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Forest Fire Detection Using IoT: A Systematic Review

Prof. KAPIL PADLAK, LEELADHAR BISANDRE, HIVRAJ PAWAR

Abstract


This paper presents a complete design, implementation, and evaluation of a forest fire detection system built on Internet of Things (IoT) principles and presented in IEEE-style format. The proposed system integrates a network of low-cost sensor nodes (temperature, humidity, smoke, CO), microcontroller-based edge processing, and a multi-tier communication architecture (local gateway → cloud). Detection is performed using a rule-based thresholding stage followed by a lightweight machine learning classifier on the gateway for improved false alarm suppression. The system supports real-time alerts (SMS/Push), geolocation tagging, and dashboard visualisation. We evaluate the system through controlled experiments and simulations and report metrics including detection accuracy, false alarm rate, detection latency, energy consumption, and network overhead. Results show that the combined threshold+ML approach reaches high detection accuracy while maintaining low energy use, making it suitable for wide-area forest deployments.


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References


Montaser N. A. Ramadan, Tasnim Basmaji, Abdalla Gad, Hasan Hamdan, Bekir T. Akgün, Mohammed A. H. Ali, Mohammad Alkhedher, Mohammed Ghazal, “Towards early forest fire detection and prevention using AI-powered drones and the IoT,” Internet of Things, vol. 27, 2024, Article 101248.

Sabina Jangirova, Branislava Jankovic, Waseem Ullah, Latif U. Khan, Mohsen Guizani, “Real-Time Aerial Fire Detection on Resource-Constrained Devices Using Knowledge Distillation,” preprint (arXiv), 2025.

Kenneth Bonilla-Ormachea, Horacio Cuizaga, Edwin Salcedo, Sebastian Castro, Sergio Fernandez-Testa, Misael Mamani, “ForestProtector: An IoT Architecture Integrating Machine Vision and Deep Reinforcement Learning for Efficient Wildfire Monitoring,” preprint (arXiv), 2025.

Dimitrios Meimetis, Sofia Papaioannou, Paraskevi Katsoni, Vaios Lappas, “An Architecture for Early Wildfire Detection and Spread Estimation Using Unmanned Aerial Vehicles, Base Stations, and Space Assets,” Drones and Autonomous Vehicles, 2024. SCIE Publish.

S. Manoj, C. Valliyammai, “Drone network for early warning of forest fire and dynamic fire quenching plan generation,” EURASIP Journal on Wireless Communications and Networking, 2023, Article number: 112.

R. Anand, P. Monisha, T. Nathiya, S. Karthik, “LoRa IoT Network for Instant Forest Fire Detection and Alert System,” Scientific Research, New Technologies and Applications, vol. 7, 2024.

Ahmet Aytuğ Ayrancı, Burcu Erkmen, “IoT-based fire detection: A comparative study of machine learning techniques,” NGÜMUH Journal, vol. 13, issue 4, 2024.

Anjitha Mary Paul, Jency Varghese, Safna Nasimudeen, Anusree K. Sanil, Esraa Alqasmy, “AI-Based Forest Fire Detection Using Satellite Imagery: Challenges, Advances, and a Framework for Real-Time Alarm Systems,” Annals of Engineering Mathematics and Computational Intelligence, vol. 2, no. 1, 2025.

“Deep Learning Approaches for Forest Fires Detection and Prediction using satellite Images,” Procedia Computer Science, vol. 251, 2024, pp. 758–763.


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