Internet of things operation and maintenance system and method supporting automatic protocol expansion

Abstract

The invention provides an Internet of Things operation and maintenance system and method supporting protocol automatic expansion, and belongs to the field of Internet of Things, and the system comprises a data collection module which is used for carrying out protocol plug-in loading according to a configuration file; when data acquisition needs to be carried out on the Internet of Things equipment, determining a target protocol type, determining a target protocol plug-in according to the target protocol type, and calling the target protocol plug-in to establish communication connection; performing data acquisition on the equipment based on the established communication connection; the data processing module is used for carrying out data preprocessing on the collected data to obtain processed business data; the rule engine module is used for performing data analysis on the processed service data based on a rule chain and a rule engine to obtain a service decision result; and the data output module is used for pushing the data and sending the to-be-pushed data to the pushing object. By applying the system provided by the invention, the communication connection can be established based on the protocol plug-in, and a new communication protocol can be adapted by configuring the protocol plug-in, so that the protocol adaptation efficiency can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of Internet of Things, and in particular to an Internet of Things operation and maintenance system and method supporting automatic protocol expansion. Background Art

[0002] With the development of IoT technology, IoT platforms have been widely used to achieve various tasks in various industrial production scenarios. In these IoT applications, IoT operation and maintenance platforms are often used to collect data from various IoT devices and conduct unified management and monitoring of these devices through data analysis.

[0003] During the operation of the IoT operation and maintenance platform, it is necessary to establish communication with IoT devices based on the communication protocols used by IoT devices and then collect data from IoT devices. Currently, various communication protocols are generally configured in the underlying code of the IoT operation and maintenance platform to achieve communication between the platform and IoT devices.

[0004] In actual application scenarios, the IoT devices connected to the network are usually changing, and the communication protocols used by each IoT device are different. If the newly connected IoT device uses a communication protocol that is not configured in the IoT operation and maintenance platform, the platform will not be able to collect data from the device. Technical personnel are required to customize and develop the underlying code of the platform to adapt the platform to the new communication protocol. This process requires a lot of manpower and time, resulting in low efficiency of protocol adaptation and poor platform versatility and scalability. Summary of the Invention

[0005] In view of this, an embodiment of the present invention provides an Internet of Things operation and maintenance system and method that supports automatic protocol expansion, so as to solve the problem that when facing a new communication protocol, the existing Internet of Things operation and maintenance platform needs to customize the development of underlying code to adapt to the new communication protocol, and the efficiency of protocol adaptation is low, which makes the platform's versatility and scalability poor.

[0006] To achieve the above objectives, the embodiments of the present invention provide the following technical solutions:

[0007] An IoT operation and maintenance system supporting automatic protocol expansion, comprising:

[0008] Data acquisition module, data processing module, rule engine module and data output module;

[0009] The data acquisition module is used to load the protocol plug-in according to a preset configuration file, and the successfully loaded protocol plug-ins form a plug-in protocol library; when data acquisition is required for a target IoT device, the target protocol type corresponding to the target IoT device is determined; in the plug-in protocol library, the target protocol plug-in corresponding to the target protocol type is determined, the target protocol plug-in is called, and a communication connection is established with the target IoT device; data is collected from the target IoT device based on the established communication connection to obtain business data corresponding to the target IoT device;

[0010] The data processing module is used to perform data preprocessing on the service data corresponding to the target IoT device to obtain processed service data;

[0011] The rule engine module is configured to determine a target rule chain corresponding to the target IoT device from among the pre-built rule chains, and perform data analysis on the processed business data based on the target rule chain and the pre-built rule engine to obtain a business decision result;

[0012] The data output module is used to determine the data to be pushed corresponding to the business decision result and the push object corresponding to the data to be pushed, and send the data to be pushed to the corresponding push object.

[0013] The above-mentioned IoT operation and maintenance system, optionally, the data acquisition module includes: a configuration file reader, a protocol loader and a protocol manager;

[0014] The configuration file reader is used to read the configuration file, parse the configuration file, and obtain the protocol plug-in path;

[0015] The protocol loader is configured to determine whether a plug-in directory exists in the protocol plug-in path. If the plug-in directory exists in the protocol plug-in path, the protocol loader traverses the plug-in files of each protocol type in the plug-in directory, performs validity verification on each plug-in file of the protocol type, and if the plug-in file passes the validity verification, loads the protocol plug-in corresponding to the plug-in file into the memory based on a preset loading algorithm, so that the protocol plug-in initiates a registration request to the protocol manager.

[0016] The protocol manager is used to, when receiving a registration request initiated by a protocol plug-in loaded in the memory, determine the registration information corresponding to the protocol plug-in, and perform legitimacy verification on the protocol plug-in based on the registration information; if the protocol plug-in passes the legitimacy verification, determine the plug-in information corresponding to the protocol plug-in, update the preset protocol-plug-in mapping table based on the plug-in information corresponding to the protocol plug-in, load the protocol plug-in into a preset version sandbox, perform compatibility verification on the protocol plug-in loaded into the version sandbox, and if the protocol plug-in loaded into the version sandbox passes the compatibility verification, perform a plug-in hot switching operation.

[0017] The above-mentioned Internet of Things operation and maintenance system, optionally, the protocol loader is further used to record a path error log when the plug-in directory does not exist in the protocol plug-in path;

[0018] The protocol loader is further configured to record invalid plug-in information corresponding to the plug-in file if the plug-in file currently undergoing validity verification fails the validity verification;

[0019] The protocol manager is further configured to refuse registration of a protocol plug-in currently undergoing validity verification if the protocol plug-in fails the validity verification, and record registration error information corresponding to the protocol plug-in;

[0020] The protocol manager is further used to, after determining the target protocol type, determine the plug-in information that matches the target protocol type among the various plug-in information recorded in the protocol-plug-in mapping table, and use the protocol plug-in corresponding to the plug-in information that matches the target protocol type as the target protocol plug-in.

[0021] The above-mentioned IoT operation and maintenance system, optionally, the data processing module includes: a data filter and a data converter;

[0022] The data filter is used to filter the business data corresponding to the target IoT device according to a preset filtering condition to obtain filtered business data;

[0023] The data converter is used to perform data format conversion on the filtered business data according to a preset format conversion rule to obtain converted business data, and use the converted business data as the processed business data.

[0024] The above-mentioned IoT operation and maintenance system, optionally, the rule engine module includes: a rule parser, a rule execution engine and a rule storage module;

[0025] The rule storage module is used to persistently store the various data analysis rules set by the user;

[0026] The rule parser is used to parse each of the data analysis rules to obtain a parsed rule corresponding to each of the data analysis rules;

[0027] The rule execution engine is used to determine the matching rules corresponding to the input data in each of the parsed rules when the rule engine receives the input data to be analyzed, apply the matching rules to perform data analysis on the input data, and call the pre-built spatiotemporal rule operator library to perform spatiotemporal correlation analysis when the preset spatiotemporal rule node is triggered.

[0028] The above-mentioned IoT operation and maintenance system, optionally, the data output module includes: a format converter and a data transmitter;

[0029] The format converter is used to determine the transmission data format corresponding to the push object, perform data format conversion on the data to be pushed according to the transmission data format, and obtain converted data corresponding to the data to be pushed;

[0030] The data transmitter is configured to transmit the converted data corresponding to the data to be pushed to the push object, so as to send the data to be pushed to the push object.

[0031] The aforementioned IoT operation and maintenance system may optionally further include: a data storage module;

[0032] The data storage module includes a protocol converter, a dynamic memory and a resource manager; the resource manager is configured with a quantized storage unit;

[0033] The protocol converter is configured to, when target data needs to be stored, perform metadata analysis on the target data to obtain a data type corresponding to the target data, perform data format conversion on the target data based on the data type corresponding to the target data and a preset storage data type, convert the target data into data of the storage data type, and use the converted data as data to be stored;

[0034] The dynamic memory is used to determine a target storage engine corresponding to the data to be stored among a plurality of preset storage engines, and store the data to be stored in the target storage engine based on a preset load balancing strategy and a hierarchical storage strategy;

[0035] The resource manager is configured to perform fault detection on each of the storage engines and, when a fault is detected, perform storage switching according to a preset storage switching policy;

[0036] The quantized storage unit is configured to perform data value analysis on each of the storage engines based on a preset value decay model, and to perform data migration on each of the storage engines based on the data value analysis results;

[0037] The resource manager is further configured to perform cache cleanup according to a preset cache management mechanism.

