Citation

Zhang J, Shi S, Lu Y, You B, Wu F, Wu K. China Saf. Sci. J. 2021; 31(9): 60-66.

Copyright

(Copyright © 2021, China Occupational Safety and Health Association, Publisher Gai Xue bao)

DOI

10.16265/j.cnki.issn1003-3033.2021.09.009

PMID

unavailable

Abstract

In order to solve problem of multi-source, massive, dynamic and complex information processing in the process of symbiotic disaster early warning, data characteristics, application architecture and key technologies of big data intelligent early warning system of gas and coal spontaneous combustion were analyzed by applying big data driven technology, application architecture of big data driven symbiotic disaster early warning system was built, and key of symbiotic disaster intelligent early warning lies in big data acquisition, integration, analysis application and early warning technology was discussed. The research results show that big data driven technology has strong insight, decision-making power and process optimization ability in the intelligent early warning of mine gas and coal spontaneous combustion symbiosis disaster, which can process massive monitoring data of symbiotic disaster timely and efficiently, extract valuable knowledge, and realize the construction of application architecture of symbiotic disaster big data intelligent early warning system. © 2021 China Safety Science Journal. All rights reserved.

Language: zh