Cloud-based integrated self-adaptive edge terminal system

Abstract

The invention discloses a cloud-based integrated self-adaptive edge terminal system, which comprises an embedded terminal and a platform terminal, the platform terminal is connected with the embedded terminal through an Internet of Things communication protocol, the embedded terminal comprises a main control unit and a communication subunit, and the communication subunit is connected with the embedded terminal through an Internet of Things communication protocol. The main control unit and the communication subunit are connected through an RTU (remote terminal unit) level private bus protocol; the method has the advantages that the embedded end and the platform end are combined, the powerful computing power of cloud computing and the real-time response advantage of edge computing can be utilized at the same time, intelligent terminal equipment is deployed at the embedded end, nearby processing and analysis of equipment data are achieved, the delay of data transmission is greatly reduced, and the data transmission efficiency is improved; the real-time performance of the system is improved; and 2, by means of cloud big data analysis and a machine learning algorithm of a platform end, the system can automatically adjust monitoring parameters and control strategies according to operation characteristics and environment changes of different devices, and self-adaptive intelligent monitoring and control are realized.

Description

Technical Field

[0001] This invention relates to the field of Internet of Things (IoT) technology, and in particular to an adaptive edge terminal system based on cloud-edge integration. Background Technology

[0002] With the rapid development of IoT technology, a large number of devices are connected to the network, making real-time monitoring and management of these devices an urgent need.

[0003] Current IoT edge terminal systems typically connect various devices directly to the cloud via IoT communication protocols, uploading device information to the cloud platform for data storage, analysis, and execution. This approach is prone to high data transmission latency, leading to slow device response and processing speeds. Furthermore, connecting a large number of devices to the cloud can result in inflexible configuration of the IoT edge terminal system. Additionally, traditional IoT edge terminal systems have poor scalability, failing to meet the need for adaptive intelligent monitoring and control by automatically adjusting monitoring parameters and control strategies based on the operating characteristics and environmental changes of different devices. Therefore, improvements are still needed. Summary of the Invention

[0004] To address the aforementioned problems, this invention provides a cloud-integrated adaptive edge terminal system, comprising an embedded terminal and a platform terminal. The platform terminal and the embedded terminal are connected via an IoT communication protocol. The embedded terminal includes a main control unit and a communication subunit, which are connected via an RTU-level private bus protocol. The platform terminal includes device management: managing terminal device information of the main control unit, such as serial number and status (online / offline); a protocol instruction library: providing a graphical interface for creating, editing, and storing protocol read commands for different sensor models, with instructions stored in structured data (such as JSON format); and instruction issuance and binding: the platform terminal provides an operation interface allowing users to issue and bind specific protocol commands from the instruction library to specific communication ports of designated main control unit terminals.

[0005] Preferably, the main control unit includes configuration management: storing and managing the configuration information of each port; sub-unit management: forwarding the received protocol instructions to the corresponding communication sub-units and issuing collection cycle instructions; and data aggregation and reporting: receiving external device data (such as sensor data) uploaded by the communication sub-units, adding timestamps, device IDs and other information, and then packaging and uploading it to the platform.

[0006] Preferably, the communication subunit includes instruction storage: receiving protocol instructions (such as MODBUS) from the main control unit and storing them non-lossably (such as storing them in Flash). Each subunit corresponds to a fixed number of configured physical ports and stores the instructions for the corresponding physical ports after configuration. Protocol execution: strictly following a preset cycle, actively sending the stored protocol instructions to the connected downstream devices to read commands. Data acquisition: receiving and verifying the response data of the sensors, and transmitting the valid sensor data values ​​back to the main control unit through the RTU-level private bus protocol.

[0007] Preferably, the platform also includes a data acquisition strategy configuration: the time period for data acquisition can be independently configured for ports with bound protocols, and data visualization: the sensor data uploaded by the main control unit terminal is displayed and presented in the form of charts, etc.

[0008] Preferably, the core of the main control unit is a high-performance embedded processor.

[0009] Preferably, the communication subunit adopts a module that supports mainstream sensor interaction protocols.