[0038] The aforementioned IoT operation and maintenance system may optionally further include: a message bus layer;

[0039] The message bus layer is used to convert the data format of the data to be distributed when data distribution is required to be performed on the data to be distributed in the system, so as to obtain the converted data to be distributed;

[0040] The message bus layer is further used to distribute the converted data to be distributed according to a preset routing mechanism and a dynamically adjusted distribution strategy; the routing mechanism is a topic-based intelligent routing mechanism.

[0041] The aforementioned IoT operation and maintenance system may optionally further include: a front-end configuration module;

[0042] The front-end configuration module is used to display the front-end configuration interface to the user, so that the user can perform operation and maintenance management through the front-end configuration interface;

[0043] The front-end configuration module is further used to display a rule chain orchestration interface to the user, so that the user can orchestrate the rule chain through the rule chain orchestration interface to build a rule chain; the rule chain orchestration interface is configured with an orchestration function of time-space associated nodes.

[0044] An IoT operation and maintenance method supporting automatic protocol expansion is applied to the aforementioned IoT operation and maintenance system supporting automatic protocol expansion, comprising:

[0045] Establishing a communication connection between the target protocol plug-in and the target IoT device through the data acquisition module; the target protocol plug-in is obtained by calling the target protocol type corresponding to the target IoT device from the plug-in protocol library;

[0046] Utilize the data acquisition module to collect data from the target IoT device to obtain business data;

[0047] Using a rule engine module to determine a target rule chain corresponding to the target IoT device from pre-built rule chains, and performing data analysis on the pre-processed business data based on the target rule chain and the pre-built rule engine to obtain a business decision result;

[0048] The data to be pushed corresponding to the business decision result and the push object corresponding to the data to be pushed are determined through a data output module, and the data to be pushed is sent to the push object.

[0049] Based on the above-mentioned embodiment of the present invention, an Internet of Things operation and maintenance system and method supporting automatic protocol expansion are provided, including: a data acquisition module, a data processing module, a rule engine module, and a data output module. The data acquisition module is used to load protocol plug-ins according to a preset configuration file, and the successfully loaded protocol plug-ins form a plug-in protocol library. When data acquisition is required for a target Internet of Things device, the target protocol type corresponding to the target Internet of Things device is determined. In the plug-in protocol library, a target protocol plug-in corresponding to the target protocol type is determined, the target protocol plug-in is called, and a communication connection is established with the target Internet of Things device. Data is collected from the target Internet of Things device based on the established communication connection to obtain business data corresponding to the target Internet of Things device. The data processing module is used to preprocess the business data corresponding to the target Internet of Things device to obtain processed business data. The rule engine module is used to determine a target rule chain corresponding to the target Internet of Things device from each pre-established rule chain, and perform data analysis on the processed business data based on the target rule chain and the pre-established rule engine to obtain a business decision result. The data output module is used to determine the data to be pushed corresponding to the business decision result and the push object corresponding to the data to be pushed, and send the data to the push object to the push object. By using the system provided by the embodiments of the present invention, it is possible to call the corresponding independent protocol plug-in based on the communication protocol adopted by the IoT device, establish communication with the target IoT device, and then collect data from the target IoT device. When the IoT device adopts a new protocol, the developer only needs to configure the corresponding protocol plug-in for the new protocol. During operation, the system can dynamically load the protocol plug-in corresponding to the new protocol based on the configuration file, realizing flexible adaptation of the communication protocol. This eliminates the need for customized development of the underlying system code, which helps improve the efficiency of protocol adaptation and the versatility and scalability of the IoT operation and maintenance platform. Secondly, the system provided by the embodiments of the present invention combines rule chains and rule engines to analyze business data. The rule nodes of the rule chain and the individual rules in the rule engine can be configured according to the actual data analysis requirements, which helps meet the complex data analysis requirements of different businesses and improves the speed and timeliness of data processing. In addition, the system provided by the embodiments of the present invention adopts a modular layered design. Each module can be independently developed, tested, and maintained, facilitating expansion and replacement, effectively reducing system coupling, improving development, testing, and maintenance efficiency, and further improving the versatility and scalability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0051] Figure 1 A schematic diagram of the structure of an Internet of Things operation and maintenance system supporting automatic protocol expansion provided by an embodiment of the present invention;

[0052] Figure 2 A schematic diagram of a data acquisition module workflow provided by an embodiment of the present invention;

[0053] Figure 3 A schematic diagram of a data processing flow of an Internet of Things operation and maintenance system provided by an embodiment of the present invention;

[0054] Figure 4 Another flow chart of a data processing flow of an Internet of Things operation and maintenance system provided by an embodiment of the present invention;

[0055] Figure 5 A schematic diagram of the architecture of an IoT operation and maintenance system supporting automatic protocol expansion provided by an embodiment of the present invention;

[0056] Figure 6 A schematic diagram of a protocol plug-in hot switching process provided by an embodiment of the present invention;

[0057] Figure 7 A flowchart of an Internet of Things operation and maintenance method supporting automatic protocol expansion is provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0059] In this application, the terms "comprises," "comprising," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not preclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0060] The embodiment of the present invention provides an Internet of Things operation and maintenance system that supports automatic protocol expansion, the execution subject of which can be a server of the system. The structural diagram of the system can be shown as follows: Figure 1 As shown, the IoT operation and maintenance system provided by the embodiment of the present invention includes:

[0061] Data collection module 101, data processing module 102, rule engine module 103 and data output module 104;

[0062] The data acquisition module 101 is used to load the protocol plug-in according to a preset configuration file, and the successfully loaded protocol plug-ins form a plug-in protocol library; when data acquisition is required for a target IoT device, the target protocol type corresponding to the target IoT device is determined; in the plug-in protocol library, the target protocol plug-in corresponding to the target protocol type is determined, the target protocol plug-in is called, and a communication connection is established with the target IoT device; data is collected from the target IoT device based on the established communication connection to obtain business data corresponding to the target IoT device;

[0063] The data processing module 102 is configured to perform data preprocessing on the service data corresponding to the target IoT device to obtain processed service data;

[0064] The rule engine module 103 is configured to determine a target rule chain corresponding to the target IoT device from among the pre-built rule chains, and perform data analysis on the processed business data based on the target rule chain and the pre-built rule engine to obtain a business decision result;

[0065] The data output module 104 is configured to determine the data to be pushed corresponding to the business decision result and the push object corresponding to the data to be pushed, and send the data to be pushed to the corresponding push object.

[0066] The system provided in the embodiment of the present invention is equipped with a data acquisition module, a data processing module, a rule engine module, and a data output module. The data acquisition module can be understood as a gateway, which is responsible for communicating with various types of IoT devices and collecting the required business data. The data acquisition module can be equipped with a variety of communication interfaces, specifically including Ethernet interfaces, serial communication interfaces (such as RS232, RS485), wireless communication interfaces (such as WIFI, Bluetooth, 4G / 5G modules), and other communication interfaces. In actual application, a protocol plug-in corresponding to each protocol type can be constructed in advance based on the communication protocols of each IoT device currently connected to the IoT, and the configuration files corresponding to each protocol plug-in can be configured and stored in the corresponding storage location. When the data acquisition module (gateway) is started, the configuration file can be obtained from the corresponding storage location, and the protocol plug-in corresponding to each protocol type can be loaded according to the configuration file. The successfully loaded protocol plug-ins serve as the system's plug-in protocol library.

[0067] When the system needs to collect data from an IoT device connected to the Internet of Things, it can use that device as the target IoT device. The communication protocol used by the target IoT device can be determined based on the handshake information sent by the target IoT device or the protocol type pre-configured for the device. This protocol type is then used as the target protocol type. The data collection module selects a protocol plug-in that matches the target protocol type from the various protocol plug-ins in the plug-in protocol library and uses that plug-in as the target protocol plug-in. The target protocol plug-in is then called to establish a communication connection with the target IoT device through the corresponding communication interface. Once a communication connection is successfully established between the system and the target IoT device, the system can collect business data from the target IoT device on demand. The business data collected by the data collection module is then sent to the data processing module for data preprocessing.

