical parameter and power, and the physical control parameter is used to control a physical parameter of the second device;

[0006] A power feedback signal is sent to the second device according to the physical control parameter, where the power feedback signal is used to indicate the physical control parameter.

[0007] In a second aspect, an embodiment of the present disclosure provides an Internet of Things device control method, which is applied to a second device, and the method includes:

[0008] receiving a power feedback signal from a first device;

[0009] A physical control parameter is determined according to the power feedback signal, and a physical parameter is controlled according to the physical control parameter.

[0010] In a third aspect, an embodiment of the present disclosure provides an IoT device control device, the device being applied to a first device, the device comprising:

[0011] A first processing module, configured to determine a physical control parameter of the second device according to detection data from the second device; the detection data includes a physical parameter and power, and the physical control parameter is used to control a physical parameter 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 parameter, where the power feedback signal is used to indicate the physical control parameter.

[0013] In a fourth aspect, an embodiment of the present disclosure provides an IoT device control device, the device being applied to a second device, the device comprising:

[0014] A second communication module, configured to receive a power feedback signal from the first device;

[0015] The second processing module is used to determine a physical control parameter according to the power feedback signal, and control a physical parameter according to the physical control parameter.

[0016] In a fifth aspect, an embodiment of the present disclosure provides an electronic device, comprising: 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, and the instructions are executed by the at least one processor so that the at least one processor can execute the Internet of Things device control method on the first device side; or, so that the at least one processor can execute the Internet of Things device control method on the second device side.

[0017] In a sixth aspect, an embodiment of the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the Internet of Things device control method on the first device side; or, the computer instructions are used to cause a computer to execute the Internet of Things device control method on the second device side.

[0018] The disclosed embodiments provide a method, apparatus, electronic device and storage medium for controlling an IoT device, the method comprising: a first device determines a physical control parameter of the second device based on detection data from the second device; the detection data comprises physical parameters and power, and the physical control parameter is used to control the physical parameter of the second device; a power feedback signal is sent to the second device based on the physical control parameter, and the power feedback signal is used to indicate the physical control parameter. Accordingly, the second device receives a power feedback signal from the first device; determines the physical control parameter based on the power feedback signal, and controls the physical parameter based on the physical control parameter. In this way, the first device can obtain the physical parameters and power information of the second device in real time by receiving the detection data from the second device, thereby calculating and determining the corresponding physical control parameters, realizing intelligent control of the second device, and improving the management efficiency of the IoT system.

[0019] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flowchart of a method for controlling an Internet of Things device provided by an embodiment of the present disclosure;

[0021] Figure 2 A schematic diagram of the structure of an Internet of Things system provided by an embodiment of the present disclosure;

[0022] Figure 3 A flowchart of another method for controlling an Internet of Things device provided by an embodiment of the present disclosure;

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

[0024] Figure 5 A schematic diagram of the structure of an intelligent router provided in an application embodiment of the present disclosure;

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

[0026] Figure 7 A schematic diagram of a flow chart of a power intelligent control Internet of Things method provided by an embodiment of the present disclosure;

[0027] Figure 8 A schematic diagram of the structure of an Internet of Things device control device provided by an embodiment of the present disclosure;

[0028] Fig. 9A schematic diagram of the structure of another IoT device control device provided by an embodiment of the present disclosure;

[0029] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0030] In order to make the purpose, features, and advantages of the present disclosure more obvious and easy to understand, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present disclosure.

[0031] Before further describing the embodiments of the present disclosure in detail, the related technologies involved in the embodiments of the present disclosure are described.

[0032] Smart IoT mainly refers to a system that shares the physical parameters of various devices through the Internet, allowing devices to be intelligently scheduled and work together. The key technologies involved are mainly the following:

[0033] Sensor technology: Through sensors, various physical parameters of networked devices in the IoT system can be monitored to understand the status of networked devices; and relevant physical parameters can be converted into electrical signals and fed back to the control center in the IoT system;

[0034] Communication network technology: Each networked device in the IoT system needs to transmit data and interconnect with the control center through the communication network. By improving the communication network technology in the IoT, the real-time performance and stability of the IoT system can be effectively improved.

[0035] Data processing and analysis technology: The control center in the IoT system can collect, store, process and analyze the data generated by the connected devices, extracting valuable information to optimize the operation of the IoT system and support decision-making;

[0036] Security and privacy protection technology. The IoT system will generate a large amount of data interaction during its working process. Therefore, protecting the security and privacy of networked devices in the IoT system during data transmission becomes one of the important considerations.

[0037] Edge computing and distributed system technology. In the IoT system, there are many devices connected to the network and the amount of data is large, which will bring higher computing power to the data processing of the control center. By distributing the computing and data processing functions to each connected device or network node, it will help improve the system data processing efficiency, reduce network latency and increase the security and stability of the system.

