A multi-type unmanned equipment unified operation management monitoring platform and a supervision method

Abstract

The application discloses a kind of unified operation management monitoring platform and supervision method of multiple types unmanned equipment, belong to unmanned system supervision field.The platform includes: standardization interface adaptation layer, for defining uniform equipment access specification and providing protocol adaptation plug-in;Data acquisition and analysis layer, for obtaining the full-dimensional operation data of unmanned equipment;Core supervision processing layer, for the global monitoring of unmanned equipment, abnormal identification and risk level determination;Multi-level linkage disposal layer, for automatically pushing abnormal information to the corresponding equipment of manufacturer after-sales system and the business system of relevant government departments;Supervision display and data storage layer, for providing visualized supervision interface and data retention.The application realizes the global unified supervision of multiple manufacturers, multiple types unmanned equipment, abnormal rapid disposal, cross-department efficient linkage and whole-process law enforcement evidence, avoids unmanned equipment operation abnormality to influence social public order and public safety.

Description

Technical Field

[0001] This invention belongs to the field of unmanned system supervision. Specifically, this invention relates to a unified operation management and monitoring platform and supervision method for multiple types of unmanned equipment. Background Technology

[0002] Currently, the management of unmanned equipment mainly falls into two categories of technical solutions: one is the private operation and maintenance monitoring platform independently developed by each equipment manufacturer. This type of platform can only realize basic positioning, operation status monitoring and fault reporting for its own brand and single type of unmanned equipment, and adopts the manufacturer's custom private communication protocol and data format; the other is a localized supervision system for a single industry, such as a drone flight control supervision platform. This type of system is designed only for a single type of unmanned equipment in a specific field, and can only realize limited supervision of equipment within that field, without the ability to access equipment across different types and manufacturers.

[0003] When supervising unmanned equipment within their jurisdiction, management departments such as traffic management departments and public security departments can only obtain scattered equipment information through methods such as equipment manufacturers' reports and manual on-site verification. They cannot achieve full-area, real-time, and refined supervision of all unmanned equipment within their jurisdiction through a unified entry point, nor can they obtain key regulatory data such as equipment operating parameters, fault status, and violations in a timely manner.

[0004] Therefore, this invention proposes a unified operation management and monitoring platform and supervision method for multiple types of unmanned equipment. Summary of the Invention

[0005] This invention aims to overcome the shortcomings of existing technologies and proposes a unified operation management and monitoring platform and supervision method for multiple types of unmanned equipment. The goal is to address the following issues in the supervision of multiple types of unmanned equipment in related technologies: the inability to uniformly access heterogeneous equipment, the lack of proactive intervention capabilities at the monitoring end, the lag in cross-departmental collaborative handling of faults / accidents, insufficient data collection dimensions, and the lack of control over sensitive areas. This invention achieves unified supervision of multiple manufacturers and types of unmanned equipment across the entire domain, rapid handling of anomalies, efficient cross-departmental collaboration, and full-process law enforcement and evidence collection, thereby preventing abnormal operation of unmanned equipment from affecting public order and public safety.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A unified operation management and monitoring platform for multiple types of unmanned equipment, the platform comprising, in sequence, a standardized interface adaptation layer, a data acquisition and parsing layer, a core monitoring and processing layer, a multi-level linkage and response layer, and a monitoring display and data storage layer, wherein:

[0008] The standardized interface adaptation layer is used to define a unified equipment access specification and provide protocol adaptation plugins to achieve standardized access for multiple types of unmanned equipment.

[0009] The data acquisition and parsing layer is used to acquire full-dimensional operational data of unmanned equipment through the standardized interface adaptation layer, and to clean, convert, and standardize the acquired data.

[0010] The core monitoring and processing layer is used to perform full-domain monitoring, anomaly identification, and risk level determination of unmanned equipment based on the data processed by the data acquisition and analysis layer.

[0011] The multi-level linkage and handling layer is used to receive the anomaly identification results from the core supervision and processing layer, automatically push the anomaly information to the corresponding equipment manufacturer's after-sales system according to the anomaly type and risk level, and link with the business systems of relevant government departments to generate standardized handling work orders and track the handling progress.

[0012] The regulatory display and data storage layer is used to provide a visual regulatory interface and to retain the platform's full-process work data for a long time.

[0013] Preferably, the core monitoring and processing layer includes a full-domain monitoring module, an electronic fence module, an anomaly identification module, a remote control module, and an access control module. The full-domain monitoring module is used to visualize the real-time location of all connected equipment. The electronic fence module is used for custom configuration of no-entry / no-fly zones in sensitive areas and automatically triggers an anomaly alarm when equipment exceeds the fence boundary. The anomaly identification module is used to identify whether any connected equipment is abnormal in real time based on preset anomaly identification rules and to determine the risk level. The remote control module is used to issue control commands to abnormal equipment to achieve remote intervention. The access control module is used to hierarchically manage the regulatory operation permissions of different management departments.

[0014] Preferably, in the anomaly identification module, the preset anomaly identification rules include:

[0015] Energy status anomaly identification: Anomaly identification is performed based on the energy parameters of the unmanned equipment, including battery power, fuel balance, range, energy consumption rate, and energy replenishment status;

[0016] Spatial location anomaly identification: Anomaly identification is performed based on the position parameters of unmanned equipment and preset spatial constraints; the position parameters include latitude and longitude, elevation, heading, trajectory, speed, and acceleration, and the spatial constraints include electronic fences, no-entry zones, restricted zones, predetermined routes, and road rules;

[0017] Equipment status anomaly identification: Anomaly identification is performed based on the unmanned equipment's own status parameters, including the unmanned equipment's operating status code, fault code, sensor data, communication status, temperature, and attitude.

[0018] Anomaly identification for safety incidents: Anomaly identification is performed based on safety incident parameters of unmanned equipment, including collision signals, rapid deceleration, video analysis results, and audio analysis results of the unmanned equipment;

[0019] Composite anomaly identification: Anomaly identification is performed based on the correlation analysis of at least two of the above-mentioned parameters.

[0020] Preferably, the visual regulatory interface provided by the regulatory display and data storage layer includes a PC-based regulatory screen, a mobile regulatory app, and a command center visual terminal.

