Intelligent equipment management method and system based on micro service, medium and equipment

Abstract

The invention discloses a micro-service-based intelligent equipment management method and system, a medium and equipment, and the method comprises the following steps: S1, creating a micro-service management system which is responsible for equipment registration, equipment information storage and updating, real-time equipment operation state monitoring, equipment health data collection, and equipment sensor data collection through an Internet of Things protocol, a remote control instruction of a user is processed and issued to the equipment, and equipment faults are predicted by using a machine learning model; s2, equipment registration; s3, collecting equipment data; s4, equipment state monitoring; s5, user remote control; and S6, equipment fault prediction. The method has the advantages that the modules related to each step link can be independently developed and deployed, the development and online speed can be improved, the addition, modification and deletion of the equipment can be more quickly completed, the equipment management process is optimized, the equipment use efficiency is improved, the fault shutdown is reduced, the maintenance process is optimized, the operation efficiency is comprehensively improved, and the maintenance cost is reduced. Therefore, the total operation cost of an enterprise is reduced for a long time.

Description

Technical Field

[0001] The present invention relates to the field of computers, and in particular to a microservice-based intelligent device management method, system, medium and device. Background Art

[0002] With the rapid development of Internet of Things technology, the number of smart devices has increased dramatically, and traditional device management methods can no longer meet the needs of efficient and flexible management. As an emerging software architecture model, microservice architecture has the advantages of loose coupling and high scalability. The maintenance of traditional smart devices is to monitor the data of the equipment on site by maintenance personnel, and then analyze the monitored data. However, due to the wide distribution range of equipment and the limitations of the number of maintenance personnel and maintenance commuting distance, sampling surveys are usually used, and the structure of the survey can only be analyzed based on data from a certain period of time, which reduces the accuracy of equipment analysis, increases maintenance costs, and reduces operation and maintenance efficiency.

[0003] In view of this, it is necessary to provide a microservice-based intelligent device management method, system, medium and device. Summary of the invention

[0004] The present invention provides a microservice-based intelligent device management method, system, medium and device, which effectively solve the problems of low accuracy of maintenance results, high maintenance costs and low equipment operation and maintenance efficiency of existing intelligent devices.

[0005] The technical solution adopted by the present invention is:

[0006] A microservice-based intelligent device management method comprises the following steps:

[0007] S1. Create a microservice management system: responsible for device registration, device information storage and update, real-time monitoring of device operation status, collection of device health data, collection of device sensor data through the Internet of Things protocol, processing of user remote control instructions and sending them to the device, and use of machine learning models to predict device failures.

[0008] S2. Device registration: The microservice management system receives the basic information of the smart device, stores the basic information in the relational database of the microservice management system through the device information management service, and returns a response message of successful device registration to the user.

[0009] S3. Device data collection: The microservice management system obtains the operation data of smart devices at predetermined time intervals.

[0010] S4. Device status monitoring: The microservice management system monitors the working status of smart devices in real time based on pre-acquired threshold rules.

[0011] S5. User remote control: Smart devices receive control instructions initiated by users through the microservice management system and respond to execution results.

[0012] S6. Equipment failure prediction: The microservice management system trains historical operation data through machine learning algorithms. The generated prediction model is used to detect and analyze potential equipment failures in real time. When the probability of predicted failure exceeds the set threshold, the user automatically receives a fault warning issued by the microservice management system.

[0013] Furthermore, in step S2, a RESTful API interface is used for device registration, and device registration and query functions are provided to the outside through HTTP / HTTPS protocol, supporting data transmission in JSON format.

[0014] Furthermore, in step S3, the device data collection adopts two-way communication to realize data interaction between the intelligent device and the microservice management system, and uses a data compression algorithm to reduce network bandwidth occupancy.

[0015] Furthermore, the microservice management system in S4 provides a perspective view to maintenance personnel, which can display the real-time status, alarm information and operation history of all connected devices, and can set different interface access permissions according to user roles.

