Intelligent coordination system and method for cross-enterprise emergency linkage drill in chemical industry park

Abstract

The invention relates to the technical field of chemical industry park emergency management, and discloses a chemical industry park cross-enterprise emergency linkage drill intelligent coordination system. The system comprises a park-level emergency linkage platform, a task distribution module, a real-time monitoring module and a drill evaluation module. The platform integrates the emergency resource information of each enterprise through a standardized interface, and adopts distributed storage to realize centralized management; the task allocation module automatically generates a cross-enterprise rescue scheme based on an intelligent algorithm by integrating factors such as an accident position, a resource matching degree and a rescue path; the real-time monitoring module collects drill data through a sensor network and video equipment; and the evaluation module generates a visual report according to the quantitative index system and provides optimization suggestions. According to the invention, efficient coordination and intelligent scheduling of cross-enterprise emergency resources are realized, the emergency response speed and cooperative processing capability of the park are significantly improved, the emergency response time is shortened by more than 60%, the resource allocation accuracy is improved by more than 20%, and a continuously optimized emergency management closed loop is formed.

Description

Technical Field

[0001] This invention belongs to the field of emergency management technology for chemical industrial parks, and in particular relates to an intelligent coordination system and method for cross-enterprise emergency response drills in chemical industrial parks. Background Technology

[0002] With the clustered development of the chemical industry, chemical industrial parks are expanding in scale, housing numerous chemical enterprises. These enterprises involve large quantities of hazardous chemicals in their production processes, and accidents can easily trigger chain reactions, causing serious casualties, property damage, and environmental pollution. Therefore, how to achieve rapid emergency collaboration, resource integration, and joint drills among different enterprises within chemical industrial parks has become a key technical issue in improving the overall emergency response capabilities of the parks.

[0003] In the existing technology, there have been several studies on emergency drill management. For example, patent CN111985746A discloses an emergency drill evaluation method and device for refining and chemical enterprises. It evaluates the emergency response situation within a single enterprise by configuring accident scenarios, drill roles, and evaluation items. However, this method focuses on internal emergency management and lacks an organization and coordination mechanism for cross-enterprise collaborative drills. Patent CN114781796A proposes an emergency plan management system for chemical industrial clusters. It improves the intelligence level of emergency plans by intelligently analyzing plan content, accurately pushing plan information, and managing drill processes. However, this system mainly focuses on the optimization and push of the plan itself and does not involve real-time task allocation and dynamic resource allocation among multiple enterprises in cross-enterprise joint drills. Patent CN120031422A relates to a mine disaster emergency response model based on knowledge graphs and swarm intelligence collaboration. It utilizes large-scale models, knowledge graphs, and swarm intelligence computing for decision support. However, this technology is designed for the mining sector and does not fully consider the unique characteristics of multi-enterprise collaborative emergency response in chemical industrial parks, and lacks real-time monitoring and evaluation of the entire drill process. Furthermore, while other systems such as CN110544402A provide virtual simulation emergency exercise functions, they primarily focus on scenario simulation and data fusion, and remain insufficient in intelligent task allocation, real-time coordination, and closed-loop evaluation for cross-enterprise collaborative drills.

[0004] Therefore, there is an urgent need for a system that can integrate park resources, achieve intelligent coordination of cross-enterprise emergency response drills, and provide full-process monitoring, evaluation, and continuous optimization. Summary of the Invention

[0005] To address the aforementioned problems in existing technologies, this invention provides an intelligent coordination system for cross-enterprise emergency response drills in chemical industrial parks, characterized by comprising:

[0006] The park-level emergency response platform connects to the internal emergency management systems of various enterprises through standardized data interfaces and is equipped with a distributed database for real-time integration and storage of emergency resource information of various enterprises. The emergency resource information includes the reserve quantity, storage location and expiration date of emergency supplies, the accident type, handling process and division of responsibilities in the emergency plan, as well as the quantity, skills and qualifications, equipment model and operating status of personnel and equipment.

[0007] The task assigner communicates with the park-level emergency response platform and has a built-in intelligent algorithm based on multi-source data fusion analysis. The intelligent algorithm generates a rescue task assignment scheme based on a preset cross-enterprise accident scenario, combined with the accident location, the distribution of surrounding enterprises, the matching degree of enterprise emergency resources, and the rescue route planning.

[0008] The real-time monitoring module consists of a sensor network and video surveillance equipment deployed at key locations in the park, and is connected to the feedback system of each enterprise. It is used to collect real-time data during the exercise, including information transmission delay time, resource allocation rate and rescue mission completion time.