[0021] This invention also provides a monitoring method for a unified operation management and monitoring platform for multiple types of unmanned equipment. Using the aforementioned unified operation management and monitoring platform for multiple types of unmanned equipment, the method includes the following steps:

[0022] Step S1: Authentication for access to multiple types of unmanned equipment;

[0023] Step S2: Collect data from all dimensions of the connected unmanned equipment;

[0024] Step S3: Based on the collected data from all dimensions, perform full-domain monitoring, anomaly identification, and risk level determination on the connected unmanned equipment; if there are no anomalies, return to step S2; otherwise, continue to the next step.

[0025] Step S4: After identifying the anomaly, link the corresponding equipment manufacturer's after-sales system and the relevant government department's business system to push the anomaly information and perform remote intervention.

[0026] Step S5: After receiving the abnormal information, the manufacturer's after-sales system and relevant government departments will carry out on-site handling and record the work data of the entire abnormal handling process, including equipment operation data, abnormal alarm data, linkage handling data, handling result data, real-time video stream and screenshots.

[0027] Preferably, step S1 includes:

[0028] Step S101: The unmanned equipment initiates an access request to the platform's standardized interface adaptation layer through its own communication module. The access request includes the equipment's unique ID, equipment type, and manufacturer code.

[0029] Step S102: The standardized interface adaptation layer performs identity authentication on the equipment information in the access request, and verifies whether the equipment has completed the filing. Unfiled equipment is rejected from access, and filed equipment proceeds to the next step.

[0030] Step S103: The standardized interface adaptation layer automatically matches the corresponding protocol adaptation plugin according to the equipment's manufacturer and type, completing the adaptation of the private protocol and the platform's unified protocol.

[0031] Step S104: After the protocol adaptation is completed, the platform registers the equipment, generates a unique platform access identifier, and establishes an encrypted data transmission link.

[0032] Step S105: The equipment uploads basic operational data to the platform through a standardized data transmission link to complete the access process.

[0033] Preferably, step S2 includes:

[0034] Step S201: The data acquisition and parsing layer's acquisition nodes receive raw operational data uploaded by the unmanned equipment in real time;

[0035] Step S202: The data acquisition and parsing layer calls the parsing server to clean the raw operating data, remove invalid and duplicate data caused by network fluctuations, mark missing data caused by equipment failure and remind the manufacturer to investigate;

[0036] Step S203: The parsing server performs format conversion and standardization processing on the cleaned raw operating data according to the platform's unified encoding rules and data format to ensure that the data formats of different manufacturers and different types of equipment are consistent;

[0037] Step S204: The standardized, multi-dimensional data is uploaded to the core regulatory processing layer in real time through the platform's internal links.

[0038] Preferably, step S3 includes:

[0039] Step S301: The full-domain monitoring module of the core supervision and processing layer marks the standardized equipment data on the electronic map in real time, realizing visualized full-domain monitoring of all connected equipment. Supervisors can view the real-time status of the equipment through the supervision display terminal.

[0040] Step S302: The electronic fence module verifies the real-time location information of the equipment in real time, determines whether the equipment has entered the preset no-entry / no-fly fence area, and automatically triggers an abnormal alarm when the equipment enters the preset no-entry / no-fly fence area.

[0041] Step S303: The anomaly identification module matches the real-time collected equipment operation data with the preset anomaly identification rules in real time to identify anomalies and determine the risk level of the equipment.

[0042] Step S304: If it is determined that there is no abnormality in the equipment, return to step S2 and continue to collect data in all dimensions; if it is determined that there is an abnormality in the equipment, push the abnormality information to the multi-level linkage and handling layer, and issue an abnormality alarm through the visual monitoring interface of the monitoring display and data storage layer.

[0043] Preferably, step S4 includes:

[0044] Step S401: After receiving the abnormal information, the linkage server of the multi-level linkage handling layer identifies the abnormal type and risk level;

[0045] Step S402: The linkage server automatically pushes the anomaly information to the corresponding equipment manufacturer's after-sales system and the relevant government department's business system through the API interface according to the anomaly type and risk level.

[0046] Step S403: The remote control module of the core monitoring and processing layer issues the corresponding remote intervention command to the abnormal equipment according to the anomaly type;

[0047] Step S404: The remote control module receives the remote intervention command execution receipt from the equipment. If the command is executed successfully, the module monitors the status changes of the equipment in real time. If the command fails to execute, the module immediately feeds back the result to the supervisor, who then takes manual intervention measures.

[0048] Preferably, step S5 includes:

[0049] Step S501: After receiving the abnormal information, the manufacturer's after-sales system and relevant government departments will carry out on-site handling work;

[0050] Step S502: After the disposal is completed, the manufacturer and government departments will feed back the disposal results to the platform's multi-level linkage disposal layer;

[0051] Step S503: The multi-level linkage processing layer's work order management system completes the closed-loop processing of the work order based on the feedback processing results, and marks the work order status as completed.

[0052] Step S504: The monitoring, display and data storage layer encrypts and stores the work data of the entire process of handling this anomaly and generates a data traceability ledger.

[0053] The technical effects of this invention are as follows:

[0054] 1. It has achieved unified access and full-domain supervision of multi-vendor and multi-type heterogeneous unmanned equipment. Through the standardized interface adaptation layer, it breaks down the protocol barriers and data silos of different manufacturers and industries. Management departments can grasp the core information of all unmanned equipment in the jurisdiction through a single platform, completely eliminate regulatory blind spots, and improve the comprehensiveness and efficiency of unmanned equipment supervision.

[0055] 2. It empowers the regulatory authorities with the ability to proactively intervene and remotely take over, which is different from the passive monitoring mode of existing technologies. When unmanned equipment malfunctions, the management department can promptly issue control commands to guide, intervene, or even take over, effectively preventing traffic congestion, public safety hazards, and other problems caused by abnormal equipment, and ensuring social order.

[0056] 3. A multi-level linkage and response mechanism involving manufacturers and multiple government departments has been established, which enables automated and precise linkage based on the type of anomaly and the level of urgency. This significantly shortens the emergency response time for malfunctions / accidents / violations, improves the efficiency of response, and realizes closed-loop management of anomaly handling for unmanned equipment.

[0057] 4. Collect full-dimensional operational data of unmanned equipment to provide comprehensive and accurate data support for regulatory decision-making, law enforcement evidence collection, and emergency rescue. Through real-time video streams, operating trajectories, fault codes, and other data, the cause of problems can be quickly located, providing objective and traceable evidence for law enforcement work and improving the precision and scientific nature of supervision.

