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Improved the accuracy of IOT based LPG leakage detection system with early fire prediction and smart alert

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  • Golam Kaderye,
  • Md. Ahsan Arif,
  • Md. Appel Mahmud Akib,
  • Shah Syed Md. Fehir,
  • Farhana Mimi Shuma
Golam Kaderye
Department of Computer Science and Engineering, University of Scholars, Dhaka,
Md. Ahsan Arif
Department of Computer Science and Engineering, University of Scholars, Dhaka,
Md. Appel Mahmud Akib
Department of Computer Science and Engineering, Asian University of Bangladesh, Dhaka,
Shah Syed Md. Fehir
Department of Computer Science and Engineering, Asian University of Bangladesh, Dhaka,
Farhana Mimi Shuma
Department of Computer Science and Engineering, Asian University of Bangladesh, Dhaka,
Published in : International Journal of Scientific Research and Management (IJSRM) , Vol. 12 No. 04 (2024)

Published 2024-04-04

Keywords

  • Classification model, Data Mining, Feature selection algorithms, Fuzzy logic and Internal and External factors

Copyright (c) 2024 Golam Kaderye, Md. Ahsan Arif, Md. Appel Mahmud Akib, Shah Syed Md. Fehir, Farhana Mimi Shuma

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

Safety is of utmost importance in the realm of smart cities, smart homes, and industries. Among the various safety measures implemented in a smart city, the detection of gas leakage and the prevention of mass fires are crucial for safeguarding lives and valuable assets. This research paper introduces a novel system that not only detects gas leakage but also provides early predictions of fire outbreaks. Unlike the conventional gas leakage detectors available in the market, which only alert when the gas concentration reaches a high level, our system utilizes fuzzy logic, environmental temperature, and humidity to accurately detect gas concentration levels and predict early fire symptoms. By employing the Internet of Things (IoT) approach, this system promptly sends notifications and sensor readings to the relevant individuals, enabling them to take immediate action and prevent extensive damage.

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