Decentralized IoT Emergency Platform for Cross-Department Dispatch
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Solution Overview
Problem
Current emergency management systems in smart cities face challenges in integrating and analyzing extensive and complex data sources, leading to information silos and inefficiencies in resource allocation and emergency response.
Innovation Solution
A method and system for smart city decentralized emergency management based on an IoT large model, utilizing an emergency supervisory management platform to process data, determine data criticality and emergency features, and control emergency rescue vehicles through a closed-loop information system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If extensive and complex data sources are collected from multiple departments, then the comprehensiveness of emergency monitoring is improved, but data integration and sharing becomes difficult leading to information silos
Solution Approach 1:
The system segments data processing by establishing separate data collection modules for different departments (fire safety, traffic management, public security, etc.) while integrating them through a unified emergency management platform. Each department's data is collected independently but then synthesized at the platform level, resolving the contradiction between comprehensive data collection and integration complexity.
Solution Approach 2:
The emergency management platform serves as an intermediary between various departmental data sources. It provides standardized interfaces and protocols that facilitate data sharing while maintaining the independence of each department's data collection system, thus reducing integration complexity despite having extensive data sources.
2Measurement precision
If data from multiple sources is collected to improve monitoring comprehensiveness, then the accuracy of emergency identification is improved, but the speed of identifying priority and criticality decreases
Solution Approach 1:
The system performs preliminary data processing and feature extraction at the data collection stage, pre-tagging and categorizing data from different departments before it enters the central platform. This preliminary organization enables faster identification of emergency priorities when data arrives, as the data is already structured and ready for rapid analysis.
Solution Approach 2:
The system extracts and prioritizes critical features from the extensive data sources automatically. By identifying and separating the most important emergency-related information from the broader data set, the system maintains high identification accuracy while reducing the processing time required to analyze all available data.
3Productivity
If decentralized emergency management is implemented to improve response efficiency, then the speed of emergency response is improved, but the complexity of coordinating between different platforms increases
Solution Approach 1:
The emergency management platform is designed with multi-functionality to handle various types of emergency data and control operations from different departments. By making the platform universal and adaptable to different emergency scenarios and departmental requirements, the system achieves efficient decentralized response while simplifying coordination through a unified interface and standardized protocols.
Data Source
AI summary
The present disclosure relates to a method and a system for smart city decentralized emergency management based on an Internet of Things large model, the method includes: determining at least one incident based on target data; determining a data criticality level and a data emergency feature based on the target data, a data basic feature, the at least one incident and a data anomaly feature; determining at least one target sub-platform based on the target data, the data anomaly feature and a division condition; determining emergency parameters based on the emergency type, the emergency level and the data emergency feature; determining operating parameters of an emergency rescue vehicle based on the emergency level, the emergency parameters and the data emergency feature; generating and transmitting a dispatch instruction based on the emergency parameters and operating parameters; and controlling the emergency rescue vehicle to move to the geographic region.