[0068] It's understood that each protocol plug-in corresponds to a specific communication protocol. Calling the plug-in establishes a communication connection based on the corresponding communication protocol through the corresponding communication interface. Each protocol plug-in provides detailed definitions of the data structures and function interfaces within the corresponding communication protocol, along with sample code. For example, key data structures such as register data formats and function code definitions are defined, and a series of function interfaces, including data parsing, encapsulation, and validation, are provided. Specifically, for the MQTT (Message Queuing Telemetry Transport) protocol plug-in, the formats of data structures such as message headers, topics, and payloads are defined within the plug-in in accordance with the MQTT protocol specification. Comprehensive function interfaces are provided, including a connection establishment function for establishing a stable TCP connection with an MQTT server; a message publishing function for efficiently encapsulating and publishing collected data in the MQTT protocol format; and message subscription and reception functions for subscribing to topics of interest and reliably receiving server-pushed messages. Each function interface is accompanied by detailed sample code to help developers gain a deep understanding and flexibly invoke it, accelerating the development and integration of protocol functionality.

[0069] In the system provided by an embodiment of the present invention, upon receiving business data from a target IoT device sent by a data acquisition module, the data processing module can preprocess the business data of the target IoT device according to a pre-defined data preprocessing strategy, and transmit the preprocessed business data as processed business data to the rule engine module. Specific data preprocessing operations, such as data filtering and data cleaning, can be configured based on actual needs.

[0070] The rule engine module analyzes business data to determine appropriate business decisions. Specific data analysis methods can be configured based on actual needs. For example, device alarm analysis can be performed to determine whether device alarms are necessary, or device control analysis can be performed to determine whether device control operations are appropriate. The rule engine module primarily conducts in-depth data analysis based on rule chains and rule engines. The rule engine module is configured with various rule chains and rule engines. A rule chain consists of multiple nodes with specific processing logic. Users can construct rule chains based on actual business needs. The rule engine is constructed based on a rule programming model and applies pre-configured rules to perform data analysis and provide feedback. After receiving processed business data from the data processing module, the rule engine module, based on the pre-configured mapping between rule chains and IoT devices, retrieves the rule chain that matches the target IoT device from the pre-configured rule chains and uses this rule chain as the target rule chain. Applying the nodes and rule engine in the target rule chain, the module analyzes the processed business data to determine the business decision. Specifically, the processed business data can be input into the first node of the target rule chain, triggering the logical operations of each node in sequence and invoking the rule engine for analysis as needed. For example, in an environmental monitoring scenario, the rule chain can consist of a data filtering node, a data conversion node, an aggregation calculation node, and an alarm triggering node. Business data is environmental data such as temperature, humidity, and air quality. When applying this rule chain for data analysis, the business data first enters the data filtering node. This node filters out invalid data based on set conditions, such as retaining only temperature data between -20 and 50 degrees Celsius. The processed data then flows to the data conversion node, which converts the data units from one format to another, such as from Fahrenheit to Celsius, for subsequent processing. Based on the data processed by the previous node, the aggregation calculation node performs in-depth statistical calculations on the data over a period of time, such as calculating key indicators such as average temperature and humidity change rate. Finally, the alarm triggering node determines whether to trigger an alarm based on the data processed by the previous node according to set thresholds and conditions. During the processing of each node, the rule engine can be called on demand. For example, the data filtering node can call the rule engine to filter data according to predetermined filtering rules, and the data filtering node can call the rule engine to convert data formats according to predetermined data conversion rules, etc.

[0071] The business decision results obtained by the rule engine module are sent to the data output module. The data output module can then, based on a pre-defined data transmission mechanism, determine the data to be pushed, along with the corresponding push targets. This push data can be data that needs to be fed back to other systems or devices, such as alarm information or device control data, or data that needs to be stored locally. The push target refers to the destination to which the data is to be sent, and can include alarm systems, IoT devices, or storage devices.

[0072] By using the system provided by the embodiments of the present invention, it is possible to call the corresponding independent protocol plug-in based on the communication protocol adopted by the IoT device, establish communication with the target IoT device, and then collect data from the target IoT device. When the IoT device adopts a new protocol, the developer only needs to configure the corresponding protocol plug-in for the new protocol. During operation, the system can dynamically load the protocol plug-in corresponding to the new protocol based on the configuration file, realizing flexible adaptation of the communication protocol. This eliminates the need for customized development of the underlying system code, which helps improve the efficiency of protocol adaptation and the versatility and scalability of the IoT operation and maintenance platform. Secondly, the system provided by the embodiments of the present invention combines rule chains and rule engines to analyze business data. The rule nodes of the rule chain and the individual rules in the rule engine can be configured according to the actual data analysis requirements, which helps meet the complex data analysis requirements of different businesses and improves the speed and timeliness of data processing. In addition, the system provided by the embodiments of the present invention adopts a modular layered design. Each module can be independently developed, tested, and maintained, facilitating expansion and replacement, effectively reducing system coupling, improving development, testing, and maintenance efficiency, and further improving the versatility and scalability of the system.

[0073] exist Figure 1 On the basis of the system shown, in the IoT operation and maintenance system provided by the embodiment of the present invention, the data acquisition module includes: a configuration file reader, a protocol loader and a protocol manager;

[0074] The configuration file reader is used to read the configuration file, parse the configuration file, and obtain the protocol plug-in path;

[0075] The protocol loader is configured to determine whether a plug-in directory exists in the protocol plug-in path. If the plug-in directory exists in the protocol plug-in path, the protocol loader traverses the plug-in files of each protocol type in the plug-in directory, performs validity verification on each plug-in file of the protocol type, and if the plug-in file passes the validity verification, loads the protocol plug-in corresponding to the plug-in file into the memory based on a preset loading algorithm, so that the protocol plug-in initiates a registration request to the protocol manager.

[0076] The protocol manager is used to, when receiving a registration request initiated by a protocol plug-in loaded in the memory, determine the registration information corresponding to the protocol plug-in, and perform legitimacy verification on the protocol plug-in based on the registration information; if the protocol plug-in passes the legitimacy verification, determine the plug-in information corresponding to the protocol plug-in, update the preset protocol-plug-in mapping table based on the plug-in information corresponding to the protocol plug-in, load the protocol plug-in into a preset version sandbox, perform compatibility verification on the protocol plug-in loaded into the version sandbox, and if the protocol plug-in loaded into the version sandbox passes the compatibility verification, perform a plug-in hot switching operation.

[0077] In the system provided by an embodiment of the present invention, the data acquisition module is equipped with a configuration file reader, a protocol loader, and a protocol manager to enable dynamic loading of protocol plug-ins. The configuration file reader is primarily used to read and parse configuration files, the protocol loader is primarily used to load protocol plug-ins into memory, and the protocol manager is primarily used to maintain the mapping relationship between protocols and plug-ins. Specifically, when the data acquisition module is running, the configuration file reader automatically reads a configuration file from a specified storage location. This configuration file can be a pre-imported configuration file or a configuration file used to store the protocol plug-in path specified in the front-end interface. The configuration file can be in XML or JSON format. For example, in a JSON-formatted configuration file, the "protocolPluginPath" field specifies the plug-in directory. The configuration file reader parses the configuration file to obtain the protocol plug-in path. The protocol loader uses the path to access the protocol plug-in path and determine whether a corresponding plug-in directory exists under the protocol plug-in path. If a plug-in directory exists, the protocol loader iterates through all plug-in files in the plug-in directory and checks whether the plug-in file for each protocol type in the plug-in directory is valid. If the plug-in file is valid, the protocol plug-in is loaded into memory based on the plug-in file using a preset loading algorithm. The loaded protocol plug-in then initiates a registration request to the protocol manager. The preset loading algorithm may adopt a loading algorithm based on a reflection mechanism.

[0078] When the protocol manager receives a registration request from a protocol plug-in, it determines the registration information based on the request and verifies the validity of the protocol plug-in based on the registration information. If the protocol plug-in passes the validity verification, the plug-in information is recorded and updated to the pre-set protocol-plug-in mapping table, and the protocol plug-in is considered to have been successfully loaded. The protocol-plug-in mapping table does not record the data table of the mapping relationship between protocol types and protocol plug-ins. It is used to maintain the mapping relationship between each protocol plug-in currently successfully loaded in the system and the protocol type.

