Safety Management System: The "Daily Prevention and Control Hub" for Safety Risks
Focused on the regular safety management of gas enterprises, it covers the entire process of "risk identification, hidden danger rectification, safety training, and compliance auditing," and builds a safety system featuring "proactive prevention and full-staff participation." Its core functions include:
1. Intelligent Dynamic Risk Identification
It integrates pipeline aging data (service life, material), historical accident data, and environmental data (heavy rain, high temperature, frozen soil). Through the "risk matrix algorithm + machine learning model," it automatically identifies high-risk areas (e.g., "85% risk of freezing and cracking of a certain old pipeline in winter," "70% risk of third-party construction collision around the station"). It generates a risk heat map, marked with four levels: red (extremely high), yellow (high), blue (medium), and green (low). It supports risk data drilling (e.g., clicking on a red area to view specific risk points and prevention suggestions).
2. Closed-Loop Management of Hidden Dangers
It supports multi-channel hidden danger reporting (inspectors uploading photos via mobile devices, user reports, automatic identification by AI monitoring). The system automatically generates a hidden danger ledger (including location, type, risk level, and responsible department) and assigns rectification work orders based on "risk levels" (rectification of extremely high risks within 24 hours, high risks within 72 hours). After rectification, on-site photos/test reports must be uploaded, and the loop can only be closed after verification and approval by the safety department. Failure to rectify on time automatically triggers multi-level early warnings (from department heads to the enterprise safety director).
3. Safety Training and Assessment
It builds an online safety training platform, providing customized courses (e.g., safe operation of pipeline inspection, station fire drills, user gas safety knowledge). It supports video learning, online exams, and archiving of training records. For key positions (inspectors, emergency repair personnel), an "annual safety assessment" is set up; those who fail the assessment are prohibited from taking up their posts to ensure that personnel meet the required safety skills.
4. Safety Compliance and Auditing
It has a built-in database of domestic and foreign gas safety regulations (updated in real time), which automatically matches the enterprise's safety system with regulatory requirements (e.g., "whether the pipeline inspection frequency complies with the Technical Code for Operation, Maintenance and Emergency Repair of Urban Gas Facilities") and generates a compliance audit report. It records all safety operations (e.g., hidden danger rectification, training assessment, risk assessment) to form traceable safety files, meeting the inspection requirements of regulatory authorities (files retained for ≥5 years).
Emergency Command System: The "Rapid Response Hub" for Emergencies
Focused on the full-process handling of gas emergencies (e.g., pipeline leaks, station fires, large-scale gas outages), it integrates the capabilities of "data monitoring, plan generation, resource scheduling, and multi-department collaboration" to achieve "scientific decision-making, efficient handling, and minimal losses." Its core functions include:
1. Real-Time Monitoring and Early Warning of Emergencies
It connects to IoT monitoring equipment (laser methane detectors, station smoke detectors, AI-based video surveillance). When abnormalities such as "excessive gas concentration (e.g., ≥5% LEL), flame signals, and sudden drops in pipeline pressure" are detected, it automatically triggers hierarchical early warnings (general, major, significant, particularly significant). It synchronously pushes early warning information to emergency command personnel (via SMS, APP, and pop-ups on the command screen) and links to the GIS system to mark the incident location and surrounding environment (e.g., densely populated areas, schools, hospitals).
2. Intelligent Emergency Plan Generation
Based on the type of emergency (e.g., leak, fire), incident location, and impact scope, it automatically retrieves the "emergency plan database" (with built-in 100+ standardized handling processes, such as the "Handling Plan for DN300 Pipeline Leaks" and "Emergency Plan for LNG Tank Leaks") and optimizes the plan using real-time data (e.g., surrounding population density, location of emergency resources). For example, in a leak incident, it automatically generates "valve-closing route planning (avoiding traffic-congested roads), personnel evacuation scope (500-meter radius), and a list of rescue resource allocations (2 emergency repair vehicles, 5 emergency repair personnel)" with a plan generation time of ≤3 minutes.
3. Visual Scheduling of Emergency Resources
It establishes an emergency resource database (including emergency repair personnel, equipment, materials, and medical rescue forces), which updates the location (based on GPS positioning) and status of resources in real time (e.g., "whether the emergency repair vehicle is idle," "inventory quantity of ventilators") and displays them visually on the command screen. During scheduling, the system automatically recommends the "optimal resource combination" (e.g., "the nearest idle emergency repair team to the incident site + leak-stopping equipment from a nearby reserve warehouse") and supports one-click issuance of scheduling instructions (including location navigation and task description). The resource response time is ≤15 minutes (urban areas) and ≤30 minutes (suburban areas).
4. Multi-Department Collaborative Linkage
It supports system connection with fire, public security, medical, environmental protection, and municipal departments, sharing emergency information in real time (e.g., leak location, impact scope, evacuation route) and receiving feedback on external support (e.g., "arrival time of the fire department," "ambulance route"). For example, in a fire incident, it synchronously pushes fire data to the fire department, receives fire water pressure requirements, and links with the station to adjust water supply valves.
5. Post-Incident Review and Plan Optimization
After the handling of an emergency, it automatically generates an "emergency review report," recording the "cause of the incident, handling process (timeline), resource consumption, handling results, and existing problems." It uses AI analysis to identify shortcomings in the handling process (e.g., "5-minute delay in valve-closing instructions," "insufficient allocation of medical resources"), puts forward plan optimization suggestions (e.g., "adjust the priority of valve-closing routes," "increase the reserve of medical resources in suburban areas"), and updates them to the emergency plan database to improve the efficiency of subsequent handling.
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