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Smart Fire Detection and Deterrent System for Human Savior by Using Internet of Things (IoT)

Author

Listed:
  • Abdul Rehman

    (Department of Computer Science & IT, Superior University, Lahore 54000, Pakistan)

  • Muhammad Ahmed Qureshi

    (Department of Computer Science & IT, The Islamia University Bahawalpur, Bahawalpur 63100, Pakistan)

  • Tariq Ali

    (Department of Computer Science, Sahiwal Campus, COMSATS University Islamabad, Sahiwal 57000, Pakistan)

  • Muhammad Irfan

    (Electrical Engineering Department, College of Engineering, Najran University, Najran 61441, Saudi Arabia)

  • Saima Abdullah

    (Department of Computer Science & IT, The Islamia University Bahawalpur, Bahawalpur 63100, Pakistan)

  • Sana Yasin

    (Department of Computer Science, University of Okara, Okara 56300, Pakistan)

  • Umar Draz

    (Department of Computer Science, University of Sahiwal, Sahiwal 57000, Pakistan)

  • Adam Glowacz

    (Department of Automatic Control and Robotics, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, AGH University of Science and Technology, al. A. Mickiewicza 30, 30-059 Kraków, Poland)

  • Grzegorz Nowakowski

    (Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155 Krakow, Poland)

  • Abdullah Alghamdi

    (College of Computer Science and Information Systems, Najran University, Najran 61441, Saudi Arabia)

  • Abdulaziz A. Alsulami

    (Department of Information Systems, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Mariusz Węgrzyn

    (Faculty of Electrical and Computer Engineering, Cracow University of Technology, Warszawska 24, 31-155 Krakow, Poland)

Abstract

Fire monitoring systems have usually been based on a single sensor such as smoke or flame. These single sensor systems have been unable to distinguish between true and false presence of fire, such as a smoke from a cigarette which might cause the fire alarm to go off. Consuming energy all day long and being dependent on one sensor that might end with false alert is not efficient and environmentally friendly. We need a system that is efficient not only in sensing fire accurately, but we also need a solution which is smart. In order to improve upon the results of existing single sensor systems, our system uses a combination of three sensors to increase the efficiency. The result from the sensor is then analyzed by a specified rule-set using an AI-based fuzzy logic algorithm; defined in the purposed research, our system detects the presence of fire. Our system is designed to make smart decisions based on the situation; it provides feature updated alerts and hardware controls such as enabling a mechanism to start ventilation if the fire is causing suffocation, and also providing water support to minimize the damage. The purposed system keeps updating the management about the current severity of the environment by continually sensing any change in the environment during fire. The purposed system proved to provide accurate results in the entire 15 test performed around different intensities of a fire situation. The simulation work for the SMDD is done using MATLAB and the result of the experiments is satisfactory.

Suggested Citation

  • Abdul Rehman & Muhammad Ahmed Qureshi & Tariq Ali & Muhammad Irfan & Saima Abdullah & Sana Yasin & Umar Draz & Adam Glowacz & Grzegorz Nowakowski & Abdullah Alghamdi & Abdulaziz A. Alsulami & Mariusz , 2021. "Smart Fire Detection and Deterrent System for Human Savior by Using Internet of Things (IoT)," Energies, MDPI, vol. 14(17), pages 1-30, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:17:p:5500-:d:628440
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    References listed on IDEAS

    as
    1. Ayaz Hussain & Umar Draz & Tariq Ali & Saman Tariq & Muhammad Irfan & Adam Glowacz & Jose Alfonso Antonino Daviu & Sana Yasin & Saifur Rahman, 2020. "Waste Management and Prediction of Air Pollutants Using IoT and Machine Learning Approach," Energies, MDPI, vol. 13(15), pages 1-22, August.
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