[0079] The protocol manager can dynamically switch between old and new versions of protocol plug-ins during system operation using a hot swapping mechanism. Specifically, the protocol manager embeds a version sandbox. Upon detecting the successful loading of a new version of a protocol plug-in in memory, it loads the sandbox environment and places the new version of the plug-in into the sandbox (an isolated memory zone). The new version of the protocol plug-in undergoes compatibility verification. If it passes, a hot swap is performed using a dual-buffered registry (co-existing mapping tables for the old and new plug-ins). This allows the new version of the protocol plug-in to be enabled without downtime. Using session mirroring technology, the TCP / UDP connection state (e.g., Modbus session ID) established by the old plug-in is losslessly migrated to the new plug-in process. After all old connections have terminated (forced closure due to timeout), the old plug-in's memory resources are released, and the old plug-in can be archived and retained within the sandbox environment. If the new version of the protocol plug-in fails compatibility verification, a protocol conversion adaptation layer is automatically injected to convert historical data in real time to a format that the new plug-in can process (e.g., using a pre-configured abstract syntax tree-based protocol converter). If there is a version conflict between the new version of the protocol plug-in and the old version of the protocol plug-in, you can roll back to the stable version in the stable sandbox and issue an alarm.

[0080] Based on the system provided by the embodiments of the present invention, technicians can configure corresponding plug-in files in the protocol plug-in path according to actual needs. During runtime, the system can dynamically load each protocol plug-in based on the plug-in files in the protocol plug-in path. This allows for dynamic loading of protocol plug-ins and flexible adaptation to various communication protocols. Furthermore, protocol plug-ins can be updated in seconds, avoiding system downtime caused by device protocol iterations in the Industrial Internet of Things.

[0081] Based on the system provided by the above embodiment, in the system provided by the embodiment of the present invention, the protocol loader is further configured to record a path error log when the plug-in directory does not exist in the protocol plug-in path;

[0082] The protocol loader is further configured to record invalid plug-in information corresponding to the plug-in file if the plug-in file currently undergoing validity verification fails the validity verification;

[0083] The protocol manager is further configured to refuse to register a protocol plug-in currently undergoing validity verification if the protocol plug-in fails the validity verification, and record registration error information corresponding to the protocol plug-in.

[0084] In the system provided by the embodiment of the present invention, if the protocol loader does not find a plug-in directory under the protocol plug-in path when judging whether there is a plug-in directory in the protocol plug-in path, the current loading process is stopped and a path error log is recorded. When the protocol loader is performing validity verification on a plug-in file, if the currently verified plug-in file fails to pass the validity verification, the protocol plug-in corresponding to the plug-in file is stopped from loading, and the invalid plug-in information corresponding to the plug-in file is recorded to indicate that the plug-in file is invalid. When the protocol manager is performing legality verification on a protocol plug-in, if the currently verified protocol plug-in fails to pass the legality verification, the current protocol plug-in is refused to be registered, which is deemed to be a failure to load the protocol plug-in, and the registration error information corresponding to the protocol plug-in is recorded to indicate that a registration error has occurred in the protocol plug-in.

[0085] In order to better illustrate the process of dynamically loading protocol plug-ins in the data acquisition module of the system provided by the embodiment of the present invention, Figure 2 A schematic diagram of the workflow of a data acquisition module is shown, which mainly shows the loading process of the protocol plug-in, which mainly includes:

[0086] S201: The configuration file reader obtains the configuration file from the specified location, parses the configuration file, and obtains the protocol plug-in path;

[0087] S202: The protocol loader defines a plug-in directory according to the protocol plug-in path and determines whether the plug-in directory exists;

[0088] S203: If the plug-in directory exists, traverse each plug-in file in the plug-in directory;

[0089] S204: If the plug-in directory does not exist, record an error log;

[0090] S205: When traversing each plug-in file, for the currently accessed plug-in file, determine whether the current file is valid;

[0091] S206: If the current file is valid, start loading the plug-in file;

[0092] S207: If the current file is invalid, record the invalid plug-in information;

[0093] S208: After loading the plug-in file, the plug-in class is analyzed based on the reflection mechanism and a plug-in instance is created;

[0094] S209: Verify the integrity of the plug-in;

[0095] S210: If the plug-in passes the integrity verification, the plug-in is loaded and the plug-in initiates a registration request to the protocol manager;

[0096] S211: The protocol manager verifies the plug-in registration information;

[0097] S212: If the registration information of the plug-in fails to pass the verification, the registration is rejected and an error is recorded;

[0098] S213: If the plug-in registration information passes the verification, the plug-in information is added to the global protocol-plug-in mapping table;

[0099] S214: Update the mapping table status to facilitate subsequent matching of protocol plug-ins based on the mapping table.

[0100] Based on the system provided in the above embodiment, in the system provided in the embodiment of the present invention, the protocol manager is further used to, after determining the target protocol type, determine the plug-in information that matches the target protocol type among the various plug-in information recorded in the protocol-plug-in mapping table, and use the protocol plug-in corresponding to the plug-in information that matches the target protocol type as the target protocol plug-in.

[0101] In the system provided by an embodiment of the present invention, when the data acquisition module needs to collect data from the target Internet of Things device, after determining the target protocol type corresponding to the target Internet of Things device, the protocol manager can match the target protocol type with each plug-in information in the protocol-plug-in mapping table, find the plug-in information that matches the target protocol type, and use the protocol plug-in corresponding to the plug-in information as the target protocol plug-in to determine the target protocol plug-in corresponding to the target protocol type in the plug-in protocol library.

[0102] exist Figure 1 On the basis of the system shown, in the IoT operation and maintenance system provided by the embodiment of the present invention, the data processing module includes: a data filter and a data converter;

[0103] The data filter is used to filter the business data corresponding to the target IoT device according to a preset filtering condition to obtain filtered business data;

[0104] The data converter is used to perform data format conversion on the filtered business data according to a preset format conversion rule to obtain converted business data, and use the converted business data as the processed business data.

[0105] In the system provided by an embodiment of the present invention, a data processing module is configured with a data filter and a data converter. Business data collected by the data acquisition module may first be input into the data filter. The data filter may filter the business data according to preset filtering conditions. The filtered business data then enters the data converter. The data converter may convert the business data into data of a corresponding format according to preset format conversion rules. The business data that has undergone data format conversion is considered business data that has completed data preprocessing, i.e., the so-called processed business data. The filtering conditions and format conversion rules may be set according to actual business needs.

[0106] Based on the system provided by the embodiment of the present invention, a modular architecture is adopted in the data processing module to deploy various data preprocessing operations, which is convenient for expanding various data preprocessing operations according to actual needs and is conducive to meeting various business needs.

[0107] exist Figure 1 On the basis of the system shown, in the IoT operation and maintenance system provided by the embodiment of the present invention, the rule engine module includes: a rule parser, a rule execution engine and a rule storage module;

[0108] The rule storage module is used to persistently store the various data analysis rules set by the user;

[0109] The rule parser is used to parse each of the data analysis rules to obtain a parsed rule corresponding to each of the data analysis rules;

[0110] The rule execution engine is used to determine the matching rules corresponding to the input data in each of the parsed rules when the rule engine receives the input data to be analyzed, apply the matching rules to perform data analysis on the input data, and call the pre-built spatiotemporal rule operator library to perform spatiotemporal correlation analysis when the preset spatiotemporal rule node is triggered.

