A Spark-based method for analyzing evacuation risks in subway stations.
By using Spark-based distributed streaming processing framework to build a data warehouse in the subway station, and using parallel association rule algorithms to analyze evacuation risk indicators, the problem of untimely evacuation after subway station accidents is solved, effective analysis and prevention of evacuation risks is achieved, and the safety of subway stations is improved.
CN114266472BActive Publication Date: 2025-03-28SHANGHAI INST OF TECH
2 Cites 0 Cited by
Patent Information
- Application Number
- CN202111570993.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2021-12-21
- Publication Date
- 2025-03-28
- Estimated Expiration
- 2041-12-21
AI Technical Summary
Technical Problem
The subway station was not evacuated in time and effectively after the accident, resulting in the expansion of the severity of the accident and the existing technology is difficult to effectively analyze and prevent evacuation risks.
Method used
A distributed streaming processing framework based on Spark is used to build a data warehouse, evacuation risk indicators are determined through cause analysis, and a parallel association rule algorithm is used to mine and analyze risk indicators to establish a risk analysis model.
Benefits of technology
It can promptly detect hidden dangers of emergency evacuation of subway stations, put forward targeted prevention measures and suggestions, improve the safety of subway stations, and reduce the possibility of major accidents.
✦ Generated by Eureka AI based on patent content.
Abstract
The present invention provides a subway station evacuation risk analysis method based on Spark, including performing cause analysis on historical related accidents of subway station evacuation failure, determining the main risk factors that caused the accident, classifying the main factors, and determining the evacuation risk index; building a distributed Spark Streaming framework to build a data warehouse, processing the data of the evacuation risk index in the data warehouse, and establishing a risk index library; using an association rule algorithm and a parallel association rule mining algorithm to perform mining analysis on each of the evacuation risk indicators, and establishing a risk analysis model of a parallel association rule mining algorithm. The present invention completes the data processing work by building a data warehouse, uses a parallelized association rule mining algorithm and an association rule algorithm to further analyze and mine the risk indicator data, outputs the risk analysis results through the obtained risk analysis model, and finally gives countermeasures according to the risk analysis results.
Need to check novelty before this filing date? Find Prior Art