[0038] The Internet of Things is a network based on information carriers such as the Internet and traditional telecommunications networks, which allows all devices that can access the network to achieve interconnection through physical information collection. At present, the Internet of Things mainly monitors various physical parameters of the network, such as temperature, voltage, current, air pressure, humidity and other physical parameters.

[0039] However, due to the large variety of physical parameters collected by the sensors of the internal devices of the Internet of Things, with the long-term use of the Internet of Things system, the data collection process will generate a large amount of data. Secondly, the traditional Internet of Things remotely monitors and controls the connected network devices through the network, which lacks certain intelligence; and with the increase in the number of networked devices, it will also cause great difficulties for managers to monitor the equipment. In summary, due to the increase in data volume and the lack of intelligent monitoring of networked devices, management efficiency is insufficient.

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

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

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

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

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

[0045] The first device can be connected to at least one second device. The first device can be a gateway device, intelligent router or control center in the Internet of Things system. It can obtain the detection data collected by the second device, calculate and determine the corresponding physical control parameters, and intelligently control the second device through the physical control parameters. The second device can be a managed device added to the Internet of Things, which can also be referred to as a networked device.

[0046] For example, Figure 2 As shown, the first device is an intelligent router, which connects household appliances, industrial control equipment, smart transportation equipment, Internet of Vehicles equipment, etc. The above household appliances, industrial control equipment, smart transportation equipment, Internet of Vehicles equipment, etc. are respectively used as the second device in an Internet of Things system.

[0047] exist Figure 2 In the IoT system shown, the first device, as the core connector of the network, can connect and manage different types of second devices to ensure that they can communicate and collaborate with each other efficiently and securely in the network. These second devices are connected to the network through intelligent routers and achieve interconnection. Of course, the first device can also analyze and process the detection data collected by the second device to achieve intelligent management and control of the second device.

[0048] In some embodiments, determining the physical control parameter of the second device according to the detection data sent by the second device includes:

[0049] Determine a power time sample set according to the detection data, wherein the power time sample set includes at least one sample pair, and each sample pair includes a power curve and a time corresponding to the power curve;

[0050] Determining a user habit of at least one first time period according to the at least one sample pair;

[0051] According to the user habits of the at least one first time period, a physical control parameter corresponding to each first time period is determined.

[0052] Specifically, the detection data includes the collected power and time. A power curve can be determined based on the detection data. The power curve reflects the process of power change. For example, the power consumption of a networked device over a period of time can be reflected in the form of a power curve due to power changes.

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

[0054] In addition, the time can be a specific time point of a certain day, so that the sample pair can help identify the user's periodic behavior pattern. That is, the detection data can not only reflect the power changes of the device, but also record these changes occurring on a specific day (such as 8 pm every Monday) or a certain time point (such as 7 am every day). In this way, the sample pair can reveal the user's habits, such as certain behaviors occur at fixed times every day or week, thereby analyzing the user's periodic habits.

[0055] It should be understood that since the power curve reflects the change of power over time, the power curve corresponds to time, that is, each data point on the power curve can be associated with a specific time, that is, each power value corresponds to the time when it was measured. In this way, more accurate data analysis can be achieved.

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

[0057] For example, a second device is a smart lamp, and a 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 (light off); time 20:00, power 60W (light on);

[0060] If this situation continues for several cycles, such as every day, the user's lighting habits in a specific time period can be identified by analyzing the data. For example, if the user usually turns on the light between 18:05 and 19:00, the generated physical control parameters can be used to control the smart lamp to automatically turn on the light at 18:05.

[0061] Specifically, the range of each first time period in the at least one first time period may be the same or different. Here, the user habits of at least one first time period are determined, and the characterization can determine different user habits in the same or different first time periods. For example, the first time period is from 18:05 to 19:00, and it may have different user habits, such as turning on the lights and turning on the air conditioner. For another example, a first time period may be from 18:05 to 19:00, and its corresponding user habit may be turning on the lights, and another first time period may be from 18:30 to 19:00, and its corresponding user habit may be turning on the air conditioner and cooling to 26 degrees. The generated physical control parameters can be used to control the smart lamps to automatically turn on the lights at 18:05, and control the air conditioner to start the air conditioner at 18:30 and cool to 26 degrees.

[0062] In this way, by inferring the user's habits in 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 is achieved, the efficiency of IoT management is improved, and the user experience is enhanced.

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

[0064] For each user habit in the first time period, determining, according to the detection data, a minimum execution time of each user habit in the first time period as the execution time of the user habit;

[0065] A power feedback signal is sent to the second device according to the execution time and the power curve corresponding to the physical control parameter.

