Equipment control system and method based on wireless mesh network and electronic equipment

Abstract

The embodiment of the invention provides an equipment control system and method based on a wireless mesh network and electronic equipment.The equipment control system comprises a cloud server, an edge server and Internet of Things equipment which communicate based on the wireless mesh network, and the cloud server is used for obtaining a current task demand and sending the current task demand to the edge server; obtaining real-time state data of the Internet of Things equipment; generating a linkage control strategy according to the current task demand and the real-time state data; wherein the linkage control strategy comprises a target Internet of Things device needing to respond to the current task demand and a linkage control instruction corresponding to the target Internet of Things device; sending the linkage control instruction to an edge server; and the edge server is used for sending the linkage control instruction to the corresponding target Internet of Things equipment, so that the target Internet of Things equipment executes the linkage control instruction.

Description

Technical Field

[0001] Embodiments of the present invention relate to the technical field of the Internet of Things, and particularly to a device control system based on a wireless mesh network, a device control method based on a wireless mesh network, an electronic device, and a computer-readable storage medium. Background Art

[0002] With the rapid development of the Internet of Things (IoT), IoT devices (intelligent devices) have gradually entered people's daily lives and are widely used in fields such as industry, agriculture, and urban management. To achieve more efficient device management and data processing, IoT devices are usually interconnected through a network to achieve data interaction and remote control.

[0003] However, the control of IoT devices usually relies on a single central controller, resulting in low control efficiency of IoT devices, and it is difficult to achieve coordinated linkage between IoT devices. Summary of the Invention

[0004] In view of the above problems, a device control system, method, and electronic device based on a wireless mesh network are proposed to overcome the above problems or at least partially solve the above problems. The specific technical solutions are as follows:

[0005] Embodiments of the present invention disclose a device control system based on a wireless mesh network. The device control system includes a cloud server, an edge server, and IoT devices that communicate based on a wireless mesh network, where:

[0006] The cloud server is configured to obtain the current task requirements and the real-time status data of the IoT devices; generate a linkage control strategy according to the current task requirements and the real-time status data; where the linkage control strategy includes target IoT devices that need to respond to the current task requirements and the corresponding linkage control instructions for the target IoT devices; and send the linkage control instructions to the edge server;

[0007] The edge server is configured to send the linkage control instructions to the corresponding target IoT devices respectively, so that the target IoT devices execute the linkage control instructions.

[0008] In an embodiment of the present invention, the edge server is configured to obtain the real-time status data of the IoT devices; and determine whether to send the real-time status data sent by the IoT devices to the cloud server according to the current task requirements and the real-time status data.

[0009] In an embodiment of the present invention, the edge server is configured to determine whether to send the real-time status data sent by the Internet of Things device to the cloud server or process the real-time status data locally according to the current task requirements and the real-time status data.

[0010] In an embodiment of the present invention, the edge server is configured to screen out first real-time status data that needs to respond to the current task requirements and second real-time status data that does not need to respond to the current task requirements from the real-time status data according to the current task requirements; screen out third real-time status data that needs to be processed by the cloud server and fourth real-time status data that does not need to be processed by the cloud server from the second real-time status data according to a preset rule; send the first real-time status data and the third real-time status data to the cloud server, and process locally the second real-time status data and the fourth real-time status data except the third real-time status data.

[0011] In an embodiment of the present invention, the cloud server is configured to input the current task requirements and the real-time status data into a preset device linkage control model, so that the device linkage control model outputs a linkage control strategy; wherein, the linkage control strategy is obtained by training with historical control data of the Internet of Things device.

[0012] In an embodiment of the present invention, the cloud server is configured to obtain historical control data of the Internet of Things device; preprocess the historical control data to obtain key features; train a device linkage control model to be trained with the key features, and obtain a trained device linkage control model when the device linkage control model meets a preset convergence condition; wherein, the preprocessing at least includes cleaning, denoising, and normalization processing.

[0013] In an embodiment of the present invention, the cloud server is configured to obtain the execution result of the target Internet of Things device sending a response to the linkage control instruction through the edge server; adjust the linkage control strategy according to the execution result.

[0014] In an embodiment of the present invention, the cloud server and the edge server are configured to monitor whether the Internet of Things device has an abnormality during the execution of the linkage control instruction by the target Internet of Things device; adjust the linkage control strategy according to the abnormality.

[0015] In an embodiment of the present invention, the edge server is configured to monitor whether the Internet of Things (IoT) device has an abnormality during the execution of the linkage control instruction by the target IoT device; determine the urgency and the scope of influence of the abnormality, and determine, according to the urgency and the scope of influence of the abnormality, whether the cloud server adjusts the linkage control strategy according to the abnormality or the local adjusts the linkage control strategy according to the abnormality.

[0016] An embodiment of the present invention also discloses a device control method based on a wireless mesh network, including a cloud server, an edge server, and IoT devices that communicate based on the wireless mesh network. The method includes:

[0017] Obtain the current task requirements and the real-time status data of the IoT device;

[0018] Generate a linkage control strategy according to the current task requirements and the real-time status data; wherein, the linkage control strategy includes target IoT devices that need to respond to the current task requirements and the corresponding linkage control instructions for the target IoT devices;

[0019] Send the linkage control instructions to the corresponding target IoT devices through the edge server respectively, so that the target IoT devices execute the linkage control instructions.

[0020] An embodiment of the present invention also discloses an electronic device, including a processor, a communication interface, a memory, and a communication bus. Wherein, the processor, the communication interface, and the memory complete communication with each other through the communication bus;

[0021] The memory is used to store a computer program;

[0022] When the processor executes the program stored on the memory, it implements the method as described in the embodiment of the present invention.

[0023] An embodiment of the present invention also discloses a computer program product, which is stored in a storage medium and is executed by at least one processor to implement the method as described in the embodiment of the present invention.