[0111] In the system provided by an embodiment of the present invention, the rule engine module is configured with a rule parser, a rule execution engine, and a rule storage module. In actual application scenarios, users can customize the data analysis rules in the rule engine in the front-end interface, for example, "When the temperature data is greater than 30 degrees Celsius and the humidity data is less than 40%, trigger a high temperature and low humidity alarm." The user-configured data analysis rules can include spatiotemporal correlation rules, which are rules used for cross-device spatiotemporal correlation analysis, that is, they can be used to jointly analyze spatiotemporal correlation events across multiple devices. In response to the user's operation to set data analysis rules, the rule storage module can persistently store the user-configured data analysis rules, ensuring that they can be quickly loaded when the gateway is restarted or the rules are updated, ensuring stable operation of the rule engine. To further improve the performance of the rule engine, optimized data structures, such as hash tables, can be used to store and query rules, ensuring millisecond-level processing speeds even when dealing with large amounts of rules and data. The rule parser is primarily responsible for parsing the data analysis rules set by the user, parsing the colloquial rules into an internal representation that the computer can understand, and obtaining the parsed rules corresponding to each data analysis rule. When the rule engine module calls the rule engine for data analysis, the rule execution engine can match the input data to be analyzed based on the parsed rules, find the rules that match the input data, and apply the rules to analyze the input data to achieve real-time data processing.

[0112] In the system provided by embodiments of the present invention, during the rule chain construction process, users can configure spatiotemporal correlation nodes as needed—i.e., nodes requiring spatiotemporal correlation analysis on data. If a spatiotemporal correlation node exists in the currently executing rule chain, the rule execution engine, upon triggering the spatiotemporal rule node, invokes a pre-defined spatiotemporal rule operator library and applies it to parse the corresponding spatiotemporal correlation rules. This allows for cross-device spatiotemporal correlation analysis and identifies whether the current state meets the requirements for a composite event of space-space correlation. Specifically, spatiotemporal window functions (such as SPATIAL_WITHIN(radius) and TEMPORAL_SEQUENCE(minutes)) can be added to the rule parser to support the compilation of geofence + time sequence composite rules as spatiotemporal correlation rules. The rule execution engine constructs a device relationship graph and updates device state correlations in real time through incremental graph calculation (e.g., using an adjacency matrix to store device topology). When a spatiotemporal correlation node is triggered, the spatiotemporal correlation rules that meet the triggering conditions are dynamically compiled into FPGA hardware acceleration instructions (e.g., using OpenCL to generate a temperature gradient calculation pipeline) to perform cross-device spatiotemporal correlation analysis. For example, in a factory equipment coordinated early warning scenario, three types of IoT devices are deployed in the reactor area of ​​a chemical plant: a temperature sensor (Device A) for real-time monitoring of reactor temperature; a gas detector (Device B) for detecting flammable gas (ether) concentrations; and a solenoid valve (Device C) for controlling the cooling water pipeline. The rule engine is configured with spatiotemporal association rules for the temperature sensor, gas detector, and valve position. When the reactor temperature sensor (Device A) detects an overtemperature event, the rule engine executes the following process: It uses an operator to confirm that Devices B and C are within a 50-meter geofence; it verifies that Device B has reported three gas level violations within five minutes; it calculates the device association weight (0.92 > threshold 0.8) using a distributed event graph; the rule engine dynamically compiles FPGA instructions and issues valve control commands; and the system triggers a multi-level alarm, completing a coordinated response across all devices.

[0113] Based on the system provided by the embodiment of the present invention, complex event processing across devices and time series can be achieved during the data analysis process, which is conducive to improving the accuracy of early warning.

[0114] exist Figure 1 On the basis of the system shown, in the IoT operation and maintenance system provided by the embodiment of the present invention, the data output module includes: a format converter and a data transmitter;

[0115] The format converter is used to determine the transmission data format corresponding to the push object, perform data format conversion on the data to be pushed according to the transmission data format, and obtain converted data corresponding to the data to be pushed;

[0116] The data transmitter is configured to transmit the converted data corresponding to the data to be pushed to the push object, so as to send the data to be pushed to the push object.

[0117] In the system provided by an embodiment of the present invention, a format converter and a data transmitter are configured in the data output module to realize data push. After the data output module determines the data to be pushed corresponding to the current business decision result and its corresponding push object, the format converter can determine the data format used by the push object in data transmission based on the pre-configured device information, and use the data format as the transmission data format corresponding to the push object. The format converter can perform data format conversion on the data to be pushed based on the transmission data format, convert the data to be pushed into data in the transmission data format, and use the converted data as the conversion data corresponding to the data to be pushed. The conversion data corresponding to the data to be pushed will enter the data transmitter, and the data transmitter can transmit the conversion data corresponding to the data to be pushed to the push object based on the address of the push object, so as to realize the operation of sending the data to be pushed to the push object.

[0118] Based on the system provided by the embodiment of the present invention, the data output module can convert the data to be pushed into data that matches the transmission data format of the push object, which is conducive to reliably sending the data to the specified destination and improving the reliability of data transmission.

[0119] exist Figure 1 On the basis of the system shown, the IoT operation and maintenance system provided by the embodiment of the present invention further includes: a data storage module;

[0120] The data storage module includes a protocol converter, a dynamic memory and a resource manager; the resource manager is configured with a quantized storage unit;

[0121] The protocol converter is configured to, when target data needs to be stored, perform metadata analysis on the target data to obtain a data type corresponding to the target data, perform data format conversion on the target data based on the data type corresponding to the target data and a preset storage data type, convert the target data into data of the storage data type, and use the converted data as data to be stored;

[0122] The dynamic memory is used to determine a target storage engine corresponding to the data to be stored among a plurality of preset storage engines, and store the data to be stored in the target storage engine based on a preset load balancing strategy and a hierarchical storage strategy;

[0123] The resource manager is configured to perform fault detection on each of the storage engines and, when a fault is detected, perform storage switching according to a preset storage switching policy;

[0124] The quantized storage unit is configured to perform data value analysis on each of the storage engines based on a preset value decay model, and to perform data migration on each of the storage engines based on the data value analysis results;

[0125] The resource manager is further configured to perform cache cleanup according to a preset cache management mechanism.

[0126] In the system provided by the embodiment of the present invention, a data storage module is also provided, which is used to store various types of data. The data that need to be stored may include various data analysis rules configured by the user, information of various rule chains, various configuration data of the system, and business data or business decision results of IoT devices, etc. The data storage module is configured with a protocol converter, a dynamic memory and a resource manager. When the data storage module needs to store target data, the protocol converter can perform metadata analysis on the target data to obtain the data type of the target data. The protocol converter can convert the data format of the target data based on a pre-configured data type conversion mechanism, convert the target data from the current data type to a preset storage data type, for example, convert multiple protocols such as MQTT / Modbus into a standard JSON format, use the converted target data as the data to be stored, and input the data to be stored into the dynamic memory.

[0127] The data storage module can be pre-deployed with multiple storage engines, such as MinIO (a high-performance distributed object storage system), databases, IOTDB (an Internet of Things database), and Redis (a key-value store). Based on the data type, the dynamic storage module can find a matching storage engine among the pre-deployed storage engines and use that engine as the target storage engine. For example, cached data can be stored in Redis, large files in MinIO, and transaction data in MySQL (a relational database management system). The dynamic storage module is pre-configured with load balancing and tiered storage strategies. During data storage, the data to be stored can be allocated to the target storage engine based on these pre-deployed load balancing and tiered storage strategies. Specifically, the load balancing strategy can intelligently partition data using a hash algorithm based on GPU load, and then store data in partitioned storage to achieve load balancing. The tiered storage strategy can use a priority queue to prioritize data storage, prioritizing the storage of alarm data. Furthermore, the tiered storage strategy can implement preemptive writes to multiple replicas of data using the Raft protocol (a consensus algorithm based on log replication). The spatiotemporal storage module also stores models of spatiotemporal association rules and the spatiotemporal rule operator library. It stores spatiotemporal rule configurations in a high-performance engine (such as Redis) for fast access. The storage data type can be expanded, with the addition of a "spatial rule configuration" category. The resource manager prioritizes frequently accessed data during cache cleanup.

[0128] The resource management module within the data storage module can detect faults in each storage engine through heartbeat signals. Upon detecting a fault, it performs storage switching according to a pre-set storage switching policy, achieving failover within seconds. Furthermore, the resource management module can clean up cold data or expired resources based on a pre-set cache management mechanism to reduce storage costs. The cache management mechanism can be based on existing cache cleaning algorithms, such as the LRU-K algorithm, which is an improvement on the Least Recently Used (LRU) algorithm.