[0010] The beneficial effects of this invention are as follows: First, by combining the embedded end and the platform end, the powerful computing capabilities of cloud computing and the real-time response advantages of edge computing can be utilized simultaneously. At the same time, by deploying intelligent terminal devices on the embedded end, the device data can be processed and analyzed locally, which greatly reduces the latency of data transmission and improves the real-time performance of the system. Second, with the help of cloud-based big data analysis and machine learning algorithms on the platform end, the system of this invention can automatically adjust monitoring parameters and control strategies according to the operating characteristics of different devices and environmental changes, so as to achieve adaptive intelligent monitoring and control. Attached Figure Description

[0011] The present invention will be described by way of example and with reference to the accompanying drawings, wherein: Figure 1 This is a schematic diagram of the system flow of the present invention; Detailed Implementation

[0012] All features disclosed in this specification, or all steps in all disclosed methods or processes, may be combined in any way, except for mutually exclusive features and / or steps.

[0013] Unless otherwise stated, any feature in this specification may be replaced by other equivalent or similar features. That is, unless otherwise stated, each feature is merely one example of a series of equivalent or similar features.

[0014] like Figure 1The system illustrates an adaptive edge terminal system based on a cloud-edge architecture, comprising an embedded terminal and a platform terminal. The platform terminal and the embedded terminal are connected via an IoT communication protocol. The embedded terminal includes a main control unit and a communication subunit, which are connected via an RTU-level private bus protocol. The platform terminal includes device management: managing terminal device information of the main control unit, such as serial number and status (online / offline), enabling remote monitoring and management of the devices; a protocol command library: providing a graphical interface for creating, editing, and storing protocol read commands for different sensor models, with commands stored in structured data (such as JSON format), improving the convenience and flexibility of command management; and command issuance and binding: the platform terminal provides an operation interface that allows users to issue and bind specific protocol commands from the command library to specific communication ports of designated main control unit terminals, achieving precise command issuance and binding.

[0015] The main control unit includes configuration management: storing and managing the configuration information of each port to ensure the flexibility and traceability of the configuration; sub-unit management: forwarding the received protocol instructions to the corresponding communication sub-units and issuing collection cycle instructions to realize the fine-grained management of external devices by the communication sub-units; and data aggregation and reporting: receiving external device data (such as sensors) uploaded by the communication sub-units, adding timestamps, device IDs and other information, and then packaging and uploading it to the platform to ensure the integrity and real-time performance of the data.

[0016] The communication subunit includes instruction storage: receiving protocol instructions (such as MODBUS) from the main control unit and storing them non-lossably (e.g., in Flash). Each subunit corresponds to a fixed number of configured physical ports and stores the instructions for the corresponding physical port configuration. Protocol execution: strictly following a preset cycle, actively sending the stored protocol instructions to the connected downstream devices to read commands and realize the timed acquisition of data from the downstream devices. Data acquisition: receiving and verifying the response data of the sensors, and transmitting the valid sensor data values ​​back to the main control unit through the RTU-level private bus protocol to ensure the accuracy and reliability of the data.

[0017] The platform also includes data acquisition strategy configuration: the time period for data acquisition can be independently configured for ports with bound protocols to meet the acquisition needs of different application scenarios. Data visualization: the sensor data uploaded by the main control unit terminal is displayed and presented in the form of charts, etc., to improve the intuitiveness and analyzability of the data.

[0018] The core of the main control unit is a high-performance embedded processor, which can ensure the system's processing power and stability.

[0019] The communication subunit uses a module that supports mainstream sensor interaction protocols to achieve stable communication with the sensor.

[0020] During operation, the platform manages terminal device information of the main control unit, such as serial number and status (online / offline), through its device management function. Then, through its protocol command library function, it provides a graphical interface for creating, editing, and storing protocol read commands for different sensor models. Commands are stored as structured data (e.g., JSON format). After the protocol commands are stored, the platform's command issuance and binding function provides an operation interface, allowing users to issue and bind specific protocol commands from the command library to specific communication ports of the designated main control unit terminal. Upon receiving configuration information from the platform, the main control unit stores and manages the configuration information of each port through its configuration management function, ensuring configuration flexibility and traceability. Simultaneously, through its sub-unit management function, it forwards received protocol commands to the corresponding communication sub-units and issues acquisition cycle commands, enabling fine-grained management of external devices by the communication sub-units. The communication sub-units, through their command storage function, store the protocol commands received from the main control unit. Instructions (such as MODBUS) are stored non-lossably (e.g., in Flash). Each subunit corresponds to a fixed number of configured physical ports, storing the instructions configured for the corresponding physical ports. Then, through the protocol execution function of the communication subunit, the stored protocol instructions are actively sent to the connected downstream devices according to a preset cycle to read the commands, realizing the timed acquisition of data from the downstream devices. The communication subunit then receives and verifies the sensor response data through the data acquisition function, and sends the valid sensor data values ​​back to the main control unit through the RTU-level private bus protocol. The main control unit's data aggregation and reporting function receives the external device data (such as sensors) uploaded by the communication subunit, adds timestamps, device IDs, and other information, and packages and uploads it to the platform to ensure data integrity and real-time performance. The platform's data visualization function displays the sensor data uploaded by the main control unit terminal and presents it in the form of charts and graphs for timely and efficient processing, improving the intuitiveness and analyzability of the data.