[0009] The exercise evaluation module is connected to the real-time monitoring module and the park-level emergency response platform. It has an exercise evaluation index system to comprehensively evaluate the collected real-time data, generate a visual evaluation report and output optimization suggestions.

[0010] The intelligent algorithm identifies the emergency resource reserves of enterprises near the accident site during operation, dynamically allocates personnel and equipment with relevant skills, and coordinates with surrounding enterprises to provide auxiliary support.

[0011] Furthermore, the preset cross-enterprise accident scenarios include at least one of the following: leakage in public utility tunnels, fire spread in industrial parks, fire in chemical material storage tank areas, and pollution of surrounding areas caused by explosions at hazardous waste treatment plants.

[0012] Furthermore, in the scenario of a public utility tunnel leakage accident, the intelligent algorithm specifically identifies the inventory status of leak-sealing equipment and protective materials of enterprises near the leak point, automatically matches and dispatches personnel with leak-sealing skills to the scene, and simultaneously coordinates with surrounding enterprises to initiate fire water supply and evacuation guidance procedures.

[0013] Furthermore, the exercise evaluation index system has quantified evaluation parameter thresholds, including an information transmission delay time threshold of 30 to 180 seconds, a resource allocation availability threshold of 80% to 100%, and a rescue mission completion time threshold of 5 to 60 minutes.

[0014] Furthermore, the distributed database adopts a highly reliable storage architecture, supporting real-time updates of emergency resource information and concurrent access from multiple nodes.

[0015] Furthermore, the intelligent algorithm integrates machine learning models and optimization algorithms, and is continuously trained using historical training data to dynamically adjust the task allocation strategy.

[0016] Furthermore, it also includes a cross-enterprise real-time communication module, which enables information sharing and collaborative instruction transmission between enterprises through a dedicated network channel.

[0017] This invention also provides an intelligent coordination method for cross-enterprise emergency response drills in chemical industrial parks, characterized by the following steps:

[0018] S1. Through the standardized data interface of the park-level emergency response platform, integrate the emergency resource information of various enterprises and store it in a distributed database to achieve real-time updates.

[0019] S2. Initiate emergency response based on preset cross-enterprise accident scenarios, use intelligent algorithms to fuse and analyze multi-source data, and automatically generate a rescue task allocation plan by combining the accident location, distribution of surrounding enterprises, matching degree of enterprise emergency resources and rescue route planning.

[0020] S3. Collect real-time data during the exercise through the real-time monitoring module, including information transmission delay time, resource allocation rate and rescue mission completion time.

[0021] S4. Based on the exercise evaluation index system, comprehensively evaluate the collected real-time data, generate a visual evaluation report, and output optimization suggestions;

[0022] S5. Based on the optimization suggestions in the assessment report, revise the enterprise's emergency plan, supplement emergency resources, and adjust the system algorithm parameters and assessment indicators to form a closed-loop management mechanism.

[0023] Furthermore, in step S2, the intelligent algorithm dynamically identifies the emergency resource reserves of enterprises near the accident site, dispatches personnel and equipment with relevant skills nearby, and coordinates with surrounding enterprises to provide fire protection, medical or evacuation support.

[0024] Furthermore, in step S5, the optimization suggestions include specific improvement measures for information transmission delay, resource allocation efficiency, and rescue mission execution effectiveness, and the algorithm and evaluation criteria are iteratively updated through the system's self-optimization mechanism.

[0025] Compared with the prior art, the present invention has the following beneficial effects:

[0026] (1) Significantly improved the response efficiency and resource allocation accuracy of cross-enterprise emergency response in chemical industrial parks. Through an intelligent task allocation mechanism, the system can quickly match the optimal rescue plan, which greatly shortens the emergency response time, significantly improves the accuracy of resource allocation, and effectively enhances the overall emergency response efficiency.

[0027] (2) It enables visualized monitoring and scientific evaluation of the entire emergency drill process. Through multi-dimensional data collection and quantitative analysis, the system generates objective and accurate evaluation reports, making the evaluation of drill effectiveness more comprehensive and reliable, and providing strong support for improving emergency response capabilities.

[0028] (3) A closed-loop management mechanism for continuous optimization has been established. The system can automatically generate improvement suggestions based on the results of drills and evaluations, driving the improvement of emergency plans and the optimization of resource allocation, forming a virtuous cycle of self-improvement and enhancing the emergency management level of the park.