[0016] Furthermore, the user remote control in step S5 has multiple security verification mechanisms, including user identity verification, operation log recording, and real-time monitoring of user operation behavior.

[0017] Furthermore, the microservice management system supports multiple device communication protocols, including but not limited to MQTT, CoAP, and HTTP.

[0018] Furthermore, when monitoring equipment failure in S6, the microservice management system uses the XGBoost algorithm to extract features and perform pattern recognition on equipment historical data, and continuously optimizes the prediction model through A / B testing.

[0019] A microservice-based intelligent device management system, including:

[0020] The device information management service module is responsible for device registration, device information storage and update.

[0021] The status monitoring service module is used to output test case text.

[0022] Test and evaluation module, used to monitor the equipment operation status in real time and collect equipment health data;

[0023] The data collection service module is used to collect device sensor data.

[0024] The remote control service module is used to process the user's remote control instructions and send them to the device.

[0025] The fault prediction service module is used to predict equipment failures using machine learning models.

[0026] A computer-readable storage medium stores a computer program, and when the computer program is processed and executed, the steps of the microservice-based intelligent device management method are implemented. The computer-readable storage medium can adopt any combination of one or more readable storage media, wherein the readable storage medium includes an electrical, optical, electromagnetic, infrared or semiconductor system, device or device, or any combination thereof.

[0027] A computer device comprises a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus:

[0028] The memory is used to store computer programs;

[0029] The processor is used to execute the steps of the microservice-based intelligent device management method by running the program stored in the memory. The communication bus mentioned in the above terminal can be a peripheral component interconnect standard (PCI) bus or an extended industry standard architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. The communication interface is used for communication between the above terminal and other devices. The memory can include a random access memory (RAM), and can also include a non-volatile memory (non-volatile memory), such as at least one disk storage. Optionally, the memory can also be at least one storage device located away from the aforementioned processor. The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0030] Beneficial effects of the invention:

[0031] 1. The microservice architecture enables the modules related to each step to be independently developed and deployed, which improves the speed of development and launch. The addition, modification and deletion of equipment can be completed more quickly, which optimizes the equipment management process, improves equipment utilization efficiency, reduces downtime due to failures, optimizes the maintenance process, and comprehensively improves operational efficiency, thereby reducing the company's total operating costs in the long run.

[0032] 2. By leveraging the high scalability of microservices, specific functions can be easily expanded or replaced as needed, allowing the entire system to adapt to changing business needs and technology upgrades.

[0033] 3. It can monitor the operating status and environmental data of the monitored equipment in real time, and analyze the equipment data through machine learning to promptly discover existing and potential problems with the equipment, and provide solutions to decision makers through data analysis, which helps users take timely measures to reduce the probability of failure and minimize losses.

[0034] 4. Users can remotely control and manage equipment through the interface without having to go to the equipment site in person. This not only enhances the ability to perceive the equipment status, but also reduces manual maintenance costs and improves equipment availability and operational flexibility.

[0035] 5. The fault prediction mechanism can warn of equipment failures in advance and formulate maintenance plans by analyzing historical data. This proactive maintenance method reduces unexpected downtime, extends equipment life, and reduces overall maintenance costs. And through the collection and analysis of historical data, the system can continuously improve fault prediction models and equipment management strategies, provide a scientific basis for corporate decision-making, and form a closed loop of data-driven decision-making.

[0036] 6. By setting up a security authentication mechanism, it ensures that only authorized users can access and operate the device, improving the security of the system and data. At the same time, the fault-tolerant design of the microservice architecture also enhances the stability of the system and reduces the risk of single point failure.

[0037] 7. The intuitive user interface and rich visualization options allow users to easily understand the device status, simplify the operation process, and improve the user experience. This friendly interactive design lowers the technical threshold and ordinary users can easily get started.