[0058] 5. It realizes automated and intelligent management and control of sensitive areas. Through the custom configuration of the electronic fence module, it enables 24-hour real-time monitoring of sensitive areas, and provides second-level early warning, automatic evidence collection and rapid handling of illegal boundary crossings, effectively preventing security risks caused by unmanned equipment entering sensitive areas;

[0059] 6. The platform architecture has good scalability and compatibility, and can flexibly connect to new types of unmanned equipment according to the development of unmanned equipment technology without making major modifications to the core architecture of the platform, reducing the platform's upgrade and maintenance costs. It is suitable for the unmanned equipment supervision work of traffic management, public security, emergency management and other departments at all levels. Attached Figure Description

[0060] Figure 1 This is a schematic diagram of an architecture for a unified operation management and monitoring platform for multiple types of unmanned equipment, provided in an embodiment of the present invention.

[0061] Figure 2 A flowchart illustrating a regulatory method for a unified operation management and monitoring platform for multiple types of unmanned equipment, provided as an embodiment of the present invention. Detailed Implementation

[0062] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. This is to help those skilled in the art to have a more complete, accurate, and in-depth understanding of the inventive concept and technical solutions of the present invention, and to facilitate its implementation. It should be noted that the terms "first," "second," etc., used in this application are only for the convenience of describing the technical solutions and to distinguish components; the corresponding component configurations may be the same or different, and are not intended to limit the scope of this application. To make the technical solutions of the present invention clearer, the present invention will be explained and illustrated through the following embodiments.

[0063] The core of this invention lies in achieving unified access to heterogeneous unmanned equipment through standardized interfaces, and combining full-dimensional data collection, intelligent anomaly identification, remote intervention control, and multi-level linkage to realize full-domain, real-time, and refined supervision of unmanned equipment.

[0064] Therefore, this embodiment provides a unified operation management and monitoring platform for multiple types of unmanned equipment. The platform adopts a cloud-based distributed architecture, supporting private deployment and hybrid cloud deployment by management departments at all levels. Figure 1 As shown, the platform includes a standardized interface adaptation layer, a data acquisition and parsing layer, a core regulatory processing layer, a multi-level linkage and handling layer, and a regulatory display and data storage layer connected in sequence, wherein:

[0065] The standardized interface adaptation layer is used to define a unified equipment access specification and provide protocol adaptation plugins to achieve standardized access for multiple types of unmanned equipment.

[0066] The data acquisition and parsing layer is used to acquire full-dimensional operational data of unmanned equipment through the standardized interface adaptation layer, and to clean, convert, and standardize the acquired data.

[0067] The core monitoring and processing layer is used to perform full-domain monitoring, anomaly identification, and risk level determination of unmanned equipment based on the data processed by the data acquisition and analysis layer.

[0068] The multi-level linkage and handling layer is used to receive the anomaly identification results from the core regulatory processing layer, automatically push the anomaly information to the corresponding equipment manufacturer's after-sales system according to the anomaly type and risk level, and link with the business systems of relevant government departments to generate standardized handling work orders and track the handling progress.

[0069] The regulatory display and data storage layer is used to provide a visual regulatory interface and to retain the platform's full-process work data for a long time.

[0070] Specifically, the standardized interface adaptation layer is based on mainstream communication protocols such as MQTT, HTTP / HTTPS, TCP / UDP, and WebSocket, defining unified equipment access specifications, including equipment identification fields (such as equipment SN code, IMEI code), equipment type codes (such as 001 for unmanned vehicles, 002 for drones, and 003 for unmanned robots), manufacturer information codes, data transmission format (using JSON format), status reporting cycle (default 1 second / time, adjustable according to equipment type), and remote control command sets (such as 01 for deceleration / hovering, 02 for guided departure / return, and 03 for forced takeover / forced landing). It also provides protocol adaptation plugins to achieve compatibility and conversion with various manufacturers' proprietary protocols, ensuring that various types of equipment, such as unmanned vehicles, drones, unmanned delivery robots, unmanned inspection robots, and unmanned law enforcement equipment, can achieve standardized access through this layer.

[0071] In a preferred embodiment of the present invention, in addition to using a preset protocol adapter plugin, the standardized interface adaptation layer can also use dynamic protocol parsing technology. By parsing the vendor's private protocols in real time, standardized access of heterogeneous equipment can be achieved without the need to develop adapter plugins in advance, thereby further improving the platform's compatibility and access efficiency.

[0072] The data acquisition and parsing layer is equipped with data acquisition nodes and data parsing servers. The data acquisition nodes receive raw data uploaded by unmanned equipment through a standardized interface adaptation layer. The parsing server cleans the raw data, removes invalid data, fills in missing data, and performs format conversion on heterogeneous data. It converts the status codes and fault codes customized by various manufacturers into the platform's unified encoding rules. Finally, the standardized full-dimensional data is uploaded to the core monitoring and processing layer. The specific data collected includes: equipment unique ID, equipment type, manufacturer name and code, real-time latitude and longitude positioning information, operating status (normal / fault / shutdown / low battery), real-time speed (unit: km / h), remaining battery power (percentage), real-time video stream (supports local and global views, resolution ≥720P), fault codes, and historical operating trajectory (recorded by timestamp).

[0073] The core monitoring and processing layer, as the core processing unit of the platform, is deployed with multiple cloud servers to achieve distributed computing. In this embodiment, the core monitoring and processing layer has several functional modules, including a global monitoring module, an electronic fence module, an anomaly detection module, a remote control module, and a permissions management module.

[0074] The overall monitoring module is used to visualize the real-time location of all connected equipment. In this embodiment, the overall monitoring module builds an overall monitoring interface based on the electronic map API, marking the real-time location information of all connected equipment on the electronic map, and distinguishing equipment type and operating status through different colored icons (green represents normal, yellow represents low battery warning, and red represents fault / violation / accident).

[0075] The electronic fence module is used for custom configuration of no-entry / no-fly zones in sensitive areas and automatically triggers an alarm when equipment exceeds the fence boundary. In this embodiment, the electronic fence module allows management to customize and draw no-entry / no-fly zones through a visual interface, setting the fence name, type, and control level. An alarm is automatically triggered when equipment exceeds the fence boundary.

[0076] The remote control module is used to issue control commands to malfunctioning equipment to enable remote intervention. In this embodiment, the remote control module supports issuing point-to-point control commands to the equipment. The commands are transmitted to the control unit of the unmanned equipment via an encrypted link, enabling operations such as deceleration, hovering, guiding departure / return, and forced takeover of the equipment. Simultaneously, it receives command execution acknowledgments from the equipment to confirm the command execution results.