[0024] An embodiment of the present invention also discloses a computer-readable storage medium, on which instructions are stored. When executed by one or more processors, the instructions cause the processors to execute the method as described in the embodiment of the present invention.

[0025] The embodiments of the present invention have the following advantages:

[0026] In an embodiment of the present invention, the device control system may include a cloud server, an edge server, and Internet of Things (IoT) devices that communicate based on a wireless mesh network. When it is necessary to perform linkage control on the IoT devices, the cloud server obtains the current task requirements and the real-time status data of the IoT devices, and generates a linkage control strategy according to the current task requirements and the real-time status data. Among them, the linkage control strategy may include the target IoT devices that need to respond to the current task requirements and the linkage control instructions corresponding to the target IoT devices. Then, the linkage control instructions are sent to the corresponding target IoT devices through the edge server respectively, so that the target IoT devices execute the linkage control instructions. The embodiment of the present invention can control IoT devices through the high-performance computing cloud server and edge server, improving the control efficiency of IoT devices, and can generate a linkage control strategy for IoT devices according to the current task requirements and the real-time status data of IoT devices, realizing the collaborative linkage control between IoT devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 FIG. is a structural block diagram of a device control system based on a wireless mesh network provided in an embodiment of the present invention;

[0028] Figure 2 FIG. is a schematic diagram of cloud-edge-end collaborative control provided in an embodiment of the present invention;

[0029] Figure 3 FIG. is a flowchart of the linkage control of Mesh network devices provided in an embodiment of the present invention;

[0030] Figure 4 FIG. is a flowchart of the steps of a device control method based on a wireless mesh network provided in an embodiment of the present invention;

[0031] Figure 5 FIG. is a schematic diagram of the hardware structure of an electronic device for implementing various embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0033] In specific implementation, the Internet of Things may include a Mesh network (wireless mesh network). The Mesh network is a "multi-hop" network. In the process of evolving to the next-generation network, wireless is an indispensable technology. The Mesh network can communicate in cooperation with other networks and is a dynamic and continuously expandable network architecture. Any two Internet of Things devices (devices) can maintain wireless interconnection.

[0034] Mesh networks have the characteristics of decentralization and self-organizing networks between devices. The topological structure of Mesh networks enables IoT devices to achieve low-latency and highly reliable communication based on multi-hop transmission. However, at present, Mesh networks often rely on the communication and computing capabilities of the devices themselves. They rely solely on edge computing for device management and linkage control, which is easily affected by device performance limitations, network congestion and data transmission delays. Therefore, how to use the collaborative mechanism of cloud computing, edge computing and device end to achieve efficient device linkage control in Mesh networks has become an important topic in the current research of IoT technology. Among them, cloud computing is achieved through the cloud (cloud server), edge computing is achieved through edge nodes (edge ​​servers), and the device end refers to IoT devices.

[0035] The purpose of the embodiment of the present invention is to propose a Mesh device (IoT device) linkage control method combined with a cloud-edge-end collaboration mechanism, which improves the real-time and coordination of IoT device control and reduces network congestion and control delay through multi-level collaboration among the cloud, edge nodes, and device ends (referred to as cloud-edge-ends), aiming to at least solve the following problems existing in the current technical solutions:

[0036] (1) Currently, the control of IoT devices in Mesh networks usually relies on a single central controller. When the number of IoT devices is large, the central controller will experience delays or freezes due to processing power limitations, and cannot meet the needs of efficient management of large-scale IoT devices.

[0037] (2) In the multi-device linkage scenario, the state synchronization and coordination between IoT devices are highly complex. The traditional linkage control method lacks an effective mechanism to adjust the working status of each IoT device in real time, making it difficult to achieve accurate coordination of IoT devices.

[0038] (3) Existing edge computing-based control methods are limited by the computing power of the device itself and operating conditions such as network conditions, and are prone to problems such as response lag and poor data transmission between devices.

[0039] In view of the above problems, the embodiments of the present invention propose the following solutions:

[0040] (1) Cloud-edge-device collaboration mechanism: This paper proposes a cloud-edge-device collaborative control mechanism that divides tasks into layers according to computational complexity and real-time requirements: the cloud is responsible for global control and optimization, the edge node is responsible for local coordination and rapid response, and the device end is only responsible for executing specific tasks. Through layered collaboration, the system can intelligently adjust the control logic according to the functions and states of different IoT devices to ensure efficient operation of the system.

[0041] (2) Mesh network device linkage control: The present invention further introduces a device linkage control mechanism. When multiple Internet of Things devices need to work together, the system can calculate the optimal device linkage plan (linkage control strategy) in the cloud according to the current task requirements, and quickly send the corresponding linkage control instructions in the linkage control strategy to the local area through the edge node to ensure the efficiency of device linkage control.

[0042] (3) Data synchronization and status prediction: Through the high-performance computing of the cloud, the system can perform real-time analysis and prediction on the operation data (real-time status data) of Internet of Things devices, so as to process possible anomalies or conflicts in advance. In addition, the cloud can also combine the historical control data of Internet of Things devices to predict the operation status of Internet of Things devices and dynamically adjust the linkage control strategy to ensure the smooth progress of device linkage.

[0043] Refer to Figure 1 , which shows a structural block diagram of a device control system based on a wireless mesh network provided in an embodiment of the present invention. The device control system includes a cloud server 101, an edge server 102, and Internet of Things devices 103 that communicate based on a wireless mesh network, where:

[0044] The cloud server 101 is used to obtain the current task requirements and the real-time status data of the Internet of Things devices; generate a linkage control strategy according to the current task requirements and the real-time status data; where the linkage control strategy includes target Internet of Things devices that need to respond to the current task requirements and the corresponding linkage control instructions for the target Internet of Things devices; and send the linkage control instructions to the edge server;

[0045] The edge server 102 is used to send the linkage control instructions to the corresponding target Internet of Things devices respectively, so that the target Internet of Things devices execute the linkage control instructions.

