Aswin A., Thulasi Ram E., Lokesh Kumar Reddy K., Pavan Kumar K., Ajay Kumar Reddy P
The problem of wildfires has become more common, leading to environmental degradation, loss of biodiversity, economic losses, and hazards to people’s lives. The necessity to detect such wildfires quickly and effectively has led to the development and implementation of intelligent solutions that overcome the drawbacks of traditional approaches. This research study provides an analysis of the recent developments in Wireless Sensor Networks (WSNs), Internet of Things (IoT), Artificial Intelligence (AI), and Unmanned Aerial Vehicle (UAV)-based wildfire monitoring systems along with the underlying communication technologies and open source datasets used for intelligent fire detection. It has been found from the reviewed research papers that the technologies offer distinct advantages in terms of distributed sensing, communication, aerial imaging, and intelligent data analysis; nevertheless, the implementation of individual technology has certain limitations in terms of scalability, energy consumption, communication reliability, and adaptability. The analysis reveals that hybrid architectures integrating WSNs, IoT, UAVs, and AI make efficient use of the inherent capabilities of each technology to enhance accuracy in detection, coverage in monitoring, awareness in situational assessment, and decision-making. Lastly, this research study explores the critical research gaps, presents emerging challenges, and identifies promising areas for future research in wildfire monitoring.