[0077] In a preferred embodiment of the present invention, in addition to point-to-point command issuance, the remote control module can also adopt a regional control method to issue unified control commands to all abnormal equipment in a specific area. This is suitable for batch equipment management in scenarios such as large-scale events and emergencies, thereby improving supervision efficiency.

[0078] The access control module is used to hierarchically manage the regulatory operation permissions of different management departments. In this embodiment, the access control module sets hierarchical permissions for regulatory personnel from different departments such as traffic management, public security, emergency medical services, fire protection, and urban management based on their responsibilities. For example, ordinary regulatory personnel only have the permission to view data and receive alarms, while senior regulatory personnel have the permission to issue remote commands, thereby realizing access control for regulatory operations.

[0079] The anomaly detection module is used to identify whether any anomalies exist in all connected equipment in real time based on preset anomaly detection rules, and to determine the risk level. In this embodiment, the anomaly detection module performs parallel detection on the standardized data accessed in real time based on preset multi-dimensional anomaly detection rules, identifies various abnormal states of unmanned equipment, and classifies the risk level according to the anomaly type and severity, providing a trigger basis for subsequent multi-level linkage response.

[0080] In this embodiment, the preset anomaly identification rules are mainly divided into the following five categories: energy status anomaly identification, spatial location anomaly identification, equipment status anomaly identification, security event anomaly identification, and composite anomaly identification.

[0081] Energy status anomaly identification: Anomaly identification is performed based on the energy parameters of the unmanned equipment. These energy parameters include battery level, remaining fuel, driving range, energy consumption rate, and energy replenishment status. For example:

[0082] When the energy parameter is lower than the first preset threshold, it is identified as a low energy warning;

[0083] When the energy parameter is lower than the second preset threshold (lower than the first threshold), it is identified as a severe low energy alarm;

[0084] When energy parameters change abnormally (such as a sudden drop or no change for a long time), it is identified as an energy system fault.

[0085] Spatial location anomaly identification: Anomaly identification is performed based on the location parameters of the unmanned equipment and preset spatial constraints; the location parameters include latitude and longitude, elevation, heading, trajectory, speed, and acceleration, and the spatial constraints include electronic fences, no-entry zones, restricted zones, predetermined routes, and road rules, for example:

[0086] When the equipment enters a pre-defined restricted area, it is identified as an intrusion into a restricted area;

[0087] When the equipment is about to enter a preset sensitive area, it is identified as an intrusion warning;

[0088] When the equipment trajectory deviates from the predetermined route by more than a preset deviation threshold, it is identified as a deviation from the route.

[0089] Equipment status anomaly identification: Anomaly identification is performed based on the unmanned equipment's own status parameters, including the unmanned equipment's operating status code, fault code, sensor data, communication status, temperature, and attitude. For example:

[0090] When the status code reported by the equipment belongs to a preset set of abnormal statuses, it is identified as the corresponding abnormality;

[0091] When the fault code reported by the equipment falls within the preset fault code mapping range, it is identified as an equipment fault.

[0092] When equipment fails to report data for more than a preset period of time, it is identified as out of contact;

[0093] When the sensor data of the equipment shows a preset abnormal change pattern, it is identified as a sensor malfunction;

[0094] When the temperature of the equipment exceeds the preset temperature threshold, it is identified as a temperature anomaly;

[0095] When the equipment's attitude parameters exceed the preset attitude threshold, it is identified as an attitude anomaly.

[0096] Anomaly identification for safety incidents: Anomaly identification is performed based on safety incident parameters of unmanned equipment. These parameters include collision signals, rapid deceleration, video analysis results, and audio analysis results of the unmanned equipment. Examples include:

[0097] When a collision signal is detected and accompanied by a sudden change in speed, it is identified as a suspected collision incident;

[0098] When the status code reported by the equipment is an accident status, it is identified as a traffic accident;

[0099] When video analytics identifies pre-defined accident scenario features, it is recognized as a safety event.

[0100] When fire-related characteristic parameters are detected, it is identified as a fire risk.

[0101] Composite anomaly identification: Anomaly identification is performed based on the correlation analysis of at least two of the above-mentioned parameters, for example:

[0102] When the same equipment triggers multiple related anomalies within a preset time window, the risk level is upgraded.

[0103] When multiple devices of the same brand trigger the same type of anomaly in the same area, it is identified as a systemic anomaly.

[0104] When an abnormal event is accompanied by specific external conditions (such as weather, time of day, major events, etc.), the risk level is dynamically adjusted.

[0105] In this embodiment, the identified abnormal events are divided into at least three risk levels, with different handling strategies corresponding to different levels. An example is shown in Table 1.

[0106] General level If it does not affect public safety, the company can handle it itself. Low battery warning, slight sensor drift Log the information and notify the company's after-sales service. Emergency Level This may affect public safety and requires attention from regulatory authorities. Breakdown (non-main route), deviation from the route Notify the company of after-sales service and send a copy to the relevant regulatory authorities. Limited Express Public safety has been or is about to be seriously affected, requiring urgent intervention. Entering a restricted area, traffic accident, loss of control Immediately initiate multi-departmental coordination, and take over the operation if necessary.

[0107] Table 1

[0108] In a preferred embodiment of the present invention, in addition to using a preset rule matching method, the anomaly identification module can also introduce a machine learning algorithm. By training a large amount of unmanned equipment operation data and anomaly data, an anomaly identification model can be constructed to achieve intelligent prediction and accurate identification of abnormal equipment states, thereby improving the accuracy and foresight of anomaly identification.

[0109] In this embodiment, the multi-level linkage response layer is deployed with a linkage server and a work order management system. The linkage server presets matching rules between anomaly types and linkage objects. For example, it links the public security department and traffic management department for violations and overstepping boundaries, links the 120 emergency center for traffic accidents, the public security department and traffic management department for traffic accidents, and links the manufacturer's after-sales service and the corresponding industry management department for equipment failures. When it receives the anomaly judgment result from the core supervision and processing layer, the linkage server automatically pushes the anomaly information (including equipment information, anomaly type, real-time location, video screenshots, and running trajectory) to the manufacturer's after-sales system and the business system of the corresponding government department through the API interface according to the matching rules. The work order management system automatically generates standardized handling work orders, including work order number, anomaly information, linkage objects, and handling requirements. At the same time, it tracks the handling progress of the manufacturer and government departments and receives feedback on the handling results.