[0046] The device control system of the wireless mesh network (Mesh network) in the embodiment of the present invention is a three-layer architecture jointly constructed by the cloud (cloud server), edge nodes (edge server), and device side (Internet of Things devices). Among them, the cloud server and the edge server are high-performance devices, and the performance of the cloud server is higher than that of the edge server. Specifically:

[0047] Cloud (cloud server): The cloud server has powerful computing power and storage space, and is responsible for the global control and optimization of the devices in the whole network. The cloud anticipates the linkage requirements between devices through big data analysis and AI (Artificial Intelligence) algorithms, formulates the optimal linkage control strategy, and sends it to each Internet of Things device through the edge node. The cloud server and the edge server are high-performance devices

[0048] Edge Node (Edge Server): Edge servers are usually set up in the local network close to the devices and act as local controllers. Edge servers receive instructions sent by the cloud server and quickly process device linkage requests locally. For tasks with high latency requirements, the edge server can directly coordinate the linkage between local devices according to the current network conditions, reducing data transmission latency.

[0049] Device Side (IoT Devices): IoT devices are only responsible for executing specific control tasks (the control tasks can be executed according to the linkage control instructions sent by the cloud server or the edge server), and feedback the status to the edge server and the cloud server. IoT devices themselves do not need to have complex computing capabilities and mainly rely on the edge server and the cloud server for control and optimization. Exemplarily, IoT devices can include lighting devices, dehumidifiers, switches, sockets, temperature and humidity sensors, smoke alarms, smart door locks, and security cameras, etc. IoT devices can communicate with each other through communication protocols.

[0050] The current task requirements can be generated when the user triggers or detects a change in the operating state of the IoT device. For example, in a smart home system, when the user sets the "leave home mode" through the mobile APP, it can trigger the generation of corresponding current task requirements in the cloud server or the edge server.

[0051] Each IoT device can upload real-time status data to the edge node through a Mesh network, and the edge server can then send the real-time status data to the cloud server for processing or local processing. Exemplarily, the real-time status data can include, but is not limited to, the following categories: Basic attribute data: such as device model, manufacturer, serial number, etc. Working status data: such as whether the device is online, operating status (such as on / off, working mode, etc.), working duration, etc. Environment perception data: such as temperature, humidity, light intensity, air quality, etc. (for devices with environment perception functions). Energy consumption data: such as real-time energy consumption of the device, historical energy consumption statistics, etc. Fault alarm data: such as device fault alarm information, error codes, etc. User interaction data: such as user operation records, preference settings, etc.

[0052] In an embodiment of the present invention, the cloud server can obtain the current task requirements and the real-time status data uploaded by the Internet of Things devices through the edge server. Then, it can generate a linkage control strategy based on the current task requirements and the real-time status data and send it to the edge server. The edge server can then send the linkage control instructions in the linkage control strategy to the corresponding target Internet of Things devices respectively, so that the target Internet of Things devices execute the linkage control instructions to achieve the linkage control of the devices. Among them, the linkage control strategy can at least include the target Internet of Things devices that need to respond to the current task requirements and the corresponding linkage control instructions for the target Internet of Things devices.

[0053] Exemplarily, the linkage control strategy can include but is not limited to the following: Timing linkage: For example, automatically turn on / off lighting devices according to time settings. Conditional linkage: For example, when the indoor humidity exceeds a certain threshold, automatically turn on the dehumidifier. Scene linkage: For example, when the user sets the "go home mode", automatically turn on Internet of Things devices such as the access control, lighting devices, and air conditioning devices. For example, in a smart home system, when the user sets the "leave home mode" through the mobile phone APP, the cloud server generates the corresponding current task requirements, and then can combine the current status data of the Internet of Things devices (such as the door and window status, indoor lighting, etc.) to generate an optimal linkage control strategy. For example, the linkage control strategy can be to turn off all non-essential electrical devices and turn on the security system, etc.

[0054] Among them, when the cloud server sends the linkage control instructions to the corresponding target Internet of Things devices through the edge server, the edge server can adjust the sending order and execution priority of the linkage control instructions in real time according to the local network conditions to ensure smooth coordination of the linkage control between devices. Specifically, the edge server can adjust the sending order and execution priority of the linkage control instructions according to the following principles:

[0055] Network latency and bandwidth: When the network latency is high or the bandwidth is insufficient, give priority to sending critical and urgent linkage control instructions, such as device fault alarm handling instructions; for non-urgent instructions, they can be sent later or merged to reduce the network burden.

[0056] Dependency relationship between devices: For devices with a dependency relationship (such as turning on the air conditioner first and then the fresh air system), the edge server should ensure that the linkage control instructions are sent in the correct order.

[0057] Device status and priority: Adjust the execution order of the linkage control instructions according to the current operating status (device status) and priority of the Internet of Things devices (such as whether the device is idle, whether it is performing other tasks, etc.).

[0058] In the above device control system based on a wireless mesh network, it may include a cloud server, an edge server, and Internet of Things (IoT) devices that communicate based on the wireless mesh network. When linkage control of the IoT devices is required, the cloud server obtains the current task requirements and the real-time status data of the IoT devices, and generates a linkage control strategy based on the current task requirements and the real-time status data. Among them, the linkage control strategy may include the target IoT devices that need to respond to the current task requirements and the corresponding linkage control instructions for the target IoT devices. Then, the linkage control instructions are sent to the corresponding target IoT devices through the edge server respectively, so that the target IoT devices execute the linkage control instructions. In the embodiment of the present invention, the cloud server and the edge server with high-performance computing can be used to control the IoT devices, improving the control efficiency of the IoT devices, and a linkage control strategy for the IoT devices can be generated according to the current task requirements and the real-time status data of the IoT devices, realizing the collaborative linkage control between the IoT devices.

