4.5 Article

Recognition of IoT-based fire-detection system fire-signal patterns applying fuzzy logic

Journal

HELIYON
Volume 9, Issue 2, Pages -

Publisher

CELL PRESS
DOI: 10.1016/j.heliyon.2023.e12964

Keywords

IoT-based fire-detection system; Unwanted fire alarm; False alarm rate

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The use of IoT technology in fire-detection systems has increased in Korea due to communication technology convergence and the proliferation of IoT. However, there has been a lack of research based on actual operational data. This study investigates actual fire accidents over a 5-year period and develops a fuzzy logic system for recognizing fire signal patterns.
Article history: In Korea, the use of fire-detection systems applying IoT technology to existing analog fire-alarm systems has increased owing to the communication technology convergence, the world's best Internet network, and the proliferation of Internet of Things (IoT). Its use can be expected to increase worldwide in the future. For IoT-based fire-detection systems to exhibit the requisite reliability (based on a low false-alarm rate), research related to the analysis of detection signals should be actively promoted and conducted. However, there has been no research activity based on actual operational data, apart from the research that has been conducted in laboratory environments. The primary reason for this state of affairs has been that the installation and use of IoT-based fire-detection systems on a large scale has been rare, worldwide. Consequently, with respect to the fire-signal characteristics of IoT-based fire-detection systems, related data in this study were obtained by investigating actual fire accident cases, using fire alarm data that occurred over a period of 5 years. Based on the signal pattern analysis results using these field data, a fuzzy logic system for recognizing fire signal patterns was developed and verified. As a result, in the actual fire accidents examined, an alarm condition-corresponding to the high possibility of fire among the five fire alarms-was determined 30 s before the actual fire alarm. Moreover, it was also found that approximately 80% of non-fire alarms could be reduced in the actual fire alarms that occurred at Institute K during the 5-year period examined.

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