[0110] In a preferred embodiment of the present invention, in addition to using preset matching rules, the multi-level linkage response layer can also introduce an intelligent scheduling algorithm to achieve intelligent matching and scheduling of linkage objects based on factors such as the handling capacity of the linkage objects, the distance to the site, and the workload, thereby further improving the efficiency and rationality of emergency response.

[0111] The monitoring display and data storage layer provides a visual monitoring interface including three display formats: a PC-based monitoring dashboard, a mobile monitoring app, and a command center visualization terminal. Each display terminal enables multi-dimensional filtering and querying of equipment data, real-time video retrieval, historical trajectory playback, abnormal alarm pop-up notifications, and work order tracking. Data storage adopts a combination of time-series database and distributed cloud storage. The time-series database is used to store real-time equipment operation data, ensuring high-speed data read and write. Distributed cloud storage is used to store large-capacity data such as real-time video streams, video screenshots, and work orders. At the same time, all data is encrypted (using the AES-256 encryption algorithm), and operation audit logs are set to record all data access and operation records, ensuring data security and traceability. The data retention period is no less than 3 years to meet the requirements of law enforcement evidence collection.

[0112] In a preferred embodiment of the present invention, in addition to using time-series databases and distributed cloud storage, the regulatory display and data storage layer can also be combined with blockchain technology to store law enforcement evidence-collecting related data on the chain, thereby achieving data immutability, further enhancing the credibility and legal validity of the data, and making it more suitable for law enforcement evidence-collecting scenarios.

[0113] This invention also provides a monitoring method for a unified operation management and monitoring platform for multiple types of unmanned equipment. Using the aforementioned unified operation management and monitoring platform for multiple types of unmanned equipment, such as... Figure 2 As shown, the method includes the following steps.

[0114] Step S1: Multi-type unmanned equipment access authentication. Specifically, step S1 in this embodiment includes:

[0115] Step S101: The unmanned equipment initiates an access request to the platform's standardized interface adaptation layer through its own communication module (such as 4G / 5G, WiFi, satellite communication). The access request includes the equipment's unique ID, equipment type, and manufacturer code.

[0116] Step S102: The standardized interface adaptation layer performs identity authentication on the equipment information in the access request, and verifies whether the equipment has completed the filing. Unfiled equipment is rejected from access, and filed equipment proceeds to the next step.

[0117] Step S103: The standardized interface adaptation layer automatically matches the corresponding protocol adaptation plugin according to the equipment's manufacturer and type, completing the adaptation of the private protocol and the platform's unified protocol.

[0118] Step S104: After the protocol adaptation is completed, the platform registers the equipment, generates a unique platform access identifier, and establishes an encrypted data transmission link.

[0119] Step S105: The equipment uploads basic operational data to the platform through a standardized data transmission link to complete the access process.

[0120] Step S2: Perform full-dimensional data collection on the connected unmanned equipment. Specifically, step S2 in this embodiment includes:

[0121] Step S201: The acquisition nodes of the data acquisition and parsing layer receive raw operational data uploaded by the unmanned equipment in real time. The raw operational data includes information such as the equipment's positioning, status, speed, battery level, video stream, and fault codes.

[0122] Step S202: The data acquisition and parsing layer calls the parsing server to clean the raw operating data, remove invalid and duplicate data caused by network fluctuations, mark missing data caused by equipment failure and remind the manufacturer to investigate;

[0123] Step S203: The parsing server performs format conversion and standardization processing on the cleaned raw operating data according to the platform's unified encoding rules and data format to ensure that the data formats of different manufacturers and different types of equipment are consistent;

[0124] Step S204: The standardized, multi-dimensional data is uploaded to the core regulatory processing layer in real time through the platform's internal links.

[0125] Step S3: Based on the comprehensive data collection, perform full-domain monitoring, anomaly identification, and risk level determination on the accessed unmanned equipment; if no anomalies are found, return to step S2; otherwise, continue to the next step. Specifically, step S3 in this embodiment includes:

[0126] Step S301: The full-domain monitoring module of the core supervision and processing layer marks the standardized equipment data on the electronic map in real time, realizing visualized full-domain monitoring of all connected equipment. Supervisors can view the real-time status of the equipment through the supervision display terminal.

[0127] Step S302: The electronic fence module verifies the real-time location information of the equipment in real time, determines whether the equipment has entered the preset no-entry / no-fly fence area, and automatically triggers an abnormal alarm when the equipment enters the preset no-entry / no-fly fence area.

[0128] Step S303: The anomaly identification module will match the real-time collected equipment operation data with the preset anomaly identification rules in real time to identify equipment anomalies, including the identification of abnormal states such as low power, fault, unauthorized boundary crossing, and accidents.

[0129] Step S304: If it is determined that there is no abnormality in the equipment, return to step S2 and continue to collect data in all dimensions; if it is determined that there is an abnormality in the equipment, push the abnormality information (including equipment ID, abnormality type, real-time location, abnormality occurrence time, and video screenshot) to the multi-level linkage and handling layer, and issue an abnormality alarm through the visual monitoring interface of the monitoring display and data storage layer.

[0130] Step S4: After identifying the anomaly, the system will be linked with the manufacturer's after-sales service system and the relevant government department's business system to push the anomaly information and perform remote intervention. Specifically, step S4 in this embodiment includes:

[0131] Step S401: After receiving the abnormal information, the linkage server of the multi-level linkage handling layer identifies the abnormal type and risk level;

[0132] Step S402: Based on the anomaly type and risk level, the linkage server automatically pushes the anomaly information to the corresponding equipment manufacturer's after-sales system and the relevant government department's business system via API interface. Among them, for urgent anomalies, multiple push methods are used, including pop-up windows, SMS, and telephone, to ensure that the linked parties receive the information in a timely manner.

[0133] Step S403: The remote control module of the core monitoring and processing layer issues corresponding remote intervention commands to the abnormal equipment according to the anomaly type. For example, it issues a command to "guide to the nearest safe area to dock / land" to the low-battery equipment, a command to "immediately leave / return" to the equipment that has violated the boundary, and a command to force takeover / forced landing to the equipment that cannot execute the command normally.

[0134] Step S404: The remote control module receives the remote intervention command execution receipt from the equipment. If the command is executed successfully, the module monitors the status changes of the equipment in real time. If the command fails to execute, the module immediately feeds back the result to the supervisor, who then takes manual intervention measures.