[0059] In an embodiment of the present invention, the edge server is configured to obtain the real-time status data of the IoT devices; determine whether to send the real-time status data sent by the IoT devices to the cloud server according to the current task requirements and the real-time status data. Specifically, the edge server is configured to determine, according to the current task requirements and the real-time status data, to send the real-time status data sent by the IoT devices to the cloud server, or process the real-time status data locally.

[0060] In the embodiment of the present invention, the edge server can obtain the real-time status data uploaded by the IoT devices through the Mesh network, and then determine whether to upload the real-time status data to the cloud server according to the current task requirements. Specifically, the edge server can decide whether to directly process the real-time status data or report the real-time status data to the cloud server for processing, so as to avoid timely processing of relevant tasks of the IoT devices, thereby ensuring better device services for the users of the IoT devices.

[0061] In an embodiment of the present invention, the edge server is configured to screen out the first real-time status data that needs to respond to the current task requirements and the second real-time status data that does not need to respond to the current task requirements from the real-time status data according to the current task requirements; screen out the third real-time status data that needs to be processed by the cloud server and the fourth real-time status data that does not need to be processed by the cloud server from the second real-time status data according to a preset rule; send the first real-time status data and the third real-time status data to the cloud server, and process the second real-time status data and the fourth real-time status data except the third real-time status data locally.

[0062] In a specific implementation, the real-time status data may include data that needs to respond to the current task requirements and data that does not need to respond to the current task requirements. At this time, the edge server can perform a first screening based on this. Then, a secondary screening can be performed on the second real-time status data (i.e., the data that does not need to respond to the current task requirements) after the first screening according to a preset rule to screen out the real-time status data (the third real-time status data) that needs to be processed by the cloud server. Then, the edge server can send the first real-time status data and the third real-time status data to the cloud server for processing, and process other real-time status data (i.e., the remaining second real-time status data and the fourth real-time status data except the third real-time status data) locally.

[0063] Exemplarily, the edge server can determine whether to directly process the real-time status data (status data) or report it to the cloud server according to the following preset rules:

[0064] Urgency and importance: For urgent and important status data (such as device fault alarms), the edge server should directly process it, such as starting a standby device or executing an emergency plan, and at the same time report it to the cloud server for global coordination.

[0065] Data complexity and processing capacity: For simple status data that the edge server can process (such as changes in the on / off state of a device), the edge server can directly process it and adjust the linkage strategy; for complex or status data that requires global analysis (such as energy consumption trend analysis), it is reported to the cloud server for processing.

[0066] Network condition and latency requirements: In the case of good network conditions and low latency requirements, the edge server can report more status data to the cloud server for comprehensive analysis; when the network condition is poor or the latency requirement is high, the edge server should give priority to processing critical status data.

[0067] In a specific example of the present invention, assume that the edge server obtains the real-time status data as follows: Status data 1: The on / off state of the lighting device is "on"; Status data 2: The operating mode of the air conditioner is "cooling", and the temperature is set to 25°C; Status data 3: The indoor temperature of the environmental sensor is 28°C, and the humidity is 60%; Status data 4: The device energy consumption of the Internet of Things device is 1000W. The current task requirement is to turn off all non-essential Internet of Things devices (such as lighting devices, air conditioning devices, etc.).

[0068] Perform the first screening on the real-time status data according to the current task requirements, and screen out the first real-time status data and the second real-time status data: The first real-time status data (which needs to respond to the current task requirements) may include: status data 1, status data 2, status data 3, and the second real-time status data (which does not need to respond to the current task requirements) may include: status data 4.

[0069] Perform further screening on the second real-time status data according to the preset rules, and screen out the third real-time status data and the fourth real-time status data. Among them, according to the "status data that is complex or requires global analysis (such as energy consumption trend analysis)" in the preset rules, it can be determined that status data 4 is the status data that requires global analysis. Therefore, it can be determined that it needs to be processed by the cloud server, and thus needs to be uploaded to the cloud server. Therefore, the edge server can upload status data 1, status data 2, status data 3, and status data 4 to the cloud server for processing.

[0070] In an embodiment of the present invention, the cloud server is configured to input the current task requirements and the real-time status data into a preset device linkage control model, so that the device linkage control model outputs a linkage control strategy; wherein, the linkage control strategy is trained by using the historical control data of the Internet of Things devices.

[0071] Among them, the historical control data of the Internet of Things devices may include the control data of the historical users for the Internet of Things devices. For example, the user likes to adjust the temperature of the air-conditioning device to 22 degrees, and still keeps the air-conditioning device on when in the "away mode", etc.

[0072] In an embodiment of the present invention, the cloud server can generate an optimal linkage control strategy by combining the historical control data of the Internet of Things devices and the current task requirements. Specifically, the device linkage control model can be trained according to the historical control data, and the device linkage control model can output a linkage control strategy. The cloud server inputs the current task requirements and the real-time status data into the device linkage control model, so that the device linkage control model performs real-time analysis and quickly and accurately generates an optimal linkage control strategy.

[0073] In an embodiment of the present invention, the cloud server is configured to obtain the historical control data of the Internet of Things devices; perform preprocessing on the historical control data to obtain key features; use the key features to train the device linkage control model to be trained, and obtain the trained device linkage control model when the device linkage control model meets the preset convergence conditions; wherein, the preprocessing at least includes cleaning, denoising, and normalization processing.