[0129] The resource management module also integrates a quantized storage unit, which is an algorithm module. The quantized storage unit dynamically analyzes the value of data based on the value decay model and guides the migration of data between conventional storage engines. The value decay model can be constructed based on the Q-Learning reinforcement learning algorithm, which can automatically calculate the data value decay curve based on dimensions such as data access frequency and business relevance. The quantum storage unit performs probabilistic migration based on the value score output by the value decay model (such as the probability P ≥ 0.8 that a high-scoring unit migrates to SSD). For low-value data, a compression algorithm based on information entropy is used to discard data dimensions with entropy values ​​greater than the threshold (such as temperature data only retains the ±3σ interval value). The value decay calculation formula can be shown as follows:

[0130] (Formula 1)

[0131] Among them, V0 represents the initial value, λ represents the decay factor, and t represents time.

[0132] The data migration process may include the following steps:

[0133] Value Tagging: The Quantum Storage Unit assigns a value classification (high, medium, or low) to data in all storage engines. High-value data (such as real-time monitoring data) is retained in the hot storage engine (Redis), while medium-value data (such as historical analysis data) is migrated to the warm storage engine (database). Low-value data (such as archived logs) is migrated to the cold storage engine (MinIO).

[0134] Migration trigger: Based on the output of the value decay model (e.g., automatic downgrade when access frequency falls below a threshold).

[0135] Migration targets: Data in all engines (not just data managed by quantized units), with a cross-engine downgrade (e.g., Redis → MySQL → MinIO). The resource manager performs the migration in conjunction with load balancing policies, ensuring high-value data is prioritized for access performance.

[0136] Based on the system provided by the embodiment of the present invention, various types of data can be persistently stored through multiple storage engines, which is conducive to adaptive expansion of the storage engine according to actual data storage needs. During the data storage process, the load balancing strategy and the hierarchical storage strategy can be combined to store data. While taking load balancing into consideration, the timeliness of the response to important data can be guaranteed, which is conducive to improving the efficiency and flexibility of data storage. Secondly, data can be migrated based on quantized storage units, which can further reduce storage costs, ensure that high-value data has priority access performance, and reduce data query latency.

[0137] exist Figure 1 On the basis of the system shown, the IoT operation and maintenance system provided by the embodiment of the present invention further includes: a message bus layer;

[0138] The message bus layer is used to convert the data format of the data to be distributed when data distribution is required to be performed on the data to be distributed in the system, so as to obtain the converted data to be distributed;

[0139] The message bus layer is further used to distribute the converted data to be distributed according to a preset routing mechanism and a dynamically adjusted distribution strategy; the routing mechanism is a topic-based intelligent routing mechanism.

[0140] The system provided by an embodiment of the present invention includes a message bus layer that can transmit data required to be transmitted between modules in the system according to a preconfigured data distribution algorithm. Specifically, the message bus layer can receive data using various protocols through protocol conversion. When data distribution is required within the system, the message bus layer can determine the target module that subscribes to the data based on preconfigured subscription requirements. Based on the data format used by the target module, the message bus layer converts the data to be distributed into a format such as JSON or binary, obtaining the converted data to be distributed. It is understood that the converted data to be distributed matches the data format of the target module. The message bus layer can distribute the converted data to be distributed to the target module through a topic-based intelligent routing mechanism and dynamically adjusted distribution strategies. Specifically, the topic-based intelligent routing mechanism can establish a mapping relationship between topics and system modules through hash partitioning, thereby implementing intelligent routing based on the topic of the data to be distributed, and sending the data to the corresponding target module. During the data transmission process, the message bus layer can dynamically adjust the data distribution order by monitoring the load in real time, for example, by using weighted round-robin to prioritize the data transmission of high-priority topics. In addition, replication strategies and automatic fault switching mechanisms can be used to ensure data reliability, and throughput performance can be optimized through zero-copy technology, memory prefetching, and parallel processing, ultimately achieving millisecond-level topic matching to ensure data transmission availability and routing efficiency.

[0141] exist Figure 1 On the basis of the system shown, the IoT operation and maintenance system provided by the embodiment of the present invention further includes: a front-end configuration module;

[0142] The front-end configuration module is used to display the front-end configuration interface to the user, so that the user can perform operation and maintenance management through the front-end configuration interface;

[0143] The front-end configuration module is further used to display a rule chain orchestration interface to the user, so that the user can orchestrate the rule chain through the rule chain orchestration interface to build a rule chain; the rule chain orchestration interface is configured with an orchestration function of time-space associated nodes.

[0144] The system provided by the embodiment of the present invention is configured with a front-end configuration module. The front-end configuration module can display a visual configuration interface on the front end for displaying the front-end configuration interface to the user. Configuration controls for various operation and maintenance operations can be set in the front-end configuration interface. Users can perform various operation and maintenance operations through the front-end configuration interface, such as protocol plug-in management, setting rules in the rule engine, viewing device status data, etc.

[0145] In the system provided by the embodiment of the present invention, the front-end configuration module is also used to display the rule chain orchestration interface to the user. The configuration functions of various rule nodes can be configured in the rule chain orchestration interface. The user can drag and drop the controls corresponding to the various rule nodes configured in the interface through the rule chain orchestration interface to build the corresponding rule chain. The rule chain orchestration interface is configured with the configuration function of the spatiotemporal association node, and the rule chain orchestration interface is integrated with the corresponding parameter setting controls, such as the time slider and geographic coordinate input. When the user drags the control corresponding to the spatiotemporal association node, the system automatically generates a spatiotemporal rule configuration form, allowing the setting of spatiotemporal parameters (such as time window, equipment group relationship). For example, for the chemical plant scenario, it is set that "the gas concentration of device B exceeds the standard within 5 minutes after device A exceeds the temperature." Based on the configuration function of the spatiotemporal association node, a rule chain containing "spatiotemporal association rules" can be constructed, thereby introducing the analysis of cross-device spatiotemporal events in the data analysis process.

[0146] The system provided by the embodiments of the present invention can provide users with a visual configuration interface, facilitating various operations and maintenance. This provides operators with an intuitive and convenient operating experience, helping to simplify the operation and maintenance process, lower the threshold for operation and maintenance, and improve the user experience. At the same time, it can achieve unified management and monitoring of equipment, improving operation and maintenance efficiency.

[0147] In order to better illustrate the system provided by the embodiment of the present invention, based on the systems provided by the above embodiments, the data processing flow of the IoT operation and maintenance system provided by the embodiment of the present invention is exemplified below. Taking the alarm detection of IoT devices as an example, Figure 3 As shown, the data processing flow of the system provided by the embodiment of the present invention mainly includes:

[0148] S301: Add model (resource classification);

[0149] In an embodiment of the present invention, operation and maintenance personnel can add models, i.e., classifications of resources, to the system based on actual operation and maintenance needs. Resources refer to specific device instances that need to be collected, such as a specific server, and models are specific classifications of device instances, such as a certain type of server.

[0150] S302: Add resources;

[0151] In the embodiment of the present invention, operation and maintenance personnel can add specific resources, such as a server with a certain IP address, under a corresponding model in the system according to actual needs.

[0152] S303: Determine whether there is a collection protocol for the resource;

[0153] In an embodiment of the present invention, the system responds to the user's operation of adding resources and determines whether the system is configured with a protocol plug-in or plug-in file corresponding to the communication protocol adopted by the resource to identify whether there is an acquisition protocol for the resource (that is, the communication protocol adopted by the resource). This process can also be implemented by the operation and maintenance personnel themselves by checking the system configuration file.

[0154] S304: Add a custom acquisition protocol;

[0155] In the embodiment of the present invention, if the collection protocol of the current resource does not exist in the system, the operation and maintenance personnel need to add a custom collection protocol, which can be specifically a plug-in file that configures the corresponding protocol.

[0156] S305: protocol reading and parsing;

[0157] In the embodiment of the present invention, the system can read and parse the corresponding protocol information for the plug-in file configured by the operation and maintenance personnel.

[0158] S306: Collection configuration;

[0159] In the embodiment of the present invention, the system may load the protocol plug-in based on the corresponding protocol information, and add the protocol plug-in corresponding to the type of protocol in the collection configuration.

[0160] S307: Collection configuration is issued;

[0161] S308: The gateway performs collection;

[0162] In an embodiment of the present invention, when the gateway (i.e., the data acquisition module) needs to collect data from an IoT device, it can establish a communication connection with the IoT device based on the corresponding protocol plug-in, and collect data from the IoT device based on the established communication connection.