[0029] (4) It effectively broke down information barriers between enterprises and enhanced cross-enterprise collaborative combat capabilities. Through standardized information sharing and real-time communication mechanisms, it ensured efficient collaboration among emergency response units and provided reliable guarantees for the joint handling of complex accidents.

[0030] (5) Enhanced the park's overall ability to respond to complex emergencies. Through intelligent coordination and command and multi-enterprise resource integration, the system significantly enhanced the park's rapid response and collaborative handling capabilities in the event of major accidents, minimizing accident risks and losses. Attached Figure Description

[0031] Figure 1 This is an overall architecture diagram of the intelligent coordination system for cross-enterprise emergency response drills in chemical industrial parks, according to an embodiment of the present invention.

[0032] Explanation of reference numerals in the attached diagram: 1. Enterprise Information; 2. Emergency Plan; 3. Personnel and Equipment Information; 4. Data Integration Layer; 5. Data Processing Layer; 6. Database; 7. Standardized Interface; 8. Task Assigner; 9. Intelligent Algorithm; 10. Task Scheduler; 11. Monitoring and Evaluation Layer; 12. Real-time Monitoring Module; 13. Exercise Evaluation Index System; 14. Enterprise-side Data Upload; 15. Enterprise Emergency Resource Information; 16. Enterprise Emergency Plan; 17. Platform Command Issuance; 18. Task Assignment Command; 19. Resource Allocation Command; 20. Enterprise One; 21. Enterprise Two; 22. Enterprise Three. Detailed Implementation

[0033] The present invention will now be described in further detail with reference to the accompanying drawings. This embodiment is implemented based on the technical solution of the present invention, and provides detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0034] The core of this invention, the intelligent coordination system for cross-enterprise emergency response drills in chemical industrial parks, lies in its hierarchical architecture design to achieve intelligent integration and collaborative scheduling of cross-enterprise emergency resources. For example... Figure 1As shown, the system uses a park-level emergency response platform as its core hub, connecting with the internal systems of each enterprise (20, 21, and 22) through standardized interface 7. The system comprises four core layers: data integration layer 4, intelligent decision-making layer, command execution layer, and monitoring and evaluation layer 11.

[0035] Among them, the data integration layer 4 receives emergency resource information 15 from various enterprises through the standardized interface 7, including enterprise information 1, emergency plan 2 and personnel and equipment information 3. After being cleaned and standardized by the data processing layer 5, this data is stored in the database 6 with a distributed architecture. The database 6 supports concurrent access from multiple nodes to ensure that the data is updated in real time.

[0036] The intelligent decision-making layer includes a task allocator 8 and a task scheduler 10. The task allocator 8 incorporates an intelligent algorithm 9 based on multi-source data fusion analysis. This algorithm integrates machine learning models and optimization algorithms, enabling it to continuously optimize task allocation strategies based on historical drill data. When a preset accident scenario is triggered, the intelligent algorithm 9 comprehensively considers factors such as the accident location, the distribution of surrounding enterprises, resource matching, and rescue route planning, generating the optimal task allocation plan within seconds.

[0037] The instruction execution layer distributes task allocation instructions 18 and resource allocation instructions 19 to relevant enterprises through the task scheduler 10. The cross-enterprise real-time communication module, based on a dedicated network channel, ensures the timeliness and accuracy of instruction transmission between enterprises.

[0038] The monitoring and evaluation layer 11 includes a real-time monitoring module 12 and a drill evaluation indicator system 13. The real-time monitoring module 12 collects key indicator data in real time during the drill by using sensor networks and video surveillance equipment deployed at key locations in the park, combined with feedback information from the enterprise.

[0039] Example 1: Cross-regional pollution emergency response coordination triggered by an explosion at a hazardous waste treatment plant

[0040] This example addresses a complex scenario involving pollution caused by an explosion at a hazardous waste treatment plant. An explosion occurred at a centralized hazardous waste treatment facility within a chemical industrial park, resulting in the leakage of toxic chemicals that spread through the atmosphere, threatening multiple businesses downwind.

[0041] After the system was started, the data integration layer 4 completed a resource inventory of the affected enterprises within 30 seconds: identifying 5 enterprises within a 2-kilometer radius that possessed relevant protection and response capabilities. Among them, enterprise 20 had 50 sets of heavy chemical protective suits, enterprise 21 was equipped with 2 environmental monitoring vehicles, and enterprise 22 had an emergency decontamination station.