[0074] In an embodiment of the present invention, the cloud server can obtain the historical control data of the Internet of Things devices, and then perform cleaning, denoising, and normalization processing on the historical control data to extract key features. Then, machine learning or deep learning algorithms (such as decision trees, neural networks, etc.) are used to train the historical control data to establish a device linkage control model. When the device linkage control model meets the preset convergence conditions, for example, the loss value of the device linkage control model reaches the preset loss value, or the number of rounds of iterative training of the model reaches the preset number of rounds, it can be considered that the device linkage control model meets the preset convergence conditions, and a trained device linkage control model is obtained. Subsequently, the cloud server can input the current task requirements and real-time status data into the device linkage control model, enabling the device linkage control model to perform real-time analysis and quickly and accurately generate an optimal linkage control strategy.

[0075] For example, in a smart home system, when the user sets the "away mode" through the mobile phone APP, the cloud server can analyze the historical data (such as the routine operations when the user leaves home) to generate a linkage control model, and then input the current status data (such as the door and window status, indoor lighting, etc.) and the current task requirements into the linkage control model, thereby outputting an optimal linkage control strategy. For example, turn off all non-essential electrical devices and turn on the security system, etc.

[0076] In an embodiment of the present invention, the cloud server is used to obtain the execution result of the linkage control instruction sent by the target Internet of Things device through the edge server; and adjust the linkage control strategy according to the execution result.

[0077] In an embodiment of the present invention, the cloud server obtains the execution result of the Internet of Things device executing the linkage control instruction through the edge server, such as whether the Internet of Things device has completed the execution and the time required for the execution, etc. According to the execution result, the cloud server can dynamically adjust the linkage control strategy, and further adjust different task allocation strategies. For example, if the execution result is that lighting device A fails to be successfully turned on, the cloud server adjusts the linkage control strategy to turn on lighting device B, which is the closest to lighting device A, to take over the lighting work of lighting device A and ensure the normal device usage experience of the user.

[0078] In an embodiment of the present invention, the cloud server and the edge server are configured to monitor whether the IoT device has an abnormality during the execution of the linkage control instruction by the target IoT device; and adjust the linkage control strategy according to the abnormality. Specifically, the edge server is configured to monitor whether the IoT device has an abnormality during the execution of the linkage control instruction by the target IoT device; determine the urgency and the scope of influence of the abnormality, and determine whether the cloud server adjusts the linkage control strategy according to the abnormality or the local adjusts the linkage control strategy according to the abnormality based on the urgency and the scope of influence of the abnormality.

[0079] In an embodiment of the present invention, during the execution of the linkage control instruction by the IoT device, the cloud server and the edge server continuously monitor the operating state of the IoT device. If it is found that the operating state of the IoT device is abnormal, the cloud server can timely adjust the linkage control strategy, so as to re-allocate the linkage control instruction. Among them, when the edge server discovers an abnormality in the IoT device, the specific processing method for the abnormality should depend on the urgency and the scope of influence of the abnormality. For example:

[0080] Urgent and global abnormality: For example, abnormalities such as large-scale device failures or network paralysis should be globally coordinated and processed by the cloud server.

[0081] Local and non-urgent abnormality: Such as a single device failure or a slight performance degradation can be initially processed by the edge server and reported to the cloud server for recording and analysis.

[0082] In practical applications, a dynamic cooperation mechanism can be established between the cloud server and the edge server to flexibly adjust the processing method according to the urgency and the scope of influence of the abnormality, so as to better solve the abnormality and ensure the user experience.

[0083] To enable those skilled in the art to better understand the embodiments of the present invention, the following uses specific examples for illustration. Refer to Figure 2 , which is a schematic diagram of cloud-edge-end collaborative control provided in the embodiment of the present invention, showing the collaborative tasks between different levels in the three-layer architecture. The specific control process may include:

[0084] Cloud control: 1. The cloud receives global data (related data of edge nodes and IoT devices) and status information (status data); 2. The cloud performs global control and optimization; 3. The cloud generates a control strategy (linkage control strategy) and sends it to the edge node;

[0085] Edge Node Adjustment: 1. The edge node receives the control policy issued by the cloud; 2. The edge node responds quickly according to local data and status (status data saved locally and the status of the edge node and IoT devices, such as network status, etc.); 3. The edge node generates specific task instructions (linkage control instructions) and issues them to the device side;

[0086] Device-side Execution: 1. The device side receives the task instructions issued by the edge node; 2. The device side executes the specific task; 3. The device side feeds back the execution result to the edge node;

[0087] Feedback and Adjustment: 1. The edge node receives the execution result of the device side; 2. The edge node feeds back the execution result and local data to the cloud; 3. The cloud performs global optimization and adjusts the control policy according to the feedback.

[0088] Refer to Figure 3 , which is a flowchart of the linkage control of Mesh network devices provided in the embodiment of the present invention. The specific process includes:

[0089] Task Requirement Identification: The system identifies the task requirements that require multiple devices to work together;

[0090] Cloud Computing: The cloud calculates the optimal device linkage scheme (control policy) according to the task requirements;

[0091] Instruction Issuance: The cloud issues the calculated linkage scheme to each device through the edge node;

[0092] Device Linkage Execution: Each device performs the linkage task according to the issued instructions;

[0093] Monitoring and Feedback: The system monitors the device execution situation and collects feedback data (including execution results);

[0094] Dynamic Adjustment: The system intelligently adapts to and dynamically adjusts the linkage scheme according to the feedback data, thereby continuously optimizing the linkage scheme and providing a better device usage experience for users.

[0095] Applying the embodiment of the present invention, the collaborative control of the cloud server, edge server and IoT devices can be realized in the Mesh network, and efficient device linkage control can be realized in the Mesh network, improving the user experience of using IoT devices.