[0038] 8. Supports multiple communication protocols and sensor integration, can adapt to different types of smart devices and diverse application scenarios, and enhances the adaptability and flexibility of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 A flowchart of a microservice-based intelligent device management method provided in an embodiment of the present application. DETAILED DESCRIPTION

[0040] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0041] like Figure 1 As shown, the first embodiment provided by the present application is a microservice-based intelligent device management method, comprising the following steps:

[0042] S1. Create a microservice management system: responsible for device registration, device information storage and update, real-time monitoring of device operation status, collection of device health data, collection of device sensor data through the Internet of Things protocol, processing user remote control instructions and sending them to the device, and using machine learning models to predict device failures;

[0043] S2. Device registration: The microservice management system receives the basic information of the smart device, stores the basic information in the relational database of the microservice management system through the device information management service, and returns a response message of successful device registration to the user; the basic information of the smart device includes but is not limited to the device unique identifier, device type, manufacturer, installation location, user information, etc.

[0044] S3. Equipment data collection: The microservice management system obtains the operation data of smart devices at predetermined time intervals (for example, every 5 seconds as a unit interval); the data includes but is not limited to temperature (unit: Celsius), humidity (unit: percentage), voltage (unit: volt), and equipment working status (for example, "running", "standby", "fault"). The data is uploaded to the data storage service in JSON format through the MQTT protocol.

[0045] S4. Equipment status monitoring: The microservice management system monitors the working status of smart devices in real time according to the pre-acquired threshold rules; the threshold rules are as follows: the upper temperature limit is 80 degrees Celsius, the lower temperature limit is 0 degrees Celsius; the upper humidity limit is 90%, and the lower humidity limit is 10%. When it is detected that the temperature or humidity exceeds the threshold, an alarm is automatically triggered, and the alarm information is displayed in real time through the user interface.

[0046] S5. User remote control: Smart devices receive control instructions initiated by users through the microservice management system and respond to execution results; control instructions include starting the device, stopping the device, and setting the working mode (such as energy-saving mode, standard mode).

[0047] S6. Equipment failure prediction: The microservice management system trains historical operation data through machine learning algorithms. The generated prediction model is used to detect and analyze potential equipment failures in real time. When the probability of predicted failure exceeds the set threshold, the user automatically receives a fault warning issued by the microservice management system.

[0048] In actual use, the microservice architecture needs to be designed to create a microservice management system. Programming language: Use Java, Python and other high-level languages, combined with the Spring Boot framework to build RESTful microservices; The database uses MySQL to store device information and historical data, and uses Redis for caching; Message queue: Use Apache Kafka for real-time data stream processing and message delivery; Use Docker to package each microservice as a container image, and deploy and manage it on the Kubernetes cluster to achieve automatic expansion and load balancing; Use the virtual machine and database services of the cloud platform (such as AWS, Alibaba Cloud, Inspur Cloud) to ensure the high availability and elasticity of the system. The architecture of microservices includes multiple aspects. The first aspect is service splitting: split the smart device management system into multiple independent microservices, including device discovery service, status monitoring service, data collection service, remote control service, fault prediction service, etc. Each service runs in an independent process and interacts through a lightweight communication mechanism (REST API, message queue). The second aspect is service registration and discovery: split the smart device management system into multiple independent microservices, including device discovery service, status monitoring service, data collection service, remote control service, fault prediction service, etc. Each service runs in an independent process and interacts through lightweight communication mechanisms (REST API, message queues). The third aspect is load balancing and fault tolerance: in the microservice architecture, load balancing technology is used to distribute requests to different service instances to achieve high availability and scalability. At the same time, fault tolerance mechanisms such as fuses and downgrades are used to ensure that the entire system can still operate normally when some services fail. The collection of device data mainly uses the Internet of Things technology to integrate sensors on smart devices with data collection microservices. Real-time collection of key indicator data such as temperature, humidity, pressure, and power of the device, and then the collected raw data is cleaned, denoised, and preprocessed to ensure the accuracy and validity of the data. The monitoring of device data requires real-time data stream processing: stream processing technology is used to continuously analyze and process real-time data. For example, by calculating algorithms such as moving averages and peak detection, abnormal behavior of devices can be monitored in real time. User remote control includes a security authentication mechanism: to ensure the security of remote control, a complete set of user authentication and authority management mechanisms is designed. Only authorized users can remotely control the device; Control command issuance: Through the remote control microservice, users can issue control commands to smart devices, such as start, stop, restart, configuration update, etc. These commands will be sent to the device for execution after verification and conversion; Remote debugging interface: Provide developers with a remote debugging interface, allowing them to debug and troubleshoot the device through remote connection tools. Device failure prediction includes the first step of feature extraction and modeling: Extract features related to device failure from historical data, including operating time, temperature peak, etc.Then, a machine learning algorithm is used to build a fault prediction model; the second step is fault prediction: the real-time collected data is input into the fault prediction model to predict the probability of equipment failure in the future. Once a potential failure risk is detected, the system will issue an early warning notification in a timely manner. Then the inspection personnel will use the fault prediction results to develop a targeted maintenance plan. For example, preventive maintenance is performed on high-risk equipment to reduce the possibility of failure.