[0066] Specifically, considering that the execution time of user habits has certain deviations, such as the light-on time in the above example, which may be any time point between 18:00 and 18:10, for each user habit in the first time period, the minimum execution time of the user habit in the first time period (i.e., the earliest duration of the user habit) can be analyzed as the execution time of the user habit.

[0067] After determining the execution time that the user is accustomed to, a power feedback signal is sent to the second device according to the power curve corresponding to the execution time and the physical control parameters. The power feedback signal instructs the second device to perform intelligent control at the execution time according to the physical control parameters corresponding to the power curve. That is, the second device determines the execution time and the power curve after receiving the power feedback signal, and then determines the corresponding physical control parameters according to the power curve. In this way, intelligent control can be performed according to the physical control parameters at the execution time later.

[0068] Of course, this is only an example of determining the execution time. In actual application, other rules can be used. For example, if there is a time point with the most operations, then this time point can be selected as the execution time. For example, after analyzing user habits, if the lights are turned on at 18:05 on 20 days in a month, then this time point can also be selected as the execution time.

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

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

[0071] receiving a power curve from a second device, wherein the power curve is used to characterize a physical parameter;

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

[0073] The physical control parameter corresponding to each second time period is re-determined according to the user habits of the at least one second time period.

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

[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 intelligent adjustment is performed until the user habit is re-determined.

[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 increase user troubles. Therefore, a judgment on whether the power curve meets the first condition is proposed here, which can reflect whether the user habits have changed; if changed, the user habits are redetermined, and the corresponding physical control parameters are redetermined according to the redetermined 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 the time range, but may be a distinction between user habits before the change and re-determined user habits.

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

[0079] Determine, according to the power curve in the first application cycle, the power curve and time of each first time period in the first application cycle;

[0080] determining a standard deviation value according to a power curve and time in each first time period in the first application cycle;

[0081] If the standard deviation value exceeds a preset standard deviation, it is determined that the power curve satisfies a first condition.

[0082] Specifically, the power collected by the second device in real time can be discretized according to time Δt to establish a power time sample set of the second device. The power time sample set can be recorded as: {(P 1 ,t 1 ),(P 2 ,t 2 ),...(P n ,t n )}. P represents power and t represents time.

[0083] After obtaining a fixed-time power-time sample set within a certain interval of days d, the following calculation is performed:

[0084]

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

[0086] σ represents the standard deviation of fixed-time power samples within a certain interval of days d;

[0087] represents the dth day t n The power at the moment, here, t n It can be a time value or a time range value, such as the range of ten minutes before and after a time point. If it is a time range value, Indicates the maximum power mutation value within this time range, that is, the maximum power mutation value in the power curve. This value can reflect the change in the device status.

[0088] Specifically, the preset standard deviation is a judgment threshold, assuming that the preset standard deviation is recorded as

[0089] The standard deviation of fixed time within d days When t n The device power P corresponding to the moment n According to d days t n The minimum value (i.e., the minimum time point, i.e., the execution time) is sent to the second device to realize intelligent control; the corresponding second device translates the power feedback signal into corresponding physical parameters (such as temperature, light amplitude, humidity, and the switching state of the device) to perform intelligent control on the second device.

[0090] The standard deviation of fixed time within d days That is, when the physical parameters and power sent by the second device to the first device deviate greatly from the previous ones, the physical parameters, power and year-month-day period at that moment will be stored in the power deviation value memory; at the same time, the first device stops the prediction activity until the value stored in the power mean square error memory meets the value within d days. When the power P generated in d days is used again 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 minimum value within d days. It means that based on the collected test data, user habits can be re-determined and meet

[0091] In actual application, the first device may have a power deviation value memory for recording the larger power deviation values ​​and times in different months, different quarters or other different time periods. Whenever a power time point has a larger power difference at the same time of the day during a certain period of the year, the year, month and day of this time will be stored in the power deviation value memory, so as to analyze user habits and whether user habits have changed.

[0092] In actual application, the first device may also have a power mean square error memory for storing the standard deviation of power time samples within a certain interval of days d. The standard deviation may change as the detection data increases or changes.

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

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

[0095] Here, physical parameters (such as temperature, pressure, humidity, etc.) and power may change over time. Determining the acquisition time of the changes means that the physical parameters and power at each moment have corresponding timestamps to form a time series data.

[0096] When a physical parameter changes, it usually results in a change in power. For example, an increase in the temperature of a device may cause it to consume more power.

[0097] The power curve actually records the changes in power over time, and these changes are caused by changes in physical parameters. Therefore, the power curve can be used as a tool to reflect the changes in physical parameters. By analyzing the power curve, the change trend of physical parameters can be indirectly inferred. In this way, it is convenient to establish management data based on physical parameters and power.