[0096] Refer to Figure 4 , which shows a step flowchart of a device control method based on a wireless mesh network provided in the embodiment of the present invention. It includes a cloud server, an edge server and IoT devices that communicate based on a wireless mesh network. The method may specifically include the following steps:

[0097] Step 401: Obtain the current task requirements and the real-time status data of the Internet of Things device;

[0098] Step 402: Generate a linkage control strategy based on the current task requirements and the real-time status data; wherein, the linkage control strategy includes the target Internet of Things devices that need to respond to the current task requirements and the corresponding linkage control instructions for the target Internet of Things devices;

[0099] Step 403: Send the linkage control instructions to the corresponding target Internet of Things devices through the edge server respectively, so that the target Internet of Things devices execute the linkage control instructions.

[0100] In an embodiment of the present invention, the edge server is used to obtain the real-time status data of the Internet of Things device; determine whether to send the real-time status data sent by the Internet of Things device to the cloud server according to the current task requirements and the real-time status data.

[0101] In an embodiment of the present invention, the edge server is used to determine to send the real-time status data sent by the Internet of Things device to the cloud server according to the current task requirements and the real-time status data, or process the real-time status data locally.

[0102] In an embodiment of the present invention, the edge server is used to screen out the first real-time status data that needs to respond to the current task requirements and the second real-time status data that does not need to respond to the current task requirements from the real-time status data according to the current task requirements; screen out the third real-time status data that needs to be processed by the cloud server and the fourth real-time status data that does not need to be processed by the cloud server from the second real-time status data according to a preset rule; send the first real-time status data and the third real-time status data to the cloud server, and process the second real-time status data and the fourth real-time status data except the third real-time status data locally.

[0103] In an embodiment of the present invention, Step 402: Generate a linkage control strategy based on the current task requirements and the real-time status data, including:

[0104] Input the current task requirements and the real-time status data into a preset device linkage control model, so that the device linkage control model outputs a linkage control strategy; wherein, the linkage control strategy is trained by using the historical control data of the Internet of Things device.

[0105] In an embodiment of the present invention, the method further includes:

[0106] Obtain the historical control data of the Internet of Things device; preprocess the historical control data to obtain key features; use the key features to train the device linkage control model to be trained, and obtain the trained device linkage control model when the device linkage control model meets the preset convergence condition; wherein, the preprocessing at least includes cleaning, denoising, and normalization processing.

[0107] In an embodiment of the present invention, the method further includes:

[0108] Obtain the execution result of the target Internet of Things device sending the linkage control instruction through the edge server; adjust the linkage control strategy according to the execution result.

[0109] In an embodiment of the present invention, the cloud server and the edge server are used to monitor whether the Internet of Things device has an abnormality during the process of the target Internet of Things device executing the linkage control instruction; adjust the linkage control strategy according to the abnormality.

[0110] In an embodiment of the present invention, the edge server is used to monitor whether the Internet of Things device has an abnormality during the process of the target Internet of Things device executing the linkage control instruction; determine the urgency and scope of influence of the abnormality, and determine whether the cloud server adjusts the linkage control strategy according to the abnormality or the local adjusts the linkage control strategy according to the abnormality according to the urgency and scope of influence of the abnormality.

[0111] In an embodiment of the present invention, the device control system may include a cloud server, an edge server, and an Internet of Things device that communicate based on a wireless mesh network. When it is necessary to perform linkage control on the Internet of Things device, the cloud server obtains the current task requirements and the real-time status data of the Internet of Things device, so as to generate a linkage control strategy according to the current task requirements and the real-time status data. Among them, the linkage control strategy may include the target Internet of Things device that needs to respond to the current task requirements and the linkage control instruction corresponding to the target Internet of Things device. Then, the linkage control instruction is sent to the corresponding target Internet of Things device through the edge server respectively, so that the target Internet of Things device executes the linkage control instruction. The embodiment of the present invention can control the Internet of Things device through the cloud server and the edge server with high-performance computing, improve the control efficiency of the Internet of Things device, and can generate the linkage control strategy of the Internet of Things device according to the current task requirements and the real-time status data of the Internet of Things device, realizing the collaborative linkage control between the Internet of Things devices.

[0112] It should be noted that, for the method embodiments, for the sake of simplicity of description, they are all expressed as a series of action combinations. However, those skilled in the art should know that the embodiments of the present invention are not limited by the described action sequences, because according to the embodiments of the present invention, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all preferred embodiments, and the actions involved are not necessarily essential for the embodiments of the present invention.

[0113] For the method embodiments, since they are basically similar to the system embodiments, the description is relatively simple. For the related parts, refer to the partial description of the system embodiments.

[0114] In addition, the embodiments of the present invention further provide an electronic device, including: a processor, a memory, and a computer program stored on the memory and executable on the processor. When the computer program is executed by the processor, it implements each process of the above-mentioned method embodiment for controlling a device based on a wireless mesh network, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0115] The embodiments of the present invention further provide a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements each process of the above-mentioned method embodiment for controlling a device based on a wireless mesh network, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here. Among them, the computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disc, etc.

[0116] The embodiments of the present invention further provide a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement each process of the method embodiment for controlling a device based on a wireless mesh network as described above, and can achieve the same technical effects. To avoid repetition, it will not be elaborated here.

[0117] Figure 5 Schematic diagram of the hardware structure of an electronic device for implementing each embodiment of the present invention.

[0118] The electronic device 500 includes, but is not limited to: a radio frequency unit 501, a network module 502, an audio output unit 503, an input unit 504, a sensor 505, a display unit 506, a user input unit 507, an interface unit 508, a memory 509, a processor 510, and a power supply 511, etc. Those skilled in the art can understand, Figure 5The structure of the electronic device shown does not constitute a limitation on the electronic device. The electronic device may include more or fewer components than shown, or combine certain components, or have a different component arrangement. In an embodiment of the present invention, the electronic device includes, but is not limited to, a mobile phone, a tablet computer, a laptop computer, a handheld computer, a vehicle-mounted terminal, a wearable device, and a pedometer, etc.

