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  • 标题:Research on High-rise Building Fire Early Warning System Based on Multidimensional Data Fusion
  • 本地全文:下载
  • 作者:Shengli Kong ; Xinmei Fang ; Pengfei Yang
  • 期刊名称:E3S Web of Conferences
  • 印刷版ISSN:2267-1242
  • 电子版ISSN:2267-1242
  • 出版年度:2021
  • 卷号:257
  • 页码:1-5
  • DOI:10.1051/e3sconf/202125703044
  • 语种:English
  • 出版社:EDP Sciences
  • 摘要:With the rapid development of urban construction and the increasing number of high-rise buildings, many problems have arisen, one of which is fire. High-rise building fires are developing rapidly, and it is difficult to extinguish them, which causes great losses and seriously threatens people’s safety in production and life. Early warning of high-rise building fire is an important means to prevent fire. In this paper, aiming at high-rise building fires, the causes of high-rise building fires in 2019 are analyzed statistically, and the causes of high-rise building fires are summarized. An intelligent early warning system of high-rise building fire based on multi-dimensional data fusion is proposed. Based on the actual forecast data, the early warning system based on multi-dimensional data fusion is analyzed through Matlab simulation, thus verifying the feasibility and reliability of the established fire early warning system. The research results have certain guiding significance for high-rise building fire warning.
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