[0042] The intelligent decision-making layer's task allocator 8, based on an improved particle swarm optimization algorithm, comprehensively considers factors such as wind speed and direction, pollutant diffusion models, and enterprise resource matching to generate disposal plans.

[0043] (1) Prioritize the deployment of chemical protective suits from Company 20 to emergency response personnel within 200 meters of the leak point; dispatch the environmental monitoring vehicle of Company 21 to set up monitoring points downwind, and activate the emergency decontamination station of Company 22 to receive potentially contaminated personnel;

[0044] (2) The real-time monitoring module 12 tracks the diffusion path of pollutants in real time through 80 air quality sensors and 30 high-definition cameras, and updates the location of the pollution cloud every 2 minutes.

[0045] (3) Exercise evaluation index system 13 Set special thresholds for this scenario: the environmental monitoring data reporting delay threshold is 90 seconds, the decontamination facility activation time threshold is 10 minutes, and the protective equipment allocation rate threshold is 85%.

[0046] Following the drill, the system-generated assessment report showed that the accuracy rate of pollutant diffusion prediction reached 88%, and the emergency resource allocation rate was 87%. However, there was an average delay of 65 seconds in information sharing between enterprises. Based on this, the system proposed optimization suggestions: add a dedicated emergency communication channel and establish a real-time sharing mechanism for environmental monitoring data between enterprises.

[0047] Example 2: Rapid Response and Coordination for Accidents Involving Hazardous Chemical Transport Vehicles

[0048] This example demonstrates the system's rapid response capability in the event of a hazardous chemical transport accident on a park road. It simulates a tanker truck carrying flammable solvents overturning on a main road within the park, resulting in a small leak and traffic congestion.

[0049] The system automatically issues an alarm within 20 seconds of an accident via roadside sensors. Data integration layer 4 immediately searches for emergency resources within a 1-kilometer radius of the accident site and identifies:

[0050] a) The company is located 300 meters from the accident site and has oil-absorbing mats and leak-sealing tools in stock.

[0051] b) Enterprise 21 is 500 meters away and is equipped with a professional fire truck and foam extinguishing agent;

[0052] c) Enterprise 22 is 800 meters away and has a medical aid station and evacuation guidance personnel.

[0053] Task Assignor 8's intelligent algorithm 9 uses Dijkstra's algorithm for optimal path planning, avoiding congested sections and generating solutions:

[0054] 1) The company's emergency response team carried oil-absorbing mats to control the leak first;

[0055] 2) The fire truck from Company 21 arrived at the scene via the backup route to establish a perimeter.

[0056] 3) Enterprise 22 simultaneously initiated the evacuation procedure for personnel in the surrounding area.

[0057] The real-time monitoring module 12 monitors the on-site situation and traffic conditions in real time through intelligent traffic cameras and drone aerial photography. The exercise evaluation index system 13 sets the key parameters for this scenario: the arrival time threshold for the first batch of personnel is 5 minutes, the leakage control completion time threshold is 15 minutes, and the traffic diversion completion rate threshold is 90%.

[0058] The implementation results show that the system's response time in this scenario was reduced by 58% compared to the traditional model. The first responders arrived on site within 3 minutes and 40 seconds, and the leak was effectively controlled within 12 minutes. Through cross-enterprise collaboration, secondary accidents were avoided, and the impact of the accident was minimized.

[0059] This invention achieves an intelligent upgrade of emergency response coordination in chemical industrial parks through the above-described embodiments. After each drill, the system automatically generates a detailed evaluation report. Based on the optimization suggestions in the report, the park management department continuously revises the emergency plan, replenishes emergency resources, and optimizes algorithm parameters. This closed-loop management mechanism ensures that the system can learn and improve from each drill, continuously enhancing the overall emergency response capability of the park.