[0021] The platform-side data acquisition strategy configuration function in this invention can independently configure the data acquisition time period of the port with the bound protocol, meet the acquisition needs of different application scenarios, and automatically adjust the monitoring parameters and control strategies according to the operating characteristics of different devices and environmental changes, so as to achieve adaptive intelligent monitoring and control.

[0022] The beneficial effects of this invention are as follows: First, by combining the embedded end and the platform end, the powerful computing capabilities of cloud computing and the real-time response advantages of edge computing can be utilized simultaneously. At the same time, by deploying intelligent terminal devices on the embedded end, the device data can be processed and analyzed locally, which greatly reduces the latency of data transmission and improves the real-time performance of the system. Second, with the help of cloud-based big data analysis and machine learning algorithms on the platform end, the system of this invention can automatically adjust monitoring parameters and control strategies according to the operating characteristics of different devices and environmental changes, so as to achieve adaptive intelligent monitoring and control.

[0023] This invention is not limited to the specific embodiments described above. The invention extends to any new feature or combination disclosed in this specification, as well as any new method or process step or combination disclosed herein.

Claims

1. A cloud-integrated adaptive edge terminal system, characterized in that, The system includes an embedded terminal and a platform terminal. The platform terminal and the embedded terminal are connected via an IoT communication protocol. The embedded terminal includes a main control unit and a communication subunit, which are connected via an RTU-level private bus protocol. The platform terminal includes device management: managing terminal device information of the main control unit, such as serial number and status (online / offline); protocol instruction library: providing a graphical interface for creating, editing, and storing protocol read commands for different sensor models, with instructions stored in structured data (such as JSON format); and instruction issuance and binding: the platform terminal provides an operation interface that allows users to issue and bind specific protocol commands from the instruction library to specific communication ports of a specified main control unit terminal.

2. The cloud-integrated adaptive edge terminal system according to claim 1, characterized in that, The main control unit includes configuration management: storing and managing the configuration information of each port; sub-unit management: forwarding the received protocol instructions to the corresponding communication sub-units and issuing collection cycle instructions; and data aggregation and reporting: receiving external device data (such as sensor data) uploaded by the communication sub-units, adding timestamps, device IDs and other information, and then packaging and uploading it to the platform.

3. The cloud-integrated adaptive edge terminal system according to claim 1, characterized in that, The communication subunit includes instruction storage: receiving protocol instructions (such as MODBUS) from the main control unit and storing them non-lossably (e.g., in Flash). Each subunit corresponds to a fixed number of configured physical ports and stores the instructions for the corresponding physical ports after configuration. Protocol execution: strictly following a preset cycle, actively sending the stored protocol instructions to the connected downstream devices to read commands. Data acquisition: receiving and verifying the response data of the sensors, and transmitting the valid sensor data values ​​back to the main control unit through the RTU-level private bus protocol.

4. The cloud-integrated adaptive edge terminal system according to claim 1, characterized in that, The platform also includes data acquisition strategy configuration: the time period for data acquisition can be independently configured for ports with bound protocols, and data visualization: the sensor data uploaded by the main control unit terminal is displayed and presented in the form of charts and other formats.

5. The cloud-integrated adaptive edge terminal system according to claim 1, characterized in that, The core of the main control unit is a high-performance embedded processor.

6. The cloud-integrated adaptive edge terminal system according to claim 1, characterized in that, The communication subunit uses a module that supports mainstream sensor interaction protocols.

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