[0135] Step S5: After receiving the abnormal information, the manufacturer's after-sales system and relevant government departments conduct on-site handling and record the entire process data of the abnormal handling, including equipment operation data, abnormal alarm data, coordinated handling data, handling result data, real-time video stream, and screenshots. Specifically, step S5 in this embodiment includes:

[0136] Step S501: After receiving the abnormal information, the manufacturer's after-sales system and relevant government departments carry out on-site handling work, such as the manufacturer arranging maintenance personnel to go to the site to repair the faulty equipment, the emergency department going to the accident site to carry out rescue, and the public security department going to the illegal site to enforce the law;

[0137] Step S502: After the disposal is completed, the manufacturer and government departments will feed back the disposal results (including disposal time, disposal measures, disposal results, on-site photos / videos) to the platform's multi-level linkage disposal layer;

[0138] Step S503: The multi-level linkage processing layer's work order management system completes the closed-loop processing of the work order based on the feedback processing results, and marks the work order status as completed.

[0139] Step S504: The regulatory display and data storage layer encrypts and stores all the work data of this anomaly handling process and generates a data traceability ledger to facilitate subsequent law enforcement evidence collection and data analysis.

[0140] To facilitate understanding, the embodiments of the present invention are further explained in conjunction with the following application scenarios.

[0141] Application Scenario 1: Monitoring and handling of unmanned vehicles entering military-controlled areas:

[0142] The platform's electronic fence module has been pre-set by the public security department as a no-entry fence for military management areas, and the control level is set to extremely urgent.

[0143] A certain brand of unmanned vehicle entered a military-controlled area due to a positioning system malfunction. The platform's anomaly detection module immediately determined it to be an "illegal boundary crossing" emergency level anomaly through real-time positioning verification, triggering a red alarm.

[0144] According to the matching rules, the multi-level linkage and handling layer immediately pushes the abnormal information (including vehicle ID, manufacturer information, real-time location, and video screenshots) to the vehicle manufacturer's after-sales system, and coordinates with the public security department and traffic management department to push the information through pop-up windows, SMS, and telephone.

[0145] The remote control module of the core monitoring and processing layer issued a command to the unmanned vehicle to "immediately force a reduction in speed and guide it to leave the restricted area." The vehicle control unit received and executed the command, and began to slowly leave the military-controlled area.

[0146] Based on the real-time location and video information provided by the platform, law enforcement officers from the public security department went to the scene to carry out law enforcement, while after-sales personnel from the manufacturer went to the scene simultaneously to troubleshoot the positioning system malfunction.

[0147] The vehicle successfully drove out of the restricted area, law enforcement officers completed on-site enforcement, and after the manufacturer's after-sales personnel investigated and repaired the positioning fault, they reported the results to the platform.

[0148] The platform completes the closed-loop processing of work orders and encrypts and stores all data related to this violation (including vehicle trajectory, violation video, law enforcement records, and fault repair records) as evidence for law enforcement.

[0149] Application Scenario 2: Emergency response and coordination in the event of a traffic accident involving an autonomous vehicle:

[0150] A driverless car collided with another vehicle while driving on the road. The vehicle's collision sensor triggered an accident signal, reported a fault code to the platform, and uploaded a real-time video of the scene.

[0151] The platform's anomaly detection module immediately identifies "traffic accident" as an emergency level anomaly based on sudden speed changes and collision fault codes, triggering a red alarm.

[0152] The multi-level linkage response layer immediately connects with the 120 emergency medical center, the traffic police department, and the vehicle manufacturer's after-sales system to push the accident location, vehicle information, and on-site video screenshots to each linked party, while providing real-time location navigation of the accident scene to the 120 emergency medical center and the traffic police department;

[0153] The core regulatory processing layer retrieves the historical operating trajectory and real-time video of the driverless car to provide data support for the traffic police department in determining liability for accidents;

[0154] The 120 emergency medical center arrived at the accident scene in a timely manner to carry out personnel rescue, the traffic police arrived at the scene to direct traffic and determine liability for the accident, and the manufacturer's after-sales personnel arrived at the scene to investigate vehicle malfunctions;

[0155] After the accident is handled, the traffic police department will report the accident liability determination results, the emergency center will report the rescue results, and the manufacturer will report the fault investigation results to the platform;

[0156] The platform completes the closed-loop handling of work orders, encrypts and stores all accident-related data, and provides a basis for subsequent accident handling and equipment improvement.

[0157] Application Scenario 3: Handling traffic congestion caused by low battery delays of unmanned delivery robots:

[0158] When an unmanned delivery robot was driving on a non-motorized vehicle lane in the city, its remaining battery level dropped to 15%. The platform's anomaly detection module identified it as a "low battery warning" (a general level anomaly) and triggered a yellow alarm.

[0159] The multi-level linkage and handling layer pushes abnormal information to the robot manufacturer's after-sales system and coordinates with urban management departments and traffic management departments;

[0160] The core monitoring and processing layer issued an instruction to the robot to "guide it to stop in the nearest safe area of ​​the sidewalk". The robot received and executed the instruction, and slowly moved to the sidewalk next to the non-motorized vehicle lane to avoid further obstructing traffic.

[0161] The manufacturer's after-sales personnel went to the site to replace the robot's battery based on the robot's real-time location provided by the platform;

[0162] After the battery was replaced, the robot returned to normal operation, and the after-sales personnel reported the results to the platform.

[0163] The platform completes the closed-loop handling of work orders, records the handling process and results of this low battery warning, and reminds manufacturers to optimize the robot's battery warning strategy through data analysis.

[0164] Application Scenario 4: Control and Handling of Drones Violating Airport Airspace:

[0165] The platform's electronic fence module has been pre-set by the civil aviation regulatory authorities and public security departments as a no-fly zone for airport airspace, and the control level is set to urgent.

[0166] A civilian drone flew into the airport's airspace without prior registration. The platform's anomaly detection module immediately identified it as an "illegal boundary crossing" emergency, triggering a red alarm. At the same time, it began recording the drone's real-time video to automatically collect evidence.

[0167] The multi-level joint response layer immediately coordinated with the civil aviation regulatory authorities, public security departments, and drone manufacturers' after-sales systems to push the drone's ID, manufacturer, real-time location, flight trajectory, and video screenshots;

[0168] The core monitoring and processing layer issues an instruction to the drone to "immediately return to base and land in the designated safe area." If the drone refuses to comply with the instruction, the platform issues a "forced landing" instruction, and the drone's flight control system executes the forced landing.