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

[0099] Determining management data of the second device according to the detection data sent by the second device, the management data comprising: a physical parameter and a power curve representing the physical parameter;

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

[0101] Here, the first device may send physical parameters and a power curve representing the physical parameters to the second device. Later, the first device may only send 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 according to the detection data sent by the second device includes:

[0103] Determine, based on the detection data, a power curve corresponding to a change in a physical parameter;

[0104] Management data of the second device is determined according to the physical parameter and the power curve when the physical parameter changes.

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

[0106] Of course, it is also possible to use techniques such as neural network models for learning to determine the corresponding relationship between the change of physical parameters and the change of power curve, that is, to establish the corresponding relationship between physical parameters and power curve. The specific technology and method for determination are not limited here.

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

[0108] Considering that changes in physical parameters will bring about changes in power, such as when the light is turned on and off, the power may change suddenly or fluctuate sharply. Therefore, the power curve here can be understood as a power mutation curve. This mutation shows a sudden increase or decrease in the power value, and also represents the change of physical parameters.

[0109] In this way, the power curve can be used to characterize the changes in physical parameters, which can effectively reduce the need for data storage. The changes in physical parameters can be inferred from the power changes based on the power curve, without the need to record the detailed data of each physical parameter separately, thus reducing the amount of data. In addition, the power curve is concise and direct, easy to analyze and manage, which can improve the efficiency of the system and reduce the burden of redundant data storage.

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

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

[0112] The update 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 curve and acquisition time of the physical parameters.

[0115] Specifically, as the second device is used, the second device may collect new detection data, such as physical parameters not included in the management data established earlier, or power not included; it can send these updated data to the first device for analysis to update the management data.

[0116] In order to facilitate the intelligent control of the second device, the first device can continuously receive the detection data of the second device. In order to reduce the amount of data, for physical parameters that have corresponding power curves, only the power curve can be sent. The first device can also determine the corresponding physical parameters based on the power curve, and continue to optimize user habits in combination with time, and update the intelligent control operation by updating the power feedback signal. In this way, not only can user habits be analyzed to achieve intelligent control, but also the amount of data can be reduced, alleviating 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, the main purpose of which is to protect the security and privacy of the data. The encrypted data will become unreadable unless the correct decryption key is used.

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

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

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

[0123] Figure 3 A flowchart of another method for controlling an IoT device provided by an embodiment of the present disclosure; Figure 3 As shown, the method can be applied to a second device, and the method includes:

[0124] Step 301: receiving a power feedback signal from a first device;

[0125] Step 302: determine a physical control parameter according to the power feedback signal, and control a physical parameter according to the physical control parameter.

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

[0127] The first device can be connected to at least one second device. The first device can be a gateway device, intelligent router or control center in the Internet of Things system. It can obtain the detection data collected by the second device, calculate and determine the corresponding physical control parameters, and intelligently control the second device through the physical control parameters. The second device can be a managed device added to the Internet of Things, referred to as a networked device.

[0128] For example, Figure 2 As shown, the first device is an intelligent router, which connects household appliances, industrial control equipment, smart transportation equipment, Internet of Vehicles equipment, etc. The above household appliances, industrial control equipment, smart transportation equipment, Internet of Vehicles equipment, etc. are respectively used as the second device in an Internet of Things system.

[0129] exist Figure 2 In the IoT system shown, the first device, as the core connector of the network, can connect and manage different types of second devices to ensure that they can communicate and collaborate with each other efficiently and securely in the network. These second devices are connected to the network through intelligent routers and achieve interconnection. Of course, the first device can also analyze and process the detection data collected by the second device to achieve intelligent management and control of the second device.

[0130] In some embodiments, determining a physical control parameter according to the power feedback signal includes:

[0131] Management data is queried according to the power feedback signal to determine the physical parameters corresponding to the power feedback signal; the management data includes: the physical parameters and the power curve representing the physical parameters.

[0132] Here, the management data includes: physical parameters and a power curve characterizing the physical parameters; the power feedback signal can be used to indicate the power curve, and by determining the physical parameters corresponding to the power curve, it is determined which physical parameter is actually to be controlled, thereby achieving 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, and there is a relationship between the temperature (a physical parameter) and power of the device. Management data is determined through learning of the previous detection data, 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] When the power feedback signal is received, the power curve 1 indicated or carried by the power feedback signal is determined according to the power feedback signal, and the corresponding physical parameter: temperature 1 can be determined. Then, the physical control parameter can be determined to be adjusted to temperature 1.

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

[0136] Management data from the first device is received, where the management data is obtained by the first device based on analysis of detection data from the second device.

[0137] Here, the management data can be obtained by the first device according to the detection data from the second device. Figure 1 The method is described in detail and will not be repeated here.

