China Safety Science Journal ›› 2024, Vol. 34 ›› Issue (12): 94-99.doi: 10.16265/j.cnki.issn1003-3033.2024.12.0688

• Safety engineering technology • Previous Articles     Next Articles

Intelligent analysis of building fire accidents based on knowledge graph

XU Hui1,2(), JIANG Mei3, XUE Hong4, ZHOU Qilin5   

  1. 1 College of Economics and Management, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
    2 Key Laboratory of Big Data Intelligent Computing, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
    3 College of Science, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
    4 School of Management, Shandong University, Jinan Shandong 250100, China
    5 Chongqing Major Projects Service Centre, Chongqing Regional Cooperation Service Centre, Chongqing 401120, China
  • Received:2024-09-05 Revised:2024-11-07 Online:2024-12-28 Published:2025-06-28

Abstract:

To provide intelligent and systematic decision support for building safety management, building fire accidents data was collected and summarized. The knowledge graph of building fire accidents was developed to construct a knowledge graph database. Based on the dimensions of time, space, theme, and important entities, the implementation process of the intelligent question-answering system was innovatively presented. Moreover, the intelligent analysis of building fire risk was performed. The results showed that daytime and summer were high-risk periods for building fires. The frequency of building fire accidents in East China was significantly higher than that in other regions, and the fire risk of building fires was higher in electrical and warehouse areas. Reinforced concrete frame structures and factory buildings were more prone to building fires. Most ignition sources were combustible solids, and the main cause of fire accidents was illegal construction behavior.

Key words: knowledge graph, building fire accident, intelligent analysis, safety management, graph database

CLC Number: