Extensible remote dynamic equipment management method and system

Abstract

The invention relates to an extensible remote dynamic equipment management method and system, and belongs to the technical field of equipment management. The method comprises the following steps: deploying a block chain node on a virtual server and configuring a block chain network configuration file; developing and deploying an intelligent contract to carry out equipment automatic management and decentralized data exchange; registering and authenticating distributed equipment and performing equipment identity management, wherein the equipment identity management comprises access control and privacy protection; the method comprises the following steps: acquiring equipment historical data on a block chain, and obtaining an equipment fault prediction model through an improved LightGBM algorithm according to the equipment historical data; equipment data on the block chain are monitored in real time, equipment abnormity is automatically detected through the equipment fault prediction model according to the equipment data, and an alarm is given in real time, so that transparency and traceability of the equipment data are ensured, automatic management of the equipment is realized, equipment fault prediction and response capabilities are improved, security audit and troubleshooting are facilitated, and the efficiency is improved. And the operation and maintenance efficiency and the expandability of the system are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of device management, and particularly relates to an extensible remote dynamic device management method and system. Background Art

[0002] In the context of the increasing popularity of intelligent devices today, the importance of device management systems has become increasingly prominent. Device management systems are designed to efficiently handle tasks such as device operation and maintenance, repair, and emergency response. However, many technical problems have emerged in the actual operation and maintenance process of existing device management systems, which have severely restricted the performance and application scope of the systems.

[0003] First, existing device management systems have security issues such as unauthorized access, insufficient identity authentication, and vulnerability of centralized servers to attacks, which may lead to the risk of data leakage. Moreover, existing device management systems lack transparent and traceable repair records, making system auditing and fault troubleshooting complex and difficult. At the same time, existing device management systems lack advanced analysis tools and algorithms, and are unable to accurately predict device failures and respond in real time to changes in device status, resulting in delays in maintenance and fault handling and low operation and maintenance efficiency. In addition, existing device management systems have the problem of rigid system architecture and lack of scalability, making it difficult to adapt to the needs of new devices or managing new types of devices, further restricting the applicability of device management systems. Summary of the Invention

[0004] To solve the above problems existing in the prior art, the present invention proposes an extensible remote dynamic device management method and system.

[0005] The object of the present invention can be achieved by the following technical solutions: An extensible remote dynamic device management method includes: Deploying blockchain nodes on a virtual server and configuring a blockchain network configuration file; Developing and deploying smart contracts for device automated management and decentralized data exchange; Registering and authenticating distributed devices and performing device identity management, where the device identity management includes access control and privacy protection; Obtaining device historical data on the blockchain and obtaining a device failure prediction model through an improved LightGBM algorithm based on the device historical data; Real-time monitoring of device data on the blockchain, automatically detecting device anomalies and giving real-time alarms according to the device data through the device failure prediction model.

[0006] Preferably, the deploying blockchain nodes on a virtual server and configuring a blockchain network configuration file includes: Recording and processing device data through the private blockchain network Quorum; The blockchain network configuration file includes, but is not limited to, consensus mechanisms, node roles, and permission policies. The consensus mechanism is used to maintain data consistency in the network and trust among nodes, including, but not limited to, Proof of Work (PoW) and Proof of Stake (PoS). The permission policy is the permission control rule defined in the blockchain network, used to manage the access permissions of nodes and users. The node roles refer to different nodes playing different roles in the blockchain network, with different permissions and responsibilities, including, but not limited to, full nodes, light nodes, and validation nodes.

[0007] Preferably, the development and deployment of smart contracts for device automation management and decentralized data exchange include: Writing smart contracts in Solidity language and deploying the smart contracts to the blockchain network to automatically process the upload of device data, the update of device status, and the interaction between devices; The decentralized data exchange is for direct data exchange between devices through P2P communication, and the change of relevant device data is notified through the event subscription mechanism of the blockchain. The smart contract automatically executes the interaction logic between devices without the intervention of a third party.

[0008] Preferably, the registration and authentication of distributed devices include that when a device joins the network, it is registered and authenticated through the smart contract and obtains a digital certificate. The device uses the digital certificate for identity verification during each communication. The digital certificate assigns a unique identity to each device for security authentication to ensure the authenticity and uniqueness of all device identities.