[0163] S309: The rule engine processes the collected data (data filtering, conversion, calculation). If spatiotemporal correlation analysis is required, the spatiotemporal rule operator library is called;

[0164] In this embodiment of the present invention, the collected data can be processed by invoking a rules engine to obtain various evaluation parameters used to assess whether to trigger an alarm. If spatiotemporal correlation analysis is currently required, a preset spatiotemporal rule operator library is invoked to parse the corresponding spatiotemporal correlation rules, and then a cross-device spatiotemporal correlation analysis is performed based on these analysis.

[0165] S310: Determine whether an alarm condition is triggered;

[0166] In the embodiment of the present invention, whether an alarm condition is triggered can be determined based on various evaluation parameters. If spatiotemporal correlation analysis is involved, the alarm determination of a composite event can also be performed based on the relevant information of the spatiotemporal correlation alarm.

[0167] S311: trigger an alarm;

[0168] In the embodiment of the present invention, if an alarm condition is triggered, an alarm prompt is issued.

[0169] S312: Front-end data display.

[0170] In the embodiment of the present invention, the specific results of the alarm detection can be displayed through the front-end interface.

[0171] Next, the data processing flow of the system provided by the embodiment of the present invention will be further illustrated by taking device control as an example. Figure 4 As shown, the data processing flow of the system provided by the embodiment of the present invention mainly includes: the operation and maintenance personnel can pre-configure the service of the model and the scenario linkage configuration in the system, and judge whether the triggering conditions of a rule in the rule engine are met based on the collected business data. When the triggering conditions are met, the rule engine is called to perform business decision analysis to obtain a business decision result that triggers a certain device operation. The business decision result can be transmitted to the gateway through the message bus (Kafka), and the gateway calls the configuration device interface to send the business decision result to the corresponding Internet of Things device, triggering the Internet of Things device to perform the operation.

[0172] In order to better illustrate the system provided by the embodiment of the present invention, based on the system architecture provided by each of the above embodiments, the embodiment of the present invention provides another IoT operation and maintenance system that supports automatic protocol expansion. The schematic diagram of the system architecture can be shown as follows: Figure 5 As shown in the figure, the system features a visual frontend that displays a large data screen and various reporting tools for presenting data during the operation and maintenance process. The frontend also allows for configurations, such as rule chains and rules in the rule engine. Rule chain configuration includes the configuration of spatiotemporal correlation nodes, and rule configuration includes the configuration of spatiotemporal correlation rules, enabling cross-device and cross-spatial correlation analysis. The system can implement various business functions, such as model management, rule management, data collection, operation and maintenance management, system management, and other functions. Model management includes model management, resource management, and module management. Rule management includes management of alarm rules, configuration of alarm templates, scenario linkage, data flow rules, and scenario management. Data collection includes management of system collection capabilities, collection protocols, and collection credentials. Operation and maintenance management includes job management, script management, and task scheduling. System management includes user management, role management, permission management, and operation log management.

[0173] The data processing process of the system provided by the embodiment of the present invention is implemented by various modular functional modules. First, the system is configured with a persistent storage module (equivalent to the data storage module in the previous embodiment) for persistent data storage. This module is configured with a variety of storage engines, such as IOTDB, database, Minio, and Redis. The persistent storage module can store various configuration information entered by the user through the visual front-end, and can also store various data during the operation and maintenance process. When the front-end needs to display data, it can read data from this module. For example, the user can enter basic configuration information of the gateway, such as network parameters, protocol plug-in path, and rule configuration key content, through the visual front-end. After the configuration file is read and parsed by the system, the relevant information is then properly stored in the data storage module, providing basic support for subsequent operation. The persistent storage module also integrates a quantized storage unit, which can migrate data between storage engines based on a value decay model.

[0174] The system's message bus distributes data that needs to be transmitted between modules in the system, employing a topic-based intelligent routing mechanism. The gateway (i.e., the data acquisition module in the aforementioned embodiment) can obtain configuration files for protocol plug-ins via the message bus or by directly accessing the persistent storage module. Based on the configuration protocol, it loads protocol plug-ins for various protocols, including, for example, TCP (Transmission Control Protocol), HTTP (Hypertext Transfer Protocol), MQTT (Message Queuing Telemetry Transport), MODBUS (a serial communication protocol), SNMP (Simple Network Management Protocol), and JDBC (Java Database Connectivity).

[0175] When the gateway starts, it can load various protocol plug-ins based on the configuration information. When the gateway needs to collect data from IoT devices, it can determine the protocol type used by the device through the handshake information sent by the device or pre-configured information, and call the protocol plug-in corresponding to this protocol type to establish a communication connection. In this way, data is collected from the IoT device and the business data of the IoT device is obtained. The business data of the IoT device can be sent to the module for data parsing, processing and integration (i.e., the rule engine module in the above embodiment) via the message bus. This module can analyze and process the data based on the rule chain and rule engine to obtain business decision results. The system can determine the actions to be triggered based on the business decision results, such as whether to trigger an alarm. The processed data is converted to the specified format by the data output module according to the configuration information and pushed to the corresponding storage device or server, ensuring the effective storage and application of the data and completing the entire data collection and processing process.

[0176] When loading a new version of the protocol plug-in, you can use hot switching to switch between the old and new versions of the protocol plug-in. The schematic diagram of the protocol plug-in hot switching process can be shown as follows: Figure 6As shown, the process mainly includes: after starting the hot update (i.e. hot switch), create a version sandbox to create an isolated environment for the new version. In the version sandbox, load the updated new protocol plug-in. Perform version compatibility check on the old and new versions of the protocol plug-in. If compatible, directly register it to the buffer registry. If not compatible, it is necessary to inject a protocol bridge to solve the version incompatibility problem. Specifically, an AST syntax tree converter can be built for protocol conversion. When the versions are compatible, register the new protocol to the buffer registry B. Start session mirroring to start the session mirroring operation. Copy the current connection state and perform session migration, including migrating TCP / UDP sessions, Modbus session IDs, and SSL contexts. Then perform traffic switching, switch the traffic to the new version, close the plug-in instance of the old version, clean up and release the sandbox resources, and the entire hot update process ends.

[0177] Overall, the hot replacement process includes three stages of migration: sandbox creation stage: the protocol manager creates a version-isolated environment to load the new plug-in, and resolves version compatibility issues through the protocol bridge; connection migration stage: session mirroring technology replicates the communication status (including key parameters such as the Modbus session ID) to ensure lossless connection transfer; traffic switching stage: the double-buffered registry completes route switching within a millisecond window, and the old plug-in instance is safely uninstalled.

[0178] In another embodiment, an IoT operation and maintenance method supporting automatic protocol expansion is shown. Figure 7 The method includes:

[0179] S701: Establish a communication connection between the target protocol plug-in and the target IoT device through the data acquisition module.

[0180] Among them, the target protocol plug-in is called from the plug-in protocol library according to the target protocol type corresponding to the target IoT device.

[0181] As you can see, establishing a communication connection with the target IoT device through the data acquisition module and the target protocol plug-in effectively enables interoperability between devices. Each protocol plug-in corresponds to a specific communication protocol, ensuring seamless connectivity between different devices and optimizing communication efficiency based on the protocol type. This allows devices to flexibly exchange data in diverse environments and meet diverse needs, improving the system's adaptability and scalability.

[0182] S702: Utilize the data acquisition module to collect data from the target IoT device to obtain business data.

[0183] S703: Using the rule engine module to determine the target rule chain corresponding to the target IoT device from the pre-built rule chains, and based on the target rule chain and the pre-built rule engine, perform data analysis on the pre-processed business data to obtain a business decision result.

[0184] As you can see, the rule engine module determines the rule chain corresponding to the target IoT device from pre-built rule chains and analyzes pre-processed business data based on these rule chains, enabling automated intelligent decision support. This process improves the efficiency and accuracy of data analysis, reduces manual intervention and errors, and enhances system reliability. Flexible management and dynamic selection of rule chains enhance the system's adaptability and scalability, allowing devices to adapt to diverse needs. Furthermore, the rule engine continuously optimizes the decision-making process through intelligent analysis, helping to achieve more efficient and intelligent management of IoT devices.

