ID2S4FH: A Novel Framework of Intelligent Decision Support System for Fire Hazards
Modern societies and industrial sectors are serviced through storage and distribution centres (SDCs) such as supermarkets, malls, warehouses, etc. Large quantities of supplies are stocked here, e.g., food grains, clothes, shoes, pharmaceuticals, electronics, plastics, edible oils, electrical wires/e...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-06-01
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| Series: | Fire |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2571-6255/6/7/248 |
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| author | Kanak Kumar Navin Singh Rajput Alexey V. Shvetsov Abdu Saif Radhya Sahal Saeed Hamood Alsamhi |
| author_facet | Kanak Kumar Navin Singh Rajput Alexey V. Shvetsov Abdu Saif Radhya Sahal Saeed Hamood Alsamhi |
| author_sort | Kanak Kumar |
| collection | DOAJ |
| description | Modern societies and industrial sectors are serviced through storage and distribution centres (SDCs) such as supermarkets, malls, warehouses, etc. Large quantities of supplies are stocked here, e.g., food grains, clothes, shoes, pharmaceuticals, electronics, plastics, edible oils, electrical wires/equipment, petroleum products, painting materials, etc. Fires due to the burning of these materials are categorized into six classes, viz., Class A, Class B, Class C, Class D, Class K, and Class F. A fire is extinguished better when the right type of fire retardant is used. A thumb rule on firefighting also says, “never fight a fire if you do not know what is burning”. In this paper, we have proposed an Intelligent Decision Support System (ID2S4FH) to generate a real-time ‘fire-map’ of such SDCs during a fire hazard. We have interfaced six tin-oxide-based gas sensor elements, a temperature and humidity sensor, and a particulate matter (PM) sensor with microcontrollers to capture the real-time signature patterns of the ambient air. We burned sixteen different types of materials belonging to six classes of fire and created a dataset consisting of 2400 samples. The sensor array responses were then pre-processed and analysed using various classifiers trained in different analysis space domains. Among the classifiers, four classifiers achieved ‘all correct’ identification of the fire classes of 80 unknown test samples, and the lowest mean squared error (MSE) achieved was 2.81 × 10<sup>−3</sup>. During a fire hazard, our proposed ID2S4FH can generate real-time fire maps of SDCs and help firefighters to extinguish the fire using the appropriate fire retardant. |
| first_indexed | 2024-03-11T01:05:41Z |
| format | Article |
| id | doaj.art-6dc1356ea70d47f787fc7b7bb36fc33d |
| institution | Directory Open Access Journal |
| issn | 2571-6255 |
| language | English |
| last_indexed | 2024-03-11T01:05:41Z |
| publishDate | 2023-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fire |
| spelling | doaj.art-6dc1356ea70d47f787fc7b7bb36fc33d2023-11-18T19:17:20ZengMDPI AGFire2571-62552023-06-016724810.3390/fire6070248ID2S4FH: A Novel Framework of Intelligent Decision Support System for Fire HazardsKanak Kumar0Navin Singh Rajput1Alexey V. Shvetsov2Abdu Saif3Radhya Sahal4Saeed Hamood Alsamhi5Department of Electronics Engineering, Indian Institute of Technology (BHU), Varanasi 221005, IndiaDepartment of Electronics Engineering, Indian Institute of Technology (BHU), Varanasi 221005, IndiaDepartment of Smart Technologies, Moscow Polytechnic University, St. Bolshaya Semenovskaya, 38, 107023 Moscow, RussiaDepartment of Communication and Computer Engineering, Faculty of Engineering and IT, Taiz University, Taiz P.O. Box 6803, YemenSchool of Computer Science and IT, University College Cork, T12 K8AF Cork, IrelandFaculty of Engineering, IBB University, Ibb P.O. Box 70270, YemenModern societies and industrial sectors are serviced through storage and distribution centres (SDCs) such as supermarkets, malls, warehouses, etc. Large quantities of supplies are stocked here, e.g., food grains, clothes, shoes, pharmaceuticals, electronics, plastics, edible oils, electrical wires/equipment, petroleum products, painting materials, etc. Fires due to the burning of these materials are categorized into six classes, viz., Class A, Class B, Class C, Class D, Class K, and Class F. A fire is extinguished better when the right type of fire retardant is used. A thumb rule on firefighting also says, “never fight a fire if you do not know what is burning”. In this paper, we have proposed an Intelligent Decision Support System (ID2S4FH) to generate a real-time ‘fire-map’ of such SDCs during a fire hazard. We have interfaced six tin-oxide-based gas sensor elements, a temperature and humidity sensor, and a particulate matter (PM) sensor with microcontrollers to capture the real-time signature patterns of the ambient air. We burned sixteen different types of materials belonging to six classes of fire and created a dataset consisting of 2400 samples. The sensor array responses were then pre-processed and analysed using various classifiers trained in different analysis space domains. Among the classifiers, four classifiers achieved ‘all correct’ identification of the fire classes of 80 unknown test samples, and the lowest mean squared error (MSE) achieved was 2.81 × 10<sup>−3</sup>. During a fire hazard, our proposed ID2S4FH can generate real-time fire maps of SDCs and help firefighters to extinguish the fire using the appropriate fire retardant.https://www.mdpi.com/2571-6255/6/7/248fire detectionPM 10PM 2.5particulate matterArduino UNOIntelligent Gas Sensor System (IGSS) |
| spellingShingle | Kanak Kumar Navin Singh Rajput Alexey V. Shvetsov Abdu Saif Radhya Sahal Saeed Hamood Alsamhi ID2S4FH: A Novel Framework of Intelligent Decision Support System for Fire Hazards Fire fire detection PM 10 PM 2.5 particulate matter Arduino UNO Intelligent Gas Sensor System (IGSS) |
| title | ID2S4FH: A Novel Framework of Intelligent Decision Support System for Fire Hazards |
| title_full | ID2S4FH: A Novel Framework of Intelligent Decision Support System for Fire Hazards |
| title_fullStr | ID2S4FH: A Novel Framework of Intelligent Decision Support System for Fire Hazards |
| title_full_unstemmed | ID2S4FH: A Novel Framework of Intelligent Decision Support System for Fire Hazards |
| title_short | ID2S4FH: A Novel Framework of Intelligent Decision Support System for Fire Hazards |
| title_sort | id2s4fh a novel framework of intelligent decision support system for fire hazards |
| topic | fire detection PM 10 PM 2.5 particulate matter Arduino UNO Intelligent Gas Sensor System (IGSS) |
| url | https://www.mdpi.com/2571-6255/6/7/248 |
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