[0009] Preferably, for privacy protection, all device data is encrypted using encryption technology during transmission and storage to ensure that the data is not accessed without authorization, and the encrypted data is transmitted to the blockchain network through the secure communication protocol TLS to ensure the security of data transmission and storage; all device data is recorded on the blockchain, and once the device data is written to the blockchain, it cannot be tampered with; The access control is to ensure that only authorized users and devices can access sensitive information through the permission control of the blockchain.

[0010] Preferably, obtaining the device historical data on the blockchain and obtaining a device fault prediction model through the improved LightGBM algorithm based on the device historical data includes: Regularly obtaining device historical data through the API interface provided by the blockchain and storing it in the database; Performing data preprocessing on the device historical data and constructing a device historical data set. The data preprocessing includes data cleaning, data normalization, and data annotation; An equipment fault prediction model is trained and tested based on the equipment historical data set by improving the LightGBM algorithm; The improved LightGBM algorithm includes first introducing the SMOTETomek integrated sampling method to balance the equipment historical data set, improving the class distribution of the data set by synthesizing minority class samples and removing noise data on the boundary, then training a model on the balanced equipment historical data set, and optimizing the hyperparameters of LightGBM using the grid search technique.

[0011] Preferably, the real-time monitoring of the equipment data on the blockchain, automatically detecting equipment anomalies and giving real-time alarms according to the equipment data through the equipment fault prediction model includes: Obtaining equipment data from the blockchain in real time through the stream processing framework Apache Kafka; Preprocessing the equipment data to obtain standard equipment data, ensuring consistency with when training the equipment fault prediction model; Inputting the standard equipment data into the equipment fault prediction model to output equipment fault prediction labels, where the equipment fault prediction labels include equipment normal labels and equipment anomaly labels; When the equipment fault prediction label is an equipment anomaly label, sending an alarm instruction to the terminal.

[0012] An extensible remote dynamic equipment management system, which is applied to the above-mentioned extensible remote dynamic equipment management method, includes a blockchain network layer module, an equipment registration and authentication module, a fault prediction and alarm module, and a user visualization management module; The blockchain network layer module is used to build a private blockchain network, deploy blockchain nodes on a virtual server, configure a blockchain network configuration file, and develop smart contracts to achieve automated equipment management and decentralized data exchange; The equipment registration and authentication module is used to manage the identities of distributed equipment, ensure that only authenticated equipment can join the network, and protect the privacy and security of equipment data; The fault prediction and alarm module is used to obtain an equipment fault prediction model based on equipment historical data through an improved LightGBM algorithm, real-time monitor the equipment data on the blockchain, automatically detect equipment anomalies through the equipment fault prediction model, and give timely alarms when anomalies are detected; The user visualization management module is used to provide a user visualization interface, enabling managers to monitor the system status, view equipment data, receive alarm information, and perform management operations.

[0013] An electronic device includes a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the above-mentioned extensible remote dynamic device management method is implemented.

[0014] A storage medium containing computer-executable instructions, which are used to execute the above-mentioned extensible remote dynamic device management method when executed by a computer processor.

[0015] The beneficial effects of the present invention are as follows: (1) By deploying blockchain nodes on a virtual server, developing and deploying smart contracts, and registering and authenticating distributed devices, automated device management, decentralized data exchange, and device identity management are achieved. All device interaction records are publicly recorded on the blockchain, making all device interactions traceable, facilitating auditing and troubleshooting, improving system transparency, ensuring that only authorized devices can join the network and operate using the immutability of the blockchain, improving data security, automatically executing device management tasks through smart contracts, reducing manual processes, improving operation efficiency, and the decentralized architecture reducing dependence on the central server, improving system stability and anti-attack capabilities.

[0016] (2) By improving the LightGBM algorithm to obtain a device fault prediction model, high-precision device fault prediction is achieved. Real-time monitoring of device data on the blockchain, automatically detecting device anomalies and giving real-time alerts through the device fault prediction model, enabling managers to quickly respond to device status changes and potential problems, and reducing maintenance costs.

[0017] (3) By providing a user-friendly visual management interface, managers can easily monitor system status, view device data, receive alert information, and perform management operations. The modular design makes it easier to add new devices and manage new types of devices, enhancing the scalability and adaptability of the system. Description of the Drawings

[0018] For the convenience of those skilled in the art to understand, the present invention will be further described below in conjunction with the drawings.