[0049] In the above design, the management system based on microservice architecture has high flexibility, maintainability and scalability. Combined with the Internet of Things technology, it can realize real-time monitoring and data collection of smart devices, and then analyze the historical data of the equipment through machine learning algorithms to provide predictive perception capabilities of equipment failures. It can also be remotely operated to achieve convenient operation.

[0050] Specifically: in step S2, a RESTful API interface is used for device registration, and device registration and query functions are provided to the outside through HTTP / HTTPS protocol, supporting data transmission in JSON format.

[0051] The above design facilitates the rapid collection of device information.

[0052] Specifically: in step S3, the device data collection adopts two-way communication to realize the data interaction between the intelligent device and the microservice management system, and uses a data compression algorithm to reduce the network bandwidth occupation.

[0053] The above design facilitates two-way communication between the device and the management system and ensures smooth communication links.

[0054] Specifically: the microservice management system in S4 provides a perspective view to maintenance personnel, which can display the real-time status, alarm information and operation history of all connected devices, and can set different interface access permissions according to user roles.

[0055] In the above design, by providing perspective views to maintenance personnel, effective understanding of real-time status, alarm information and operation history can be achieved.

[0056] Specifically: the user remote control in step S5 has multiple security verification mechanisms, including user identity verification, operation log recording, and real-time monitoring of user operation behavior.

[0057] In the above design, the device can be remotely controlled only after user verification, ensuring the control security of the device.

[0058] Specifically: the microservice management system supports multiple device communication protocols, including but not limited to MQTT, CoAP, and HTTP.

[0059] In the above design, supporting multiple communication protocols for communication can improve compatibility with different devices and realize application on different devices.

[0060] Specifically: When monitoring equipment failure in S6, the microservice management system uses the XGBoost algorithm to extract features and perform pattern recognition on equipment historical data, and continuously optimizes the prediction model through A / B testing.

[0061] In the above design, the faults faced by the equipment can be automatically judged and traced, and the fault perception ability can be enhanced by continuously optimizing the model.

[0062] The second embodiment provided by the present application is a system for managing intelligent devices based on microservices, including:

[0063] The device information management service module is responsible for device registration, device information storage and update.

[0064] The status monitoring service module is used to output the test case text.

[0065] The test and evaluation module is used to monitor the operating status of the device in real time and collect the health data of the device.

[0066] The data collection service module is used to collect device sensor data.

[0067] The remote control service module is used to process the user's remote control instructions and send them to the device.

[0068] The fault prediction service module is used to predict equipment failures using machine learning models.

[0069] The user interface module supports multi-terminal access (computer, mobile phone, tablet), and provides intuitive user operation and device status display.

[0070] The operation log service module records all user operations and system events for subsequent auditing and data analysis.

[0071] The third embodiment provided by the present application is a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is processed and executed, the steps of the microservice-based intelligent device management method are implemented.

