Abstract
Forests are crucial resources for human existence and social progress because they safeguard the earth's natural balance.However, forest fires occur regularly as a result of unmanaged human activities and erratic environmental conditions.These fires are the most destructive natural disasters to forest resources and the human environment.Forest fires have become more common in this scenario as a result of climate change, human activity, and other things.Forest fire detection and monitoring has become a global problem for forest fire prevention organisations.Currently, forest fire detection methods mostly include vigils, observation from watch towers, and, more recently, satellite monitoring.Although observation from watch towers is simple and feasible, there are various obstacles.First and foremost, this strategy requires Keywords - Wireless sensor networks(WSN), Computer vision, aerial vehicles(UAV), YOLO, Internet of things(IOT), Moderate Resolution Imaging Spectroradiometer(MODIS), mAP (mean Average Precision) Many financial and material resources, as well as a skilled labour force.Second, there are numerous issues with fire protection manpower, such as inattention, absenteeism from the post, a lack of real-time monitoring capability, and limited area coverage.A variety of parameters limit the spectrum of use of satellite detection systems, reducing their efficiency in forest fire detection.A satellite monitoring system, for example, has a long scanning period and a low resolution of saturated pixel dots of photographs.Another issue is that cloud layers might obscure photos during the scanning process, and real-time quantitative quantification of fire parameters is extremely difficult to perform.Given the limitations of traditional monitoring, we propose a cloud-based wireless sensor network technology and Explain how it can be used as a monitoring system.This system can monitor real-time related parameters such as temperature and relative humidity and promptly transfer the data to the monitoring center's computer.The computer will assess and manage the collected data.In comparison to standard baroscopic data and fundamental forest resource data, the system can conduct an immediate assessment of a potential fire threat.The analytical results will then be provided to the relevant department as the policy-making foundation on which the department will decide whether to battle fires or prevent fires.
Cite
CITATION STYLE
Kandhari, A., Ginkal, P. M., & Kalaiselvi, K. (2024). Forest Fire Detection using AI. In 15th International Conference on Advances in Computing, Control, and Telecommunication Technologies, ACT 2024 (Vol. 1, pp. 2857–2866). Grenze Scientific Society. https://doi.org/10.55041/isjem04668
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