[0060] The above description is a preferred embodiment of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A smart coordination system for cross-enterprise emergency response drills in a chemical industrial park, characterized in that: include: The park-level emergency response platform connects to the internal emergency management systems of various enterprises through standardized data interfaces and is equipped with a distributed database for real-time integration and storage of emergency resource information of various enterprises. The emergency resource information includes the reserve quantity, storage location and expiration date of emergency supplies, the accident type, handling process and division of responsibilities in the emergency plan, as well as the quantity, skills and qualifications, equipment model and operating status of personnel and equipment. The task assigner communicates with the park-level emergency response platform and has a built-in intelligent algorithm based on multi-source data fusion analysis. The intelligent algorithm generates a rescue task assignment scheme based on a preset cross-enterprise accident scenario, combined with the accident location, the distribution of surrounding enterprises, the matching degree of enterprise emergency resources, and the rescue route planning. The real-time monitoring module consists of a sensor network and video surveillance equipment deployed at key locations in the park, and is connected to the feedback system of each enterprise. It is used to collect real-time data during the exercise, including information transmission delay time, resource allocation rate and rescue mission completion time. The exercise evaluation module is connected to the real-time monitoring module and the park-level emergency response platform. It has an exercise evaluation index system to comprehensively evaluate the collected real-time data, generate a visual evaluation report and output optimization suggestions. The intelligent algorithm identifies the emergency resource reserves of enterprises near the accident site during operation, dynamically allocates personnel and equipment with relevant skills, and coordinates with surrounding enterprises to provide auxiliary support.

2. The intelligent coordination system for cross-enterprise emergency response drills in chemical industrial parks according to claim 1, characterized in that, The preset cross-enterprise accident scenarios include at least one of the following: leakage in public utility tunnels, fire spread in industrial parks, fire in chemical material storage tank areas, and pollution caused by explosions at hazardous waste treatment plants.

3. The intelligent coordination system for cross-enterprise emergency response drills in chemical industrial parks according to claim 1, characterized in that, In the scenario of a public utility tunnel leakage accident, the intelligent algorithm specifically identifies the inventory of leak-sealing equipment and the reserve status of protective materials of enterprises near the leak point, automatically matches and dispatches personnel with leak-sealing skills to the scene, and at the same time coordinates with surrounding enterprises to initiate fire water supply and evacuation guidance procedures.

4. The intelligent coordination system for cross-enterprise emergency response drills in chemical industrial parks according to claim 1, characterized in that, The exercise evaluation index system has quantified evaluation parameter thresholds, including an information transmission delay time threshold of 30 to 180 seconds, a resource allocation availability threshold of 80% to 100%, and a rescue mission completion time threshold of 5 to 60 minutes.

5. The intelligent coordination system for cross-enterprise emergency response drills in chemical industrial parks according to claim 1, characterized in that, The distributed database adopts a highly reliable storage architecture, supporting real-time updates of emergency resource information and concurrent access from multiple nodes.

6. The intelligent coordination system for cross-enterprise emergency response drills in chemical industrial parks according to claim 1, characterized in that, The intelligent algorithm integrates machine learning models and optimization algorithms, and is continuously trained using historical training data to dynamically adjust the task allocation strategy.

7. The intelligent coordination system for cross-enterprise emergency response drills in chemical industrial parks according to claim 1, characterized in that, It also includes a cross-enterprise real-time communication module, which enables information sharing and collaborative instruction transmission between enterprises through a dedicated network channel.

8. A method for intelligent coordination of cross-enterprise emergency response drills in chemical industrial parks based on the system described in any one of claims 1 to 7, characterized in that, Includes the following steps: S1. Through the standardized data interface of the park-level emergency response platform, integrate the emergency resource information of various enterprises and store it in a distributed database to achieve real-time updates. S2. Initiate emergency response based on preset cross-enterprise accident scenarios, use intelligent algorithms to fuse and analyze multi-source data, and automatically generate a rescue task allocation plan by combining the accident location, distribution of surrounding enterprises, matching degree of enterprise emergency resources and rescue route planning. S3. Collect real-time data during the exercise through the real-time monitoring module, including information transmission delay time, resource allocation rate and rescue mission completion time. S4. Based on the exercise evaluation index system, comprehensively evaluate the collected real-time data, generate a visual evaluation report, and output optimization suggestions; S5. Based on the optimization suggestions in the assessment report, revise the enterprise's emergency plan, supplement emergency resources, and adjust the system algorithm parameters and assessment indicators to form a closed-loop management mechanism.

9. The method according to claim 8, characterized in that, In step S2, the intelligent algorithm dynamically identifies the emergency resource reserves of enterprises near the accident site, dispatches personnel and equipment with relevant skills nearby, and coordinates with surrounding enterprises to provide fire protection, medical or evacuation assistance.

10. The method according to claim 8, characterized in that, In step S5, the optimization suggestions include specific improvement measures for information transmission delay, resource allocation efficiency, and rescue mission execution effectiveness, and the algorithm and evaluation criteria are iteratively updated through the system's self-optimization mechanism.

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