[0019] Figure 1 It is a schematic flowchart of an extensible remote dynamic device management method of the present invention. Detailed Embodiments

[0020] To further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will, in conjunction with the drawings and preferred embodiments, detail the specific embodiments, structures, features, and their effects according to the present invention.

[0021] Please refer toFigure 1 , a scalable remote dynamic device management method, comprising: S1: Deploy a blockchain node on a virtual server and configure a blockchain network configuration file; S2: Develop and deploy a smart contract for device automation management and decentralized data exchange; S3: Register and authenticate distributed devices and perform device identity management, where the device identity management includes access control and privacy protection; S4: Obtain the device historical data on the blockchain, and obtain a device fault prediction model through an improved LightGBM algorithm according to the device historical data; S5: Real-time monitor the device data on the blockchain, and automatically detect device anomalies and give real-time alerts according to the device data through the device fault prediction model.

[0022] In this embodiment, the deployment of the blockchain node on the virtual server and the configuration of the blockchain network configuration file are specifically implemented through the following steps: S101: To ensure the security and privacy of device data, use the private blockchain network Quorum to record and process device data to ensure that only authorized nodes can join the network; S102: The blockchain network configuration file includes, but is not limited to, a consensus mechanism, node roles, and permission policies. The consensus mechanism is used to maintain the consistency of data in the network and the trust between nodes, including, but not limited to, proof of work (PoW) and proof of stake (PoS). The permission policy is the permission control rule defined in the blockchain network, used to manage the access permissions of nodes and users. The node roles are that in the blockchain network, different nodes play different roles, with different permissions and responsibilities, including, but not limited to, full nodes, light nodes, and verification nodes.

[0023] In this embodiment, the development and deployment of the smart contract for device automation management and decentralized data exchange are specifically implemented through the following steps: S201: Write a smart contract in Solidity language and deploy the smart contract to the blockchain network to automatically process the upload of device data, the update of device status, and the interaction between devices; S202: The decentralized data exchange is the direct data exchange between devices through P2P communication. The event subscription mechanism of the blockchain is used to notify relevant devices of data changes, and the smart contract automatically executes the interaction logic between devices without the intervention of a third party.

[0024] In this embodiment, the registration and authentication of distributed devices and the performance of device identity management, where the device identity management includes access control and privacy protection are specifically implemented through the following steps: S301: When the device joins the network, it registers and authenticates through the smart contract and obtains a digital certificate. The device uses the digital certificate for authentication during each communication. The digital certificate assigns a unique identity to each device for security authentication, ensuring the authenticity and uniqueness of all device identities.

[0025] S302: The privacy protection encrypts all device data using encryption technology during transmission and storage to ensure that the data is not accessed without authorization, and transmits the encrypted data to the blockchain network through the secure communication protocol TLS to ensure the security of data transmission and storage; all device data is recorded on the blockchain. Once the device data is written to the blockchain, it cannot be tampered with, ensuring the immutability, traceability, and transparency of the data, which is convenient for security auditing.

[0026] S303: The access control is to ensure that only authorized users and devices can access sensitive information through the permission control of the blockchain.

[0027] Specifically, role-based access control is used to ensure that only authorized personnel can perform critical operations.

[0028] It should be noted that the blockchain is a distributed ledger technology. It maintains the consistency and integrity of data through multiple nodes in the network, and uses encryption algorithms to ensure the security of transactions and the immutability of data. The smart contract is a computer program that automatically executes, controls, or records legal events.

[0029] In this embodiment, the steps for obtaining the device historical data on the blockchain and obtaining the device fault prediction model through the improved LightGBM algorithm based on the device historical data are specifically implemented as follows: S401: Regularly obtain the device historical data through the API interface provided by the blockchain and store it in the database; S402: Perform data preprocessing on the device historical data and construct a device historical data set. The data preprocessing includes data cleaning, data normalization, and data annotation; S403: Train and test the device fault prediction model through the improved LightGBM algorithm based on the device historical data set; The improved LightGBM algorithm first introduces the SMOTETomek comprehensive sampling method to balance the device historical data set, improves the class distribution of the data set by synthesizing minority class samples and removing noise data on the boundary, then trains the model on the balanced device historical data set, and optimizes the hyperparameters of LightGBM using the grid search technique.