[0119] It should be understood that in an embodiment of the present invention, the radio frequency unit 501 can be used for receiving and sending information or signals during a call. Specifically, after receiving the downlink data from the base station, it is given to the processor 510 for processing; in addition, the uplink data is sent to the base station. Generally, the radio frequency unit 501 includes, but is not limited to, an antenna, at least one amplifier, a transceiver, a coupler, a low-noise amplifier, a duplexer, etc. In addition, the radio frequency unit 501 can also communicate with the network and other devices through a wireless communication system.

[0120] The electronic device provides the user with wireless broadband Internet access through the network module 502, such as helping the user to send and receive emails, browse the web, and access streaming media, etc.

[0121] The audio output unit 503 can convert the audio data received by the radio frequency unit 501 or the network module 502 or stored in the memory 509 into an audio signal and output it as sound. Moreover, the audio output unit 503 can also provide an audio output related to the specific functions executed by the electronic device 500 (for example, a call signal reception sound, a message reception sound, etc.). The audio output unit 503 includes a speaker, a buzzer, and a receiver, etc.

[0122] The input unit 504 is used for receiving audio or video signals. The input unit 504 may include a graphics processing unit (GPU) 5041 and a microphone 5042. The graphics processing unit 5041 processes the image data of a still picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The processed image frame can be displayed on the display unit 506. The processed image frame can be stored in the memory 509 (or other storage media) or sent via the radio frequency unit 501 or the network module 502. The microphone 5042 can receive sound and can process such sound into audio data. The processed audio data can be converted into a format that can be sent to the mobile communication base station via the radio frequency unit 501 in the case of a phone call mode and output.

[0123] The electronic device 500 further includes at least one sensor 505, such as a light sensor, a motion sensor, and other sensors. Specifically, the light sensor includes an ambient light sensor and a proximity sensor. Among them, the ambient light sensor can adjust the brightness of the display panel 5061 according to the brightness of the ambient light, and the proximity sensor can turn off the display panel 5061 and / or the backlight when the electronic device 500 is moved to the ear. As a kind of motion sensor, the accelerometer sensor can detect the magnitude of acceleration in all directions (generally three axes), and can detect the magnitude and direction of gravity when stationary, and can be used to identify the posture of the electronic device (such as horizontal and vertical screen switching, related games, magnetometer posture calibration), vibration recognition related functions (such as pedometer, tapping), etc.; the sensor 505 can also include a fingerprint sensor, a pressure sensor, an iris sensor, a molecular sensor, a gyroscope, a barometer, a hygrometer, a thermometer, an infrared sensor, etc., which will not be elaborated here.

[0124] The display unit 506 is used to display information input by the user or information provided to the user. The display unit 506 may include a display panel 5061, and the display panel 5061 can be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), etc.

[0125] The user input unit 507 can be used to receive input digital or character information, and generate key signal inputs related to the user settings and function control of the electronic device. Specifically, the user input unit 507 includes a touch panel 5071 and other input devices 5072. The touch panel 5071, also known as a touch screen, can collect touch operations of the user on or near it (such as operations of the user using a finger, a stylus, or any suitable object or accessory on or near the touch panel 5071). The touch panel 5071 can include two parts: a touch detection device and a touch controller. Among them, the touch detection device detects the touch position of the user and detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into contact coordinates, and then sends it to the processor 510, and receives and executes the commands sent by the processor 510. In addition, the touch panel 5071 can be implemented in multiple types such as resistive, capacitive, infrared, and surface acoustic wave. In addition to the touch panel 5071, the user input unit 507 can also include other input devices 5072. Specifically, the other input devices 5072 can include but are not limited to a physical keyboard, function keys (such as volume control keys, power on / off keys, etc.), a trackball, a mouse, a joystick, which will not be elaborated here.

[0126] Further, the touch panel 5071 can cover the display panel 5061. After the touch panel 5071 detects a touch operation on or near it, it transmits the operation to the processor 510 to determine the type of touch event. Subsequently, the processor 510 provides a corresponding visual output on the display panel 5061 according to the type of touch event. Although in Figure 5 the touch panel 5071 and the display panel 5061 are implemented as two independent components to achieve the input and output functions of the electronic device, in some embodiments, the touch panel 5071 and the display panel 5061 can be integrated to achieve the input and output functions of the electronic device, and the specific implementation here is not limited.

[0127] The interface unit 508 is an interface for connecting an external device to the electronic device 500. For example, the external device may include a wired or wireless headset port, an external power supply (or battery charger) port, a wired or wireless data port, a memory card port, a port for connecting a device with an identification module, an audio input / output (I / O) port, a video I / O port, a headset port, and so on. The interface unit 508 can be used to receive inputs from an external device (such as data information, power, etc.) and transmit the received inputs to one or more components within the electronic device 500 or can be used to transmit data between the electronic device 500 and the external device.

[0128] The memory 509 can be used to store software programs and various data. The memory 509 mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, application programs required for at least one function (such as a sound playback function, an image playback function, etc.); the data storage area can store data created according to the use of the mobile phone (such as audio data, a phone book, etc.). In addition, the memory 509 can include a high-speed random access memory and can also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices.

[0129] The processor 510 is the control center of the electronic device. It uses various interfaces and circuits to connect all parts of the entire electronic device. By running or executing software programs and / or modules stored in the memory 509, and by calling data stored in the memory 509, it executes various functions of the electronic device and processes data, thereby monitoring the electronic device as a whole. The processor 510 can include one or more processing units; preferably, the processor 510 can integrate an application processor and a modem processor. Among them, the application processor mainly processes the operating system, user interface, and application programs, etc., and the modem processor mainly processes wireless communication. It can be understood that the above-mentioned modem processor may not be integrated into the processor 510 either.