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

[0139] collecting a physical parameter using at least one physical parameter sensor;

[0140] Collecting power using a power collector;

[0141] Determine detection data according to the physical parameter, the collection time corresponding to the physical parameter, the power, and the collection time corresponding to the power, and send the collected detection data to the first device.

[0142] Here, the second device may have or be connected to at least one physical parameter sensor and a power collector, and collect corresponding physical parameters and power respectively. During the collection, timestamp information is added to the physical parameters and power according to the collection 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 started, current gas concentration, etc.

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

[0145] Perform power and / or physical parameter identification based on the collected detection data to determine update data;

[0146] Sending the update data to the first device, where the update data is used for the first device to update management data and / or a power feedback signal; 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 curve and acquisition time of the physical parameters.

[0149] Specifically, as the second device is used, the second device may collect new detection data, for example, physical parameters not included in the management data established earlier, or power not included; it can send these 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, so as to determine whether they are updated data.

[0150] In order to facilitate the intelligent control of the second device, the first device can continuously receive the detection data of the second device. In order to reduce the amount of data, for physical parameters that have corresponding power curves, only the power curve can be sent. The first device can also determine the corresponding physical parameters based on the power curve, and continue to optimize user habits in combination with time, and update the intelligent control operation by updating the power feedback signal. In this way, not only can user habits be analyzed to achieve intelligent control, but also the amount of data can be reduced, alleviating 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, determining the physical control parameter according to the power feedback signal includes:

[0153] The power feedback signal is decrypted based on a decryption algorithm, and a physical control parameter is determined according to the decrypted power feedback signal.

[0154] Here, the encryption algorithm is used to encrypt the power feedback signal, the main purpose of which is to protect the security and privacy of the data. The encrypted data will become unreadable unless the correct decryption key is used.

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

[0156] After receiving the encrypted data, the second device uses the corresponding decryption algorithm to decrypt and obtain the original data. In this way, the first device and the second device respectively have encryption and / or decryption algorithms to improve the security and privacy of data transmission.

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

[0158] In the disclosed embodiment, the Internet of Things system realizes information exchange between the second device and the first device in the Internet of Things through routing. The first device can obtain the physical parameters and power information of the second device in real time by receiving the detection data from the second device, thereby calculating and determining the corresponding physical control parameters, realizing intelligent control of the second device, and improving the management efficiency of the Internet of Things system. In addition, by learning the relationship between the power curve and the physical parameters and characterizing the changes in the physical parameters through the power curve, it is possible to avoid the waste of data transmission and processing resources caused by the massive data generated in the process of information transmission of multiple physical parameters in the traditional Internet of Things, and effectively reduce the demand for data transmission and processing; and, subsequently, both the first device and the second device can infer the changes in the physical parameters from the power changes according to the power curve, without the need to record the detailed data of each physical parameter separately, which also greatly reduces the storage and transmission of the amount of data and reduces the burden of redundant data storage.

[0159] Figure 4 A schematic diagram of a network access device provided by an application embodiment of the present disclosure; Figure 4 As shown, the network access device (equivalent to an example of a second device) has or is connected to a physical parameter sensor, a power collection module (a power collector or a power sensor or other device that can collect power may be used), a microcontroller, a processor, a routing device, etc.

[0160] After the network-connected device enters the Internet of Things, the physical parameter sensor can collect the physical parameters of the network-connected device in real time, and the power collection module can collect the power of the network-connected device in real time.

[0161] The collected data is encoded by the processor and formed into a data packet and transmitted to the routing device, and then sent by the routing device to the intelligent router (equivalent to an example of the first device).

[0162] If the intelligent router generates data that needs to be fed back (such as a power feedback signal) after data analysis, the relevant data can be encoded into a data packet and sent to the routing device of the network-access device; the routing device of the network-access 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-access device.

[0163] Of course, the smart router can also send management data to the routing device of the networked device, which will be received by the routing device of the networked device and transmitted to the processor of the networked device for subsequent intelligent control.

[0164] Figure 5 A schematic diagram of the structure of an intelligent router provided by an application embodiment of the present disclosure; Figure 5As shown, the intelligent 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 information exchange with the networked device routing in the Internet of Things, such as collecting physical parameters, power, and sending intelligent control signals.

[0166] The processor is used to provide computing functions for the physical power modeling module and the power processing module. The physical power modeling module is used to collect real-time signals of physical parameters and power, analyze the signal data through the processor, and store relevant modeling information.

[0167] The processor modeling process may include: when the physical parameters of a networked device change, the physical power modeling module records and stores the current power mutation curve (i.e., the above-mentioned power curve) to form a power change mutation curve library corresponding to the physical parameters. After all power change parameters are stored, the processor can perform artificial intelligence recognition based on the power change curve to determine the physical parameters of the current networked 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, the predicted power value, power mean square value, and power deviation value are obtained through data processing and are stored in the three memories respectively.

