IoT Rescue Resource Allocation in Smart Cities
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Solution Overview
Problem
Existing methods for determining an allocation scheme of accident rescue resources in smart cities are inefficient, as they fail to provide real-time resource allocation during emergencies, leading to delays and misallocation of resources.
Innovation Solution
An Internet of Things (IoT) system comprising a user platform, service platform, management platform, and sensor network platform, which collects accident information, determines resource demand, identifies available resources, and allocates rescue resources based on demand and availability, facilitating quick and efficient resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual resource allocation methods are used, then system complexity is reduced, but resource allocation efficiency and timeliness deteriorate
Solution Approach 1:
The system is divided into five distinct platforms: object platform for data collection, sensor network platform for transmission, management platform for processing, service platform for coordination, and user platform for delivery. This segmentation allows automated resource allocation while managing complexity through modular design, where each platform handles specific functions independently.
Solution Approach 2:
The management platform acts as an intermediary between the sensor network platform and service platform, processing accident information and determining resource demands. This intermediary layer automates the allocation decision-making process, improving efficiency while keeping the overall system manageable through clear role definition.
2Loss of time
If real-time automated resource allocation is implemented, then resource allocation timeliness is improved, but system complexity increases
Solution Approach 1:
The system pre-establishes the five-platform architecture and defines clear protocols for information flow and resource allocation. By preparing the system structure in advance with predetermined roles and communication channels, real-time automated allocation can occur without ad-hoc decision-making, reducing time loss while maintaining manageable complexity through pre-planning.
3Measurement precision
If comprehensive accident information collection is performed, then resource demand determination accuracy is improved, but information processing complexity increases
Solution Approach 1:
The information processing function is segmented across multiple platforms: the object platform collects raw accident information, the sensor network platform transmits it, and the management platform processes it to determine resource demands. This segmentation distributes processing complexity while maintaining comprehensive data collection and high determination accuracy through specialized functions at each level.
Data Source
AI summary
The present disclosure provides a method for determining an allocation scheme of accident rescue resource in a smart city. The method comprises: obtaining accident information of an accident point based on the object platform; sending the accident information to the management platform based on the sensor network platform; determining resource demand of the accident point based on the accident information through the management platform; obtaining available resource of at least one candidate rescue point based on the object platform; sending the available resource to the management platform based on the sensor network platform; determining the allocation scheme of rescue resource based on the resource demand and the available resource through the management platform; and sending the allocation scheme of rescue resource to the user platform through the service platform.