[0130] The electronic device 500 may further include a power source 511 (such as a battery) for powering each component. Preferably, the power source 511 may be logically connected to the processor 510 through a power management system, so as to manage functions such as charging, discharging, and power consumption management through the power management system.

[0131] In addition, the electronic device 500 includes some functional modules not shown, which will not be elaborated here.

[0132] It should be noted that in this article, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including one..." does not exclude the existence of additional identical elements in the process, method, article or device including that element.

[0133] Through the description of the above embodiments, those skilled in the art can clearly understand that the above-described embodiment methods can be implemented by means of software plus a necessary general hardware platform. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation. Based on such an understanding, the technical solution of the present invention, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in various embodiments of the present invention.

[0134] The above describes the embodiments of the present invention in conjunction with the drawings, but the present invention is not limited to the above specific embodiments. The above specific embodiments are merely illustrative and not restrictive. Under the inspiration of the present invention, those of ordinary skill in the art can also make many forms without departing from the spirit and scope protected by the claims of the present invention, and all of them belong to the protection scope of the present invention.

[0135] Those of ordinary skill in the art can realize that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the embodiments of the present invention can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of the present invention.

[0136] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0137] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division, and there can be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the couplings, direct couplings, or communication connections shown or discussed among each other can be through some interfaces. The indirect couplings or communication connections of the devices or units can be in electrical, mechanical, or other forms.

[0138] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0139] In addition, each functional unit in various embodiments of the present invention can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0140] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, ROM, RAM, magnetic disks, or optical discs that can store program codes.

[0141] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art can easily think of changes or substitutions within the technical scope disclosed by the present invention and should be covered by the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A device control system based on a wireless mesh network, characterized in that: The device control system includes a cloud server, an edge server and an IoT device that communicate based on a wireless mesh network, wherein: The cloud server is used to obtain the current task requirements and the real-time status data of the IoT device; generate a linkage control strategy according to the current task requirements and the real-time status data; wherein the linkage control strategy includes the target IoT device that needs to respond to the current task requirements and the linkage control instructions corresponding to the target IoT device; and send the linkage control instructions to the edge server; The edge server is used to send the linkage control instructions to the corresponding target Internet of Things devices respectively, so that the target Internet of Things devices execute the linkage control instructions.

2. The device control system based on wireless mesh network according to claim 1, characterized in that: The edge server is used to obtain the real-time status data of the Internet of Things device; and determine whether to send the real-time status data sent by the Internet of Things device to the cloud server according to the current task requirements and the real-time status data.

3. The device control system based on wireless mesh network according to claim 2, characterized in that: The edge server is used to determine whether to send the real-time status data sent by the IoT device to the cloud server, or to process the real-time status data locally, according to the current task requirements and the real-time status data.

4. The device control system based on wireless mesh network according to claim 3, characterized in that: The edge server is used to filter out first real-time status data that needs to respond to the current task requirement and second real-time status data that does not need to respond to the current task requirement from the real-time status data according to the current task requirement; and filter out third real-time status data that needs to be processed by the cloud server and fourth real-time status data that does not need to be processed by the cloud server from the second real-time status data according to a preset rule; The first real-time status data and the third real-time status data are sent to the cloud server, and the second real-time status data and the fourth real-time status data except the third real-time status data are processed locally.

5. The device control system based on wireless mesh network according to claim 1, characterized in that: The cloud server is used to input the current task requirements and the real-time status data into a preset device linkage control model, so that the device linkage control model outputs a linkage control strategy; wherein the linkage control strategy is obtained by training using the historical control data of the Internet of Things device.

6. The device control system based on wireless mesh network according to claim 5, characterized in that: The cloud server is used to obtain the historical control data of the IoT device; pre-process the historical control data to obtain key features; use the key features to train the device linkage control model to be trained, and obtain the trained device linkage control model when the device linkage control model meets the preset convergence conditions; wherein the pre-processing at least includes cleaning, denoising and normalization processing.

7. The device control system based on wireless mesh network according to claim 6, characterized in that: The cloud server is used to obtain the execution result of the linkage control instruction sent by the target IoT device through the edge server; and adjust the linkage control strategy according to the execution result.

8. The device control system based on wireless mesh network according to claim 7, characterized in that: The cloud server and the edge server are used to monitor whether an abnormality occurs in the IoT device during the process of the target IoT device executing the linkage control instruction; and adjust the linkage control strategy according to the abnormality.

9. The device control system based on wireless mesh network according to claim 8, characterized in that: The edge server is used to monitor whether an abnormality occurs in the IoT device during the process in which the target IoT device executes the linkage control instruction; Determine the urgency and impact scope of the exception, and determine whether the cloud server adjusts the linkage control strategy according to the exception or the local server adjusts the linkage control strategy according to the exception based on the urgency and impact scope of the exception.

10. A device control method based on a wireless mesh network, characterized in that: The wireless mesh network includes a cloud server, an edge server and an IoT device, and the method includes: Obtain current task requirements and real-time status data of the IoT device; Generate a linkage control strategy according to the current task requirements and the real-time status data; wherein the linkage control strategy includes a target IoT device that needs to respond to the current task requirements and a linkage control instruction corresponding to the target IoT device; The linkage control instructions are sent to the corresponding target IoT devices through the edge server, so that the target IoT devices execute the linkage control instructions.

11. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; The memory is used to store computer programs; The processor is used to implement the method according to claim 10 when executing the program stored in the memory.

12. A computer-readable storage medium having instructions stored thereon, which when executed by one or more processors cause the processors to perform the method of claim 10.

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