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

[0170] The memory 2 is used to store the mean square power value, such as storing the standard deviation of the fixed time power samples within a certain interval of days d; wherein the value of the standard deviation is calculated as follows:

[0171]

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

[0173] σ represents the standard deviation of fixed-time power samples within a certain interval of days d;

[0174] represents the dth day t n The power at the moment, here, t n It can be a time value or a time range value, such as the range of ten minutes before and after a time point. If it is a time range value, Indicates the maximum power mutation value within this time range, that is, the maximum power mutation value in the power curve. This value can reflect the change in the device status.

[0175] The memory 3 is used to store the power deviation value, specifically to record the larger power deviation value and time in different months, different quarters or other different time periods. Whenever a power time point has a larger power difference at the same time of the day during a certain period of the year, the year, month and day of this time will be stored in the power deviation value memory, so as to analyze the user's habits and determine whether the user's habits have changed.

[0176] For example, when the fixed time standard deviation within d days is When t n The device power P corresponding to the moment n According to d days t n The minimum value (i.e., the minimum time point, i.e., the execution time) is sent to the second device to realize intelligent control; the corresponding second device translates the power feedback signal into corresponding physical parameters (such as temperature, light amplitude, humidity, and the switching state of the device) to perform intelligent control on the second device.

[0177] The standard deviation of fixed time within d days That is, when the physical parameters and power sent by the second device to the first device deviate greatly from the previous ones, the physical parameters, power and year-month-day period at that moment will be stored in the power deviation value memory; at the same time, the first device stops the prediction activity until the value stored in the power mean square error memory meets the value within d days. When the power P generated in d days is used again 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 minimum value within d days. It means that based on the collected test data, user habits can be re-determined and meet

[0178] Figure 7 A schematic diagram of a power intelligent control Internet of Things method provided by the application embodiment of the present disclosure is shown in FIG. 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 sensors and power collectors are used to collect signals from networked devices, including various physical parameters and power; and the collected signals are fed back to the smart router through the routing device.

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

[0183] Step 704: The intelligent router performs intelligent management of networked devices through power feedback signals.

[0184] Specifically, the intelligent router analyzes the physical parameters and power of the networked device and establishes a corresponding relationship between the power and physical 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, which is sent by the intelligent router to the networked device, and the networked device is intelligently controlled by the microcontroller of the networked device.

[0185] It should be noted that network-connected devices are preferentially controlled manually. Each manual control will generate relevant physical and power signals that are fed back to the smart router. The smart router then corrects the deviation of the feedback signal based on the support vector machine algorithm, thereby achieving more accurate intelligent control of network-connected devices.

[0186] Through the above method, the smart router can monitor the status of all networked devices through power detection, and realize intelligent control of networked devices through the transmission of power feedback signals. This method can avoid the waste of data transmission and processing resources caused by the massive data generated in the process of information transmission of multiple physical parameters in the traditional Internet of Things. At the same time, the operation mode of devices with strong time limits is learned through artificial intelligence processing methods and fed back to the operation of the devices, so as to achieve the function of intelligent management and control of devices.

[0187] Figure 8 A schematic diagram of the structure of an Internet of Things device control device provided by an embodiment of the present disclosure; Figure 8 As shown, the apparatus is applied to a first device, and the apparatus includes:

[0188] A first processing module, configured to determine a physical control parameter of the second device according to detection data from the second device; the detection data includes a physical parameter and power, and the physical control parameter is used to control a physical parameter 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 parameter, where the power feedback signal is used to indicate the physical control parameter.

[0190] In some embodiments, the first processing module is used 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 a user habit of at least one first time period based on the at least one sample pair; determine a physical control parameter corresponding to each first time period based on the user habit of the at least one first time period.

[0191] In some embodiments, the first communication module is used to determine, for each user habit in the first time period, a minimum execution time of each user habit in the first time period according to the detection data 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 according to the execution time and the power curve corresponding to the physical control parameter.

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

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

[0195] In some embodiments, the first processing module is used to determine the power curve and time of each first time period in the first application cycle based on the power curve in the first application cycle; determine the standard deviation value based on the power curve and time of each first time period in the first application cycle; if the standard deviation value exceeds the preset standard deviation, it is determined that the power curve meets the first condition.

[0196] In some embodiments, the first processing module is further used to determine management data of the second device according to the detection data sent by the second device, the management data including: a physical parameter and a power curve representing the physical parameter;

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

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

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

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

[0201] The update 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 curve and acquisition time of the physical parameters.

[0204] In some embodiments, the first processing module is used to determine a power curve corresponding to a change in a physical parameter based on the detection data; and determine management data of the second device based on the physical parameter and the power curve during the change.

