Open Access
Int. J. Metrol. Qual. Eng.
Volume 13, 2022
Article Number 7
Number of page(s) 13
Published online 05 July 2022
  1. R. Ghali, M. Jmal, M.W. Souidene, R. Attia, Recent advances in fire detection and monitoring systems: a review, Springer Proc. Phys. 146, 332–340 (2020) [Google Scholar]
  2. F. Yang, Z. Cai, L. Su, Y. Xue, Y. Shen, J. Wang, Research on fire source localization in confined space based on the fire characteristic physical quantity information, Int. J. Metrol. Qual. Eng. 13, 1–8 (2022) [CrossRef] [EDP Sciences] [Google Scholar]
  3. V. Hristidis, S. Chen, T. Li, Survey of data management and analysis in disaster situations, J. Syst. Softw. 83, 1701–1714 (2010) [CrossRef] [Google Scholar]
  4. Y. Luo, Q. Li, L. Jiang, Analysis of Chinese fire statistics during the period 1997–2017, Fire. Saf. J. 125 (2021) [Google Scholar]
  5. T. Buffington, O.A. Ezekoye, Statistical analysis of fire department response times and effects on fire outcomes in the United States, Fire. Technol. 55, 2369–2393 (2019) [CrossRef] [Google Scholar]
  6. Y. Li, Design of integrated fire protection system for building electrical fire based on multi-sensor data fusion, Proc. SPIE-Int. Soc. Opt. Eng. 11930 (2021) [Google Scholar]
  7. X. Yang, K. Zhang, Y. Chai, A multi-sensor characteristic parameter fusion analysis based electrical fire detection model, Lect. Notes Electr. Eng. 528, 397–410 (2019) [CrossRef] [Google Scholar]
  8. D. Sahid, M. Alaydrus, Multi sensor fire detection in low voltage electrical panel using modular fuzzy logic, Int. Conf. Broadband Commun. (2020) [Google Scholar]
  9. C. Zhang, Y. Feng, Design of multi-sensor combined detector for electric fire, Fire. Sci. Technol. 35, 1726–1728 (2016) [Google Scholar]
  10. P. Sridhar, R.R. Sathiya, Computer vision based early electrical fire-detection in video surveillance oriented for building environment, J. Phys. Conf. Ser. 1916, 275–286 (2021) [Google Scholar]
  11. D. Zhao, H. Liu, Application of intelligent electricity monitoring system in electrical fire, Fire. Sci. Technol. 37, 1697–1700 (2018) [Google Scholar]
  12. C. Yang, X. You, Design of electric fire monitoring system for urban commercial complex, Fire. Sci. Technol. 37, 1239–1241 (2018) [Google Scholar]
  13. Y. Zhao, Y. Wang, Y. Liu, Ancient building electrical fire early warning system based on JenNet wireless technology, Proc. Chin. Control. Decis. Conf. 21, 6301–6304 (2016) [Google Scholar]
  14. L. Zhang, Y. Wang, Design of monitoring system for electrical fire disaster of high-rise buildings based on ZigBee, Acta. Tech. CSAV. 61, 225–236 (2016) [Google Scholar]
  15. M. Zhang, M. Di, D. Xia, Applications of metallographic analysis software in electrical fire evidence identification, J. Northeast. Univ. 33, 21–24 (2012) [Google Scholar]
  16. D. Gao, Q. Liu, Review of the research on the identification of electrical fire trace evidence, Proc. Eng. 135, 29–32 (2016) [CrossRef] [Google Scholar]
  17. M.K. Ngo, V.D. Le, D.T. Doan, An advanced IoT system for monitoring and analysing chosen power quality parameters in micro-grid solution, Arch. Electr. Eng. 70, 173–188 (2021) [Google Scholar]
  18. H. Ge, B. Xu, W. Chen, Topology identification of low voltage distribution network based on current injection method, Arch. Electr. Eng. 70, 297–306 (2021) [Google Scholar]
  19. C. He, Qi. Su, C. Li, Research on the cause of building fire using social network analysis, IEEE Int. Conf. Ind. Eng. Appl. 12, 958–962 (2020) [Google Scholar]
  20. J. Zhang, L. Huang, T. Chen, Simulation based analysis of electrical fire risks caused by poor electric contact between plug and receptacle, Fire. Saf. J. 126, 13–24 (2021) [Google Scholar]
  21. K. Yang, R. Zhang, J. Yang, A novel arc fault detector for early detection of electrical fires, Sensors 16, 500–513 (2016) [CrossRef] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.