[0169] Based on the emergency landing location provided by the platform, law enforcement officers from the public security department went to the scene to conduct law enforcement and investigation, and the civil aviation regulatory department recorded this illegal flight.

[0170] After the law enforcement investigation is completed, the public security department will report the results to the platform. The platform will then complete the closed loop of the handling work order and encrypt and store all data of the illegal flight as the basis for punishment.

[0171] Application Scenario 5: Supervision and handling of unmanned traffic police robots experiencing malfunctions and shutdowns:

[0172] An unmanned traffic police robot at a certain intersection stopped due to a hardware malfunction and was unable to carry out traffic control work normally. It reported a fault code to the platform, and the platform's anomaly identification module determined it to be an "equipment malfunction" emergency level anomaly, triggering an orange alarm.

[0173] The multi-level linkage response layer pushes abnormal information to the robot manufacturer's after-sales system and coordinates with the local traffic police department;

[0174] The remote control module of the core monitoring and processing layer first sends a "remote restart" command to the robot to attempt to repair the fault through remote operation. If the remote restart fails, it sends a work order to the manufacturer's after-sales system to "immediately arrange maintenance personnel for on-site repair".

[0175] Based on the alarm information from the platform, the traffic police department promptly dispatched officers to the intersection to manually take over traffic control and prevent traffic chaos caused by the shutdown of the unmanned traffic police robot.

[0176] The manufacturer's maintenance personnel went to the site to troubleshoot and repair the robot's hardware faults. After the robot returned to normal operation, the repair results were reported back to the platform.

[0177] The platform completes the closed-loop handling of work orders, records the cause of the fault, the repair process, and the handling time. At the same time, by analyzing the equipment fault data, it reminds manufacturers to optimize the hardware quality of the robots and the fault self-diagnosis strategy.

[0178] Application Scenario 6: Unified scheduling and supervision of various types of unmanned equipment during large-scale events:

[0179] When a city hosts a large-scale public event, security control needs to be strengthened in the event site and surrounding areas. The management department uses the platform of this invention to uniformly access various types of unmanned equipment at the event site, such as unmanned patrol vehicles, security drones, unmanned inspection robots, and emergency rescue robots.

[0180] The platform's core monitoring and processing layer performs unified path planning and operation scheduling for various types of unmanned equipment based on the area division and control requirements of the event site, avoiding path conflicts between different equipment, and setting up electronic fences at the event site to limit the operating range of the equipment.

[0181] The data acquisition and analysis layer collects all-dimensional operational data of all connected equipment in real time. The full-domain monitoring module enables real-time visual monitoring of all equipment on the command center's large screen, allowing supervisors to view the equipment's location, status, and operational trajectory in real time.

[0182] If a security drone issues a low battery warning, the platform immediately issues a guidance command to direct it to the nearest charging area, while simultaneously dispatching another security drone to take over its patrol mission; if an abnormal situation is discovered in a certain area, the unmanned inspection robot promptly reports it, and the platform immediately coordinates with on-site police personnel and dispatches unmanned patrol vehicles to the scene for handling.

[0183] During the event, the platform used multi-dimensional data collection and intelligent anomaly identification to achieve real-time monitoring and rapid response of all unmanned equipment, ensuring the safety and order of the event site.

[0184] After the event, the platform generates operation and monitoring reports for various types of unmanned equipment, and compiles data such as equipment runtime, number of malfunctions, and handling efficiency, providing a reference for the management and control of unmanned equipment in subsequent large-scale events.

[0185] The platform and method of this invention, through standardized interface adaptation, full-dimensional data collection, intelligent anomaly identification, remote intervention control, and multi-level linkage, achieve unified supervision of unmanned equipment from multiple manufacturers and of multiple types. It effectively solves many problems in the supervision of unmanned equipment in the prior art, and ensures social public order and public safety during the operation of unmanned equipment. It can be widely used in the supervision of unmanned equipment in multiple government departments such as traffic management, public security, emergency management, and urban management. At the same time, it has good scalability and can adapt to the supervision needs of new types of unmanned equipment in the future.

[0186] The present invention has been described above by way of example with reference to the accompanying drawings. Obviously, the specific implementation of the present invention is not limited to the above-described manner. Any non-substantial improvements made using the inventive concept and technical solution; or the direct application of the inventive concept and technical solution to other situations without modification, are all within the protection scope of the present invention.

Claims

1. A unified operation management and monitoring platform for multiple types of unmanned equipment, characterized in that: The platform comprises, in sequence, a standardized interface adaptation layer, a data acquisition and parsing layer, a core regulatory processing layer, a multi-level linkage and handling layer, and a regulatory display and data storage layer, wherein: The standardized interface adaptation layer is used to define a unified equipment access specification and provide protocol adaptation plugins to achieve standardized access for multiple types of unmanned equipment. The data acquisition and parsing layer is used to acquire full-dimensional operational data of unmanned equipment through the standardized interface adaptation layer, and to clean, convert, and standardize the acquired data. The core monitoring and processing layer is used to perform full-domain monitoring, anomaly identification, and risk level determination of unmanned equipment based on the data processed by the data acquisition and analysis layer. The multi-level linkage and handling layer is used to receive the anomaly identification results from the core regulatory processing layer, automatically push the anomaly information to the corresponding equipment manufacturer's after-sales system according to the anomaly type and risk level, and link with the business systems of relevant government departments to generate standardized handling work orders and track the handling progress. The regulatory display and data storage layer is used to provide a visual regulatory interface and to retain the platform's full-process work data for a long time.

2. The unified operation management and monitoring platform for multiple types of unmanned equipment according to claim 1, characterized in that: The core monitoring and processing layer includes a full-domain monitoring module, an electronic fence module, an anomaly detection module, a remote control module, and an access control module. The full-domain monitoring module provides real-time location visualization of all connected equipment. The electronic fence module allows for customized configuration of no-entry / no-fly zones in sensitive areas and automatically triggers an anomaly alarm when equipment exceeds the fence boundary. The anomaly detection module identifies anomalies in all connected equipment in real time based on preset anomaly detection rules and determines the risk level. The remote control module issues control commands to abnormal equipment for remote intervention. The access control module provides hierarchical management of the monitoring operation permissions of different management departments.

