Recognition of IoT-based fire-detection system fire-signal patterns applying fuzzy logic
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 expect...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2023-02-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023001718 |
| _version_ | 1811161863200702464 |
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| author | Seung Hwan Park Doo Hyun Kim Sung Chul Kim |
| author_facet | Seung Hwan Park Doo Hyun Kim Sung Chul Kim |
| author_sort | Seung Hwan Park |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-10T06:20:54Z |
| format | Article |
| id | doaj.art-ba001fd7ec7b435faf0d8f1c499e2bb0 |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-10T06:20:54Z |
| publishDate | 2023-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-ba001fd7ec7b435faf0d8f1c499e2bb02023-03-02T04:59:50ZengElsevierHeliyon2405-84402023-02-0192e12964Recognition of IoT-based fire-detection system fire-signal patterns applying fuzzy logicSeung Hwan Park0Doo Hyun Kim1Sung Chul Kim2Laboratory Safety Management Team, Korea Atomic Energy Research Institute, South KoreaDepartment of Safety Engineering, Chungbuk National University, South Korea; Corresponding author.Department of Safety Engineering, Chungbuk National University, South KoreaArticle 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.http://www.sciencedirect.com/science/article/pii/S2405844023001718IoT-based fire-detection systemUnwanted fire alarmFalse alarm rate |
| spellingShingle | Seung Hwan Park Doo Hyun Kim Sung Chul Kim Recognition of IoT-based fire-detection system fire-signal patterns applying fuzzy logic Heliyon IoT-based fire-detection system Unwanted fire alarm False alarm rate |
| title | Recognition of IoT-based fire-detection system fire-signal patterns applying fuzzy logic |
| title_full | Recognition of IoT-based fire-detection system fire-signal patterns applying fuzzy logic |
| title_fullStr | Recognition of IoT-based fire-detection system fire-signal patterns applying fuzzy logic |
| title_full_unstemmed | Recognition of IoT-based fire-detection system fire-signal patterns applying fuzzy logic |
| title_short | Recognition of IoT-based fire-detection system fire-signal patterns applying fuzzy logic |
| title_sort | recognition of iot based fire detection system fire signal patterns applying fuzzy logic |
| topic | IoT-based fire-detection system Unwanted fire alarm False alarm rate |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023001718 |
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