[0030] It should be noted that the SMOTETomek comprehensive sampling method combines SMOTE oversampling and Tomek Links undersampling. This method first applies the SMOTE technique to oversample the minority class samples to generate additional synthetic samples. Subsequently, the Tomek Links undersampling technique is used to screen these augmented samples to remove the noise and overlapping samples located on the class boundary. Such processing ensures that the generated synthetic samples can effectively fill the blank areas near the class boundary, thereby providing more accurate boundary information in the model training stage and improving the performance and prediction accuracy of the model when dealing with imbalanced datasets.

[0031] In this embodiment, the real-time monitoring of the device data on the blockchain and the automatic detection of device anomalies and real-time alarming according to the device data through the device fault prediction model are specifically implemented through the following steps: S501: Obtain device data from the blockchain in real time through the stream processing framework Apache Kafka; S502: Preprocess the device data to obtain device standard data to ensure consistency with the training of the device fault prediction model; S503: Input the device standard data into the device fault prediction model to output device fault prediction labels, where the device fault prediction labels include device normal labels and device abnormal labels; S504: When the device fault prediction label is a device abnormal label, send an alarm instruction to the terminal.

[0032] An extensible remote dynamic device management system includes a blockchain network layer module, a device registration and authentication module, a fault prediction and alarming module, and a user visualization management module; The blockchain network layer module is used to construct a private blockchain network, deploy blockchain nodes on a virtual server, configure a blockchain network configuration file, and develop smart contracts to achieve automated device management and decentralized data exchange; The device registration and authentication module is used to manage the device identities of distributed devices, ensure that only authenticated devices can join the network, and protect the privacy and security of device data; The fault prediction and alarming module is used to obtain a device fault prediction model through an improved LightGBM algorithm based on device historical data, real-time monitor the device data on the blockchain, and automatically detect device anomalies through the device fault prediction model, and give an alarm in time when an anomaly is detected; The user visualization management module is used to provide a user visualization interface, enabling managers to monitor the system status, view device data, receive alarm information, and perform management operations.

[0033] It should be noted that the scalable remote dynamic device management system adopts a modular design and consists of multiple microservices that can be independently deployed and extended. It provides a unified API interface through an API gateway, facilitating the integration and extension of third-party systems; integrates the monitoring data of different devices, provides a unified operation interface, and allows remote execution of device control commands, such as switch operations and parameter adjustments.

[0034] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can, for example, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device.

[0035] The computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device.

[0036] The program code contained on a computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wire, optical fiber cable, RF, etc., or any suitable combination of the foregoing. The computer program code for performing the operations of the present invention can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., by using an Internet service provider to connect through the Internet).

[0037] As described above, the above are only the preferred embodiments of the present invention and do not impose any formal limitations on the present invention. Although the present invention has been disclosed above in preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or refinements to the above-disclosed technical content to obtain equivalent embodiments with equivalent changes within the scope of the technical solution of the present invention. However, as long as the content of the technical solution of the present invention is not departed from, any simple modifications, equivalent changes, and refinements made to the above embodiments based on the technical essence of the present invention still fall within the scope of the technical solution of the present invention.

Claims

1. A scalable remote dynamic device management method, characterized in that: include: Deploy blockchain nodes on virtual servers and configure blockchain network configuration files; Develop and deploy smart contracts for automated equipment management and decentralized data exchange; Register and authenticate distributed devices and perform device identity management, including access control and privacy protection; Obtain the historical data of the equipment on the blockchain, and obtain the equipment failure prediction model by improving the LightGBM algorithm based on the historical data of the equipment; The device data on the blockchain is monitored in real time, and the device fault prediction model is used to automatically detect device anomalies and issue real-time alarms based on the device data.

2. The scalable remote dynamic device management method according to claim 1, characterized in that: Deploying a blockchain node on a virtual server and configuring a blockchain network configuration file includes: Record and process device data through the private blockchain network Quorum; The blockchain network configuration file includes but is not limited to consensus mechanism, node role and permission strategy. The consensus mechanism is used to maintain the consistency of data in the network and the trust between nodes, including but not limited to proof of work PoW and proof of stake PoS. The permission strategy is the permission control rules defined in the blockchain network, which are used to manage the access rights of nodes and users. The node role is that different nodes play different roles in the blockchain network, with different permissions and responsibilities, including but not limited to full nodes, light nodes, and verification nodes.