3. The unified operation management and monitoring platform for multiple types of unmanned equipment according to claim 2, characterized in that: In the anomaly detection module, the preset anomaly detection rules include: Energy status anomaly identification: Anomaly identification is performed based on the energy parameters of the unmanned equipment, including battery power, fuel balance, range, energy consumption rate, and energy replenishment status; Spatial location anomaly identification: Anomaly identification is performed based on the position parameters of unmanned equipment and preset spatial constraints; the position parameters include latitude and longitude, elevation, heading, trajectory, speed, and acceleration, and the spatial constraints include electronic fences, no-entry zones, restricted zones, predetermined routes, and road rules; Equipment status anomaly identification: Anomaly identification is performed based on the unmanned equipment's own status parameters, including the unmanned equipment's operating status code, fault code, sensor data, communication status, temperature, and attitude. Anomaly identification for safety incidents: Anomaly identification is performed based on safety incident parameters of unmanned equipment, including collision signals, rapid deceleration, video analysis results, and audio analysis results of the unmanned equipment; Composite anomaly identification: Anomaly identification is performed based on the correlation analysis of at least two of the above-mentioned parameters.

4. The unified operation management and monitoring platform for multiple types of unmanned equipment according to claim 1, characterized in that: The visualization interface provided by the monitoring display and data storage layer includes a PC-based monitoring screen, a mobile monitoring app, and a command center visualization terminal.

5. A method for monitoring a unified operation management and monitoring platform for multiple types of unmanned equipment, using the unified operation management and monitoring platform for multiple types of unmanned equipment according to any one of claims 1-4, characterized in that: The method includes the following steps: Step S1: Authentication for access to multiple types of unmanned equipment; Step S2: Collect data from all dimensions of the connected unmanned equipment; Step S3: Based on the collected data from all dimensions, perform full-domain monitoring, anomaly identification, and risk level determination on the connected unmanned equipment; if there are no anomalies, return to step S2; otherwise, continue to the next step. Step S4: After identifying the anomaly, link the corresponding equipment manufacturer's after-sales system and the relevant government department's business system to push the anomaly information and perform remote intervention. Step S5: After receiving the abnormal information, the manufacturer's after-sales system and relevant government departments will carry out on-site handling and record the work data of the entire abnormal handling process, including equipment operation data, abnormal alarm data, linkage handling data, handling result data, real-time video stream and screenshots.

6. The monitoring method for a unified operation management and monitoring platform for multiple types of unmanned equipment according to claim 5, characterized in that: Step S1 includes: Step S101: The unmanned equipment initiates an access request to the platform's standardized interface adaptation layer through its own communication module. The access request includes the equipment's unique ID, equipment type, and manufacturer code. Step S102: The standardized interface adaptation layer performs identity authentication on the equipment information in the access request, and verifies whether the equipment has completed the filing. Unfiled equipment is rejected from access, and filed equipment proceeds to the next step. Step S103: The standardized interface adaptation layer automatically matches the corresponding protocol adaptation plugin according to the equipment's manufacturer and type, completing the adaptation of the private protocol and the platform's unified protocol. Step S104: After the protocol adaptation is completed, the platform registers the equipment, generates a unique platform access identifier, and establishes an encrypted data transmission link. Step S105: The equipment uploads basic operational data to the platform through a standardized data transmission link to complete the access process.

7. The supervision method for a unified operation management and monitoring platform for multiple types of unmanned equipment according to claim 5, characterized in that: Step S2 includes: Step S201: The data acquisition and parsing layer's acquisition nodes receive raw operational data uploaded by the unmanned equipment in real time; Step S202: The data acquisition and parsing layer calls the parsing server to clean the raw operating data, remove invalid and duplicate data caused by network fluctuations, mark missing data caused by equipment failure and remind the manufacturer to investigate; Step S203: The parsing server performs format conversion and standardization processing on the cleaned raw operating data according to the platform's unified encoding rules and data format to ensure that the data formats of different manufacturers and different types of equipment are consistent; Step S204: The standardized, multi-dimensional data is uploaded to the core regulatory processing layer in real time through the platform's internal links.

8. The supervision method for a unified operation management and monitoring platform for multiple types of unmanned equipment according to claim 5, characterized in that: Step S3 includes: Step S301: The full-domain monitoring module of the core supervision and processing layer marks the standardized equipment data on the electronic map in real time, realizing visualized full-domain monitoring of all connected equipment. Supervisors can view the real-time status of the equipment through the supervision display terminal. Step S302: The electronic fence module verifies the real-time location information of the equipment in real time, determines whether the equipment has entered the preset no-entry / no-fly fence area, and automatically triggers an abnormal alarm when the equipment enters the preset no-entry / no-fly fence area. Step S303: The anomaly identification module matches the real-time collected equipment operation data with the preset anomaly identification rules in real time to identify anomalies and determine the risk level of the equipment. Step S304: If it is determined that there is no abnormality in the equipment, return to step S2 and continue to collect data in all dimensions; if it is determined that there is an abnormality in the equipment, push the abnormality information to the multi-level linkage and handling layer, and issue an abnormality alarm through the visual monitoring interface of the monitoring display and data storage layer.

9. The supervision method for a unified operation management and monitoring platform for multiple types of unmanned equipment according to claim 5, characterized in that: Step S4 includes: Step S401: After receiving the abnormal information, the linkage server of the multi-level linkage handling layer identifies the abnormal type and risk level; Step S402: The linkage server automatically pushes the anomaly information to the corresponding equipment manufacturer's after-sales system and the relevant government department's business system through the API interface according to the anomaly type and risk level. Step S403: The remote control module of the core monitoring and processing layer issues the corresponding remote intervention command to the abnormal equipment according to the anomaly type; Step S404: The remote control module receives the remote intervention command execution receipt from the equipment. If the command is executed successfully, the module monitors the status changes of the equipment in real time. If the command fails to execute, the module immediately feeds back the result to the supervisor, who then takes manual intervention measures.

10. The supervision method for a unified operation management and monitoring platform for multiple types of unmanned equipment according to claim 5, characterized in that: Step S5 includes: Step S501: After receiving the abnormal information, the manufacturer's after-sales system and relevant government departments will carry out on-site handling work; Step S502: After the disposal is completed, the manufacturer and government departments will feed back the disposal results to the platform's multi-level linkage disposal layer; Step S503: The multi-level linkage processing layer's work order management system completes the closed-loop processing of the work order based on the feedback processing results, and marks the work order status as completed. Step S504: The monitoring, display and data storage layer encrypts and stores the work data of the entire process of handling this anomaly and generates a data traceability ledger.

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