[0072] In addition, the computer-readable storage medium of this embodiment may adopt any combination of one or more computer-readable storage media, wherein the computer-readable storage medium includes electrical, optical, electromagnetic, infrared or semiconductor systems, devices or components, or any combination thereof.

[0073] The fourth embodiment provided by the present application is a computer device, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus: wherein:

[0074] The memory is used to store computer programs.

[0075] The processor is used to execute the steps of the microservice-based intelligent device management method by running the program stored in the memory.

[0076] As an embodiment of the present invention, the communication bus mentioned in the above terminal can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc.

[0077] As an implementation mode of the present invention, the communication interface is used for communication between the above-mentioned terminal and other devices.

[0078] As an embodiment of the present invention, the memory may include a random access memory (RAM) or a non-volatile memory, such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0079] As an embodiment of the present invention, the above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components.

[0080] To further explain in detail, it should be understood that the above is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A microservice-based intelligent device management method, characterized in that: The steps include: S1. Create a microservice management system: responsible for device registration, device information storage and update, real-time monitoring of device operation status, collection of device health data, collection of device sensor data through the Internet of Things protocol, processing user remote control instructions and sending them to the device, and using machine learning models to predict device failures; S2. Device registration: The microservice management system receives the basic information of the smart device, stores the basic information in the relational database of the microservice management system through the device information management service, and returns a response message of successful device registration to the user; S3, device data collection: the microservice management system obtains the operation data of smart devices at predetermined time intervals; S4. Device status monitoring: The microservice management system monitors the working status of smart devices in real time according to the pre-acquired threshold rules; S5, user remote control: the smart device receives the control instructions initiated by the user through the microservice management system and responds to the execution results; S6. Equipment failure prediction: The microservice management system trains historical operation data through machine learning algorithms. The generated prediction model is used to detect and analyze potential equipment failures in real time. When the probability of predicted failure exceeds the set threshold, the user automatically receives a fault warning issued by the microservice management system.

2. The microservice-based intelligent device management method according to claim 1, characterized in that: The device registration in step S2 adopts a RESTful API interface, provides device registration and query functions to the outside through HTTP / HTTPS protocol, and supports data transmission in JSON format.

3. The microservice-based intelligent device management method according to claim 1, characterized in that: In step S3, the device data collection adopts two-way communication to realize the data interaction between the intelligent device and the microservice management system, and uses a data compression algorithm to reduce the network bandwidth occupation.

4. The microservice-based intelligent device management method according to claim 1, characterized in that: The microservice management system in S4 provides maintenance personnel with a perspective view that can display the real-time status, alarm information, and operation history of all connected devices, and can set different interface access permissions based on user roles.

5. The microservice-based intelligent device management method according to claim 1, characterized in that: The user remote control in step S5 has multiple security verification mechanisms, including user identity verification, operation log recording, and real-time monitoring of user operation behavior.

6. The microservice-based intelligent device management method according to claim 1, characterized in that: The microservice management system supports multiple device communication protocols, including but not limited to MQTT, CoAP, and HTTP.

7. The microservice-based intelligent device management method according to claim 1, characterized in that: When monitoring equipment faults in S6, the microservice management system uses the XGBoost algorithm to extract features and perform pattern recognition on equipment historical data, and continuously optimizes the prediction model through A / B testing.

8. A microservice-based intelligent device management system, characterized by: include, The device information management service module is responsible for device registration, device information storage and update; The status monitoring service module is used to output the test case text; Test and evaluation module, used to monitor the equipment operation status in real time and collect equipment health data; Data collection service module, used to collect device sensor data; Remote control service module, used to process user's remote control instructions and send them to the device; The fault prediction service module is used to predict equipment failures using machine learning models.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is processed and executed, the steps of the microservice-based intelligent device management method according to any one of claims 1 to 7 are implemented.

10. A computer 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 execute the steps of the microservice-based intelligent device management method according to any one of claims 1 to 7 by running the program stored in the memory.

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