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

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

[0207] Fig. 9 A schematic diagram of the structure of another IoT device control device provided in an embodiment of the present disclosure; Fig. 9 As shown, the device is applied to a second device, and the device includes:

[0208] A second communication module, configured to receive a power feedback signal from the first device;

[0209] The second processing module is used to determine a physical control parameter according to the power feedback signal, and control a physical parameter according to the physical control parameter.

[0210] In some embodiments, the second processing module is used to query management data according to 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 used to receive management data from the first device, and the management data is obtained by the first device based on analysis of detection data from the second device.

[0212] In some embodiments, the device further comprises: a collection module for collecting physical parameters using at least one physical parameter sensor; collecting power using a power collector;

[0213] The second communication module is used to determine the detection data according to the physical parameters, the collection time corresponding to the physical parameters, the power and the collection time corresponding to the power, and send the collected detection data to the first device.

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

[0215] The second communication module is further used to send the update data to the first device, where the update data is used for the first device to update the management data and / or the power feedback signal; 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 curve and acquisition time of the physical parameters.

[0218] In some embodiments, the second communication module is used 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 a decryption algorithm, and determine the physical control parameter according to the decrypted power feedback signal.

[0220] It is understandable that when the IoT device control device provided in the above embodiment implements the corresponding IoT device control method on the second device side, the above processing can be assigned to different program modules as needed to complete all or part of the processing described above. In addition, the device provided in the above embodiment and the embodiment of the corresponding method belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0221] An embodiment of the present disclosure provides a computer-readable storage medium storing executable instructions, wherein the executable instructions are stored. When the executable instructions are executed by a processor, the processor will be triggered to execute the routing method on the first device side provided by the embodiment of the present disclosure, or the routing method on the second device side.

[0222] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.

[0223] Fig.10 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure; Fig.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 so that the processor 1001 can execute: determining 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; based on the physical control parameters, sending a power feedback signal to the second device, and the power feedback signal is used to indicate the physical control parameters.

[0225] If the electronic device is a second device, the instruction is executed by the processor 1001 so that the processor 1001 can execute: receiving a power feedback signal from the first device; determining a physical control parameter according to the power feedback signal, and controlling the physical parameter according to the physical control parameter.

[0226] Of course, the electronic device provided in the above embodiments and the embodiments of the corresponding methods belong to the same concept, and the processor 1001 can also execute any of the above IoT device control methods. The specific implementation process is detailed in the method embodiments and will not be repeated here.

[0227] In actual application, 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 realize the connection and communication between these components. In addition to the data bus, the bus system 1004 also includes a power bus, a control bus, and a status signal bus. However, for the sake of clarity, Fig.10 In the figure, various buses are marked as bus system 1004. There may be at least one processor 1001 and at least one memory 1002. The network interface 1003 is used for wired or wireless communication between the electronic device 100 and other devices.

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

[0229] The method disclosed in the above embodiment of the present disclosure can be applied to the processor 1001, 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 hardware integrated logic circuit in the processor 1001 or the instruction in the form of software. The above processor 1001 can be a general processor, a digital signal processor (DSP, DiGital Signal Processor), or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. The processor 1001 can implement or execute the disclosed methods, steps and logic block diagrams in the embodiment of the present disclosure. The general processor can be a microprocessor or any conventional processor, etc. The steps of the method disclosed in the embodiment of the present disclosure can be directly embodied as a hardware decoding processor to execute, or the hardware and software modules in the decoding processor can be combined to execute. The software module can 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 above method in combination with its hardware.

[0230] In some embodiments, the electronic device 100 can be implemented by one or more application specific integrated circuits (ASIC), DSP, programmable logic device (PLD), complex programmable logic device (CPLD), field programmable gate array (FPGA), general processor, controller, microcontroller (MCU), microprocessor, or other electronic components to execute the aforementioned method.

[0231] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0232] In the above description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it can be 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 those commonly understood by those skilled in the art to which this disclosure belongs. The terms used in this disclosure are only for the purpose of describing the embodiments of this disclosure and are not intended to limit this disclosure.

[0234] It should be understood that in the various embodiments of the present disclosure, the size of the serial number of each implementation process does not mean 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 the present disclosure.

[0235] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of the present disclosure, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0236] The above is only a specific embodiment of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed in the present disclosure, which should be included in the protection scope of the present disclosure. Therefore, the protection scope of the present disclosure should be based on the protection scope of the claims.

Claims

1. A method for controlling an Internet of Things device, characterized in that: Applied to a first device, the method includes: Determine a physical control parameter of the second device according to detection data from the second device; the detection data includes a physical parameter and power, and the physical control parameter is used to control a physical parameter of the second device; A power feedback signal is sent to the second device according to the physical control parameter, where the power feedback signal is used to indicate the physical control parameter.

