Forest Fire Detection System based on Low-Cost Wireless Sensor Network and Internet of Things

Author:

Al-Dahoud Ali1,Fezari Mohamed2,Alkhatib Ahmad AA3,Soltani Mohamed Nadir2,Al-Dahoud Ahmed4

Affiliation:

1. Department of Computer Science, Al Zaytoonah University of Jordan, Airport St, Amman, JORDAN

2. Department of Computer Science, Badji Mokhtar Annaba University, ALGERIA

3. Department of Cyber Security, Al Zaytoonah University of Jordan, Airport St, Amman, JORDAN

4. Faculty of Architecture and Design, Department of Multimedia, Al Zaytoonah University of Jordan, Airport St, Amman, JORDAN

Abstract

Forest fires are one of the most devastating natural disasters that can have a significant impact on the environment, economy, and human lives. Early detection and prompt response are crucial to minimize the damage caused by forest fires. In recent years, Wireless Sensor Networks (WSN) and Internet of Things (IoT) technologies have emerged as promising solutions for forest fire detection due to their low-cost and efficient monitoring capabilities. This paper proposes a low-cost forest fire detection system based on WSN and IoT. The system uses a network of sensor nodes that are strategically placed in the forest to monitor environmental conditions such as temperature, humidity, and smoke. The sensor data is transmitted to a central server, where advanced algorithms are used to detect and predict the occurrence of forest fires. The system provides real-time alerts to forest authorities and users using a mobile application that shows the fire maps and the current updates. The proposed system has been evaluated using based on experiments, and the results show that it can effectively detect forest fires with high accuracy, low false alarms, and low cost. This system has the potential to provide an efficient and cost-effective solution for forest fire detection and can play a vital role in protecting the environment and saving lives.

Publisher

World Scientific and Engineering Academy and Society (WSEAS)

Subject

General Energy,General Environmental Science,Geography, Planning and Development

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Forest Fire identification: Harnessing Internet of Things (IoT) and Artificial Intelligence;2024 1st International Conference on Cognitive, Green and Ubiquitous Computing (IC-CGU);2024-03-01

2. Optimizing Sensor Node Placement for Forest Fire Prevention Using Clustering and Regression;2023 22nd Mediterranean Microwave Symposium (MMS);2023-10-30

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