3. The scalable remote dynamic device management method according to claim 1, characterized in that: The development and deployment of smart contracts for automated equipment management and decentralized data exchange includes: Write smart contracts in Solidity and deploy them to the blockchain network to automate the uploading of device data, updating of device status, and interaction between devices. The decentralized data exchange is a direct data exchange between devices through P2P communication. The changes in data of related devices are notified through the event subscription mechanism of the blockchain. The smart contract automatically executes the interaction logic between devices without the intervention of a third party.

4. The scalable remote dynamic device management method according to claim 1, characterized in that: The registration and authentication of distributed devices includes registering and authenticating the device through the smart contract when joining the network and obtaining a digital certificate. The device uses the digital certificate for identity authentication each time it communicates. The digital certificate assigns a unique identity to each device for security authentication to ensure the authenticity and uniqueness of all device identities.

5. The scalable remote dynamic device management method according to claim 1, characterized in that: The privacy protection mentioned above is that all device data is encrypted using encryption technology during transmission and storage to ensure that the data is not accessed by unauthorized persons, and the encrypted data is transmitted to the blockchain network through the secure communication protocol TLS to ensure the security of data transmission and storage; all device data is recorded on the blockchain, and once the device data is written into the blockchain, it cannot be tampered with; The access control is permission control through blockchain, ensuring that only authorized users and devices can access sensitive information.

6. The scalable remote dynamic device management method according to claim 1, characterized in that: The acquisition of equipment historical data on the blockchain and the acquisition of an equipment failure prediction model by improving the LightGBM algorithm based on the equipment historical data include: Regularly obtain historical data of equipment through the API interface provided by the blockchain and store it in the database; Performing data preprocessing on the equipment historical data and constructing an equipment historical data set, wherein the data preprocessing includes data cleaning, data normalization, and data labeling; According to the equipment historical data set, an equipment failure prediction model is obtained by training and testing the improved LightGBM algorithm; The improved LightGBM algorithm includes first introducing the SMOTETomek comprehensive sampling method to balance the device historical data set, synthesizing minority class samples and eliminating noise data on the boundary to improve the data set category distribution, then training the model on the balanced device historical data set, and using grid search technology to optimize the hyperparameters of LightGBM.

7. The scalable remote dynamic device management method according to claim 1, characterized in that: The real-time monitoring of device data on the blockchain, automatically detecting device anomalies and issuing real-time alarms through the device fault prediction model according to the device data, includes: Get device data from the blockchain in real time through the stream processing framework Apache Kafka; Preprocessing the equipment data to obtain equipment standard data to ensure consistency with the equipment failure prediction model when training; Inputting the equipment standard data into the equipment failure prediction model to output equipment failure prediction labels, wherein the equipment failure prediction labels include equipment normal labels and equipment abnormal labels; When the equipment fault prediction tag is an equipment abnormality tag, an alarm instruction is sent to the terminal.

8. An extensible remote dynamic device management system, applied to the extensible remote dynamic device management method as claimed in any one of claims 1 to 7, characterized in that: It includes blockchain network layer module, equipment registration and authentication module, fault prediction and alarm module, and user visualization management module; The blockchain network layer module is used to build a private blockchain network, deploy blockchain nodes on virtual servers, configure blockchain network configuration files, and develop smart contracts to achieve automated management of devices and decentralized data exchange; The device registration and authentication module is used for distributed devices to perform device identity management, ensuring that only authenticated devices can join the network and protecting the privacy and security of device data; The fault prediction and alarm module is used to obtain a device fault prediction model based on the device historical data by improving the LightGBM algorithm, monitor the device data on the blockchain in real time, and automatically detect device anomalies through the device fault prediction model, and issue an alarm in time when anomalies are detected; The user visualization management module is used to provide a user visualization interface, so that managers can monitor system status, view device data, receive alarm information and perform management operations.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the scalable remote dynamic device management method according to any one of claims 1 to 7 is implemented.

10. A storage medium containing computer executable instructions, characterized in that: When the computer executable instructions are executed by a computer processor, they are used to perform the scalable remote dynamic device management method as described in any one of claims 1 to 7.

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