2. The method according to claim 1, characterized in that: The determining, according to the detection data sent by the second device, a physical control parameter of the second device includes: Determine a power time sample set according to the detection data, the power time sample set comprising at least one sample pair, each sample pair comprising a power curve and a time corresponding to the power curve; Determining a user habit of at least one first time period according to the at least one sample pair; According to the user habits of the at least one first time period, a physical control parameter corresponding to each first time period is determined.

3. The method according to claim 2, characterized in that Sending a power feedback signal to the second device according to the physical control parameter includes: For each user habit in the first time period, determining, according to the detection data, a minimum execution time of each user habit in the first time period as the execution time of the user habit; A power feedback signal is sent to the second device according to the execution time and the power curve corresponding to the physical control parameter.

4. The method according to claim 1, characterized in that The method further comprises: receiving a power curve from a second device, wherein the power curve is used to characterize a physical parameter; If it is determined that the power curve satisfies the first condition, stopping the control of the second device until the user habits of at least one second time period are re-determined; The physical control parameter corresponding to each second time period is re-determined according to the user habits of the at least one second time period.

5. The method according to claim 4, characterized in that Determining that the power curve satisfies a first condition includes: Determine, according to the power curve in the first application cycle, the power curve and time of each first time period in the first application cycle; determining a standard deviation value according to a power curve and time in each first time period in the first application cycle; If the standard deviation value exceeds a preset standard deviation, it is determined that the power curve meets a first condition.

6. The method according to claim 1, characterized in that The method further comprises: Determining management data of the second device according to the detection data sent by the second device, the management data comprising: a physical parameter and a power curve representing the physical parameter; The management data is sent to the second device.

7. The method according to claim 6, characterized in that The method further comprises: Receive detection data from the second device; the detection data also includes: collection time corresponding to the physical parameter and collection time corresponding to the power.

8. The method according to claim 1 or 7, characterized in that: The method further comprises: receiving update data from the second device, and updating the management data and / or the power feedback signal according to the update data; The update 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 curve and acquisition time of the physical parameters.

9. The method according to claim 6, characterized in that The determining, according to the detection data sent by the second device, the management data of the second device includes: Determine, based on the detection data, a power curve corresponding to a change in a physical parameter; Management data of the second device is determined according to the physical parameter and the power curve when the physical parameter changes.

10. The method according to claim 1, characterized in that The sending a 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.

11. A method for controlling an Internet of Things device, characterized in that: Applied to the second device, the method includes: receiving a power feedback signal from a first device; A physical control parameter is determined according to the power feedback signal, and a physical parameter is controlled according to the physical control parameter.

12. The method according to claim 11, characterized in that Determining a physical control parameter according to the power feedback signal includes: Management data is queried according to the power feedback signal to determine the physical parameters corresponding to the power feedback signal; the management data includes: the physical parameters and the power curve representing the physical parameters.

13. The method according to claim 12, characterized in that The method further comprises: Management data from the first device is received, where the management data is obtained by the first device based on analysis of detection data from the second device.

14. The method according to claim 13, characterized in that The method further comprises: collecting physical parameters using at least one physical parameter sensor; Collecting power using a power collector; Determine detection data according to the physical parameter, the collection time corresponding to the physical parameter, the power, and the collection time corresponding to the power, and send the collected detection data to the first device.

15. The method according to claim 11, characterized in that The method further comprises: Perform power and / or physical parameter identification based on the collected detection data to determine update data; Sending the update data to the first device, where the update data is used for the first device to update management data and / or a power feedback signal; the update 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 curve and acquisition time of the physical parameters.

16. The method according to claim 11, characterized in that Receiving a power feedback signal from a first device includes: receiving an encrypted power feedback signal from the first device; Accordingly, determining the physical control parameter according to the power feedback signal includes: The power feedback signal is decrypted based on a decryption algorithm, and a physical control parameter is determined according to the decrypted power feedback signal.

17. An Internet of Things device control device, characterized in that: The device is applied to a first device, and includes: A first processing module, configured to determine a physical control parameter of the second device according to detection data from the second device; the detection data includes a physical parameter and power, and the physical control parameter is used to control a physical parameter of the second device; The first communication module is used to send a power feedback signal to the second device according to the physical control parameter, where the power feedback signal is used to indicate the physical control parameter.

18. An Internet of Things device control device, characterized in that: The device is applied to a second device, and includes: A second communication module, configured to receive a power feedback signal from the first device; The second processing module is used to determine a physical control parameter according to the power feedback signal, and control a physical parameter according to the physical control parameter.

19. 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, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method described in any one of claims 1 to 10; or to enable the at least one processor to execute the method described in any one of claims 11 to 16.

20. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause a computer to execute the method according to any one of claims 1 to 10; or, the computer instructions are used to cause a computer to execute the method according to any one of claims 11 to 16.

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