@article{article_1482838, title={Advancements in Intelligent Technologies Approaches for Forest Fire Detection: A Comparative Study}, journal={European Journal of Forest Engineering}, volume={11}, pages={66–80}, year={2025}, DOI={10.33904/ejfe.1482838}, author={Sairi, Amira and Labed, Said and Miles, Badreddine}, keywords={Forest fire, satellites, drones, Wireless Sensor Networks, Internet of Things, Deep Learning, Camera}, abstract={Forest fires pose a significant threat to ecosystems, wildlife, and communities worldwide, leading to severe environmental impacts such as soil degradation, reduced air quality, and increased greenhouse gas emissions. Effective forest fire prevention and management are a critical global challenge, with detection and suppression technologies constantly evolving. This paper provides a comparative study of various forest fire detection techniques, including watchtowers, satellites, wireless sensor networks (WSN), cameras, and drone systems. By examining the advantages and limitations of each method, the paper highlights specific examples of recent research using Artificial Intelligence (AI) and Internet of Things (IoT) technologies to illustrate their effectiveness and the problems. A detailed comparison table is included to summarize the performance and applicability of these techniques. The study concludes by evaluating the current state of fire detection technologies and proposing future research directions to enhance early fire detection systems. This comprehensive review aims to inform ongoing efforts in wildfire management and advance the development of more efficient detection strategies.}, number={1}, publisher={Forest Engineering and Technologies Platform}