[0185] S704: Determine the data to be pushed corresponding to the business decision result and the push object corresponding to the data to be pushed through the data output module, and send the data to be pushed to the push object.

[0186] It should be noted that the specific implementation process of steps S701 to S704 is detailed in the embodiment of the present invention. Figures 1 to 6 The contents shown in will not be repeated here.

[0187] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. The systems and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the scheme of this embodiment. A person of ordinary skill in the art can understand and implement it without expending creative effort.

[0188] Professionals may further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the above description has generally described the components and steps of each example according to their functions. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professionals and technicians may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of the present invention.

[0189] The above description of the disclosed embodiments is intended to enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An IoT operation and maintenance system that supports automatic protocol expansion, characterized in that: include: Data acquisition module, data processing module, rule engine module and data output module; The data acquisition module is used to load the protocol plug-in according to the preset configuration file, and the successfully loaded protocol plug-ins form a plug-in protocol library; When data collection is required for a target IoT device, a target protocol type corresponding to the target IoT device is determined; In the plug-in protocol library, determine the target protocol plug-in corresponding to the target protocol type, call the target protocol plug-in, and establish a communication connection with the target Internet of Things device; based on the established communication connection, collect data from the target Internet of Things device to obtain business data corresponding to the target Internet of Things device; The data processing module is used to perform data preprocessing on the service data corresponding to the target IoT device to obtain processed service data; The rule engine module is configured to determine a target rule chain corresponding to the target IoT device from among the pre-built rule chains, and perform data analysis on the processed business data based on the target rule chain and the pre-built rule engine to obtain a business decision result; The data output module is used to determine the data to be pushed corresponding to the business decision result and the push object corresponding to the data to be pushed, and send the data to be pushed to the corresponding push object.

2. The IoT operation and maintenance system supporting automatic protocol expansion according to claim 1, characterized in that: The data acquisition module includes: a configuration file reader, a protocol loader and a protocol manager; The configuration file reader is used to read the configuration file, parse the configuration file, and obtain the protocol plug-in path; The protocol loader is configured to determine whether a plug-in directory exists in the protocol plug-in path. If the plug-in directory exists in the protocol plug-in path, the protocol loader traverses the plug-in files of each protocol type in the plug-in directory, performs validity verification on each plug-in file of the protocol type, and if the plug-in file passes the validity verification, loads the protocol plug-in corresponding to the plug-in file into the memory based on a preset loading algorithm, so that the protocol plug-in initiates a registration request to the protocol manager. The protocol manager is used to, when receiving a registration request initiated by a protocol plug-in loaded in the memory, determine the registration information corresponding to the protocol plug-in, and perform legitimacy verification on the protocol plug-in based on the registration information; if the protocol plug-in passes the legitimacy verification, determine the plug-in information corresponding to the protocol plug-in, update the preset protocol-plug-in mapping table based on the plug-in information corresponding to the protocol plug-in, load the protocol plug-in into a preset version sandbox, perform compatibility verification on the protocol plug-in loaded into the version sandbox, and if the protocol plug-in loaded into the version sandbox passes the compatibility verification, perform a plug-in hot switching operation.

3. The IoT operation and maintenance system supporting automatic protocol expansion according to claim 2, characterized in that: The protocol loader is further configured to record a path error log when the plug-in directory does not exist in the protocol plug-in path; The protocol loader is further configured to record invalid plug-in information corresponding to the plug-in file if the plug-in file currently undergoing validity verification fails the validity verification; The protocol manager is further configured to refuse registration of a protocol plug-in currently undergoing validity verification if the protocol plug-in fails the validity verification, and record registration error information corresponding to the protocol plug-in; The protocol manager is further used to, after determining the target protocol type, determine the plug-in information that matches the target protocol type among the various plug-in information recorded in the protocol-plug-in mapping table, and use the protocol plug-in corresponding to the plug-in information that matches the target protocol type as the target protocol plug-in.

4. The IoT operation and maintenance system supporting automatic protocol expansion according to claim 1, characterized in that: The data processing module includes: a data filter and a data converter; The data filter is used to filter the business data corresponding to the target IoT device according to a preset filtering condition to obtain filtered business data; The data converter is used to perform data format conversion on the filtered business data according to a preset format conversion rule to obtain converted business data, and use the converted business data as the processed business data.

5. The IoT operation and maintenance system supporting automatic protocol expansion according to claim 1, characterized in that: The rule engine module includes: a rule parser, a rule execution engine and a rule storage module; The rule storage module is used to persistently store the various data analysis rules set by the user; The rule parser is used to parse each of the data analysis rules to obtain a parsed rule corresponding to each of the data analysis rules; The rule execution engine is used to determine the matching rules corresponding to the input data in each of the parsed rules when the rule engine receives the input data to be analyzed, apply the matching rules to perform data analysis on the input data, and call the pre-built spatiotemporal rule operator library to perform spatiotemporal correlation analysis when the preset spatiotemporal rule node is triggered.

6. The IoT operation and maintenance system supporting automatic protocol expansion according to claim 1, characterized in that: The data output module includes: a format converter and a data transmitter; The format converter is used to determine the transmission data format corresponding to the push object, perform data format conversion on the data to be pushed according to the transmission data format, and obtain converted data corresponding to the data to be pushed; The data transmitter is configured to transmit the converted data corresponding to the data to be pushed to the push object, so as to send the data to be pushed to the push object.

7. The IoT operation and maintenance system supporting automatic protocol expansion according to claim 1, characterized in that: Also includes: Data storage module; The data storage module includes a protocol converter, a dynamic memory and a resource manager; the resource manager is configured with a quantized storage unit; The protocol converter is configured to, when target data needs to be stored, perform metadata analysis on the target data to obtain a data type corresponding to the target data, perform data format conversion on the target data based on the data type corresponding to the target data and a preset storage data type, convert the target data into data of the storage data type, and use the converted data as data to be stored; The dynamic memory is used to determine a target storage engine corresponding to the data to be stored among a plurality of preset storage engines, and store the data to be stored in the target storage engine based on a preset load balancing strategy and a hierarchical storage strategy; The resource manager is configured to perform fault detection on each of the storage engines and, when a fault is detected, perform storage switching according to a preset storage switching policy; The quantized storage unit is configured to perform data value analysis on each of the storage engines based on a preset value decay model, and to perform data migration on each of the storage engines based on the data value analysis results; The resource manager is further configured to perform cache cleanup according to a preset cache management mechanism.

8. The IoT operation and maintenance system supporting automatic protocol expansion according to claim 1, characterized in that: Also includes: message bus layer; The message bus layer is used to convert the data format of the data to be distributed when data distribution is required to be performed on the data to be distributed in the system, so as to obtain the converted data to be distributed; The message bus layer is further used to distribute the converted data to be distributed according to a preset routing mechanism and a dynamically adjusted distribution strategy; the routing mechanism is a topic-based intelligent routing mechanism.

9. The IoT operation and maintenance system supporting automatic protocol expansion according to claim 1, characterized in that: Also includes: Front-end configuration module; The front-end configuration module is used to display the front-end configuration interface to the user, so that the user can perform operation and maintenance management through the front-end configuration interface; The front-end configuration module is further configured to display a rule chain arrangement interface to the user, so that the user can arrange the rule chain through the rule chain arrangement interface to construct a rule chain; The rule chain orchestration interface is configured with an orchestration function for time-space related nodes.

10. An IoT operation and maintenance method supporting automatic protocol expansion, characterized in that: Applied to the IoT operation and maintenance system according to any one of claims 1 to 9 above, the method comprises: Establishing a communication connection between the target protocol plug-in and the target IoT device through the data acquisition module; the target protocol plug-in is obtained by calling the target protocol type corresponding to the target IoT device from the plug-in protocol library; Utilize the data acquisition module to collect data from the target IoT device to obtain business data; Using a rule engine module to determine a target rule chain corresponding to the target IoT device from pre-built rule chains, and performing data analysis on the pre-processed business data based on the target rule chain and the pre-built rule engine to obtain a business decision result; The data to be pushed corresponding to the business decision result and the push object corresponding to the data to be pushed are determined through a data output module, and the data to be pushed is sent to the push object.

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