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

https://doi.org/10.18535/ijsrm/v12i04.ec01
Classification model, Data Mining, Feature selection algorithms, Fuzzy logic and Internal and External factors

Authors

  • Md. Ahsan Arif Department of Computer Science and Engineering, University of Scholars, Dhaka,, Bangladesh
  • Golam Kaderye Department of Computer Science and Engineering, University of Scholars, Dhaka, , Bangladesh
  • Md. Appel Mahmud Akib Department of Computer Science and Engineering, Asian University of Bangladesh, Dhaka, , Bangladesh
  • Shah Syed Md. Fehir Department of Computer Science and Engineering, Asian University of Bangladesh, Dhaka, , Bangladesh
  • Farhana Mimi Shuma Department of Computer Science and Engineering, Asian University of Bangladesh, Dhaka, , Bangladesh
Vol. 12 No. 04 (2024)
Engineering and Computer Science
April 4, 2024

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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.