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