Forest fire detection system using wireless sensor networks and machine learning

Abstract

Forest fires have become a major threat around the world, causing many negative impacts on human habitats and forest ecosystems. Climatic changes and the greenhouse effect are some of the consequences of such destruction. Interestingly, a higher percentage of forest fires occur due to human activities. Therefore, to minimize the destruction caused by forest fires, there is a need to detect forest fires at their initial stage. This paper proposes a system and methodology that can be used to detect forest fires at the initial stage using a wireless sensor network. Furthermore, to acquire more accurate fire detection, a machine learning regression model is proposed. Because of the primary power supply provided by rechargeable batteries with a secondary solar power supply, a solution is readily implementable as a standalone system for prolonged periods. Moreover, in-depth attention is given to sensor node design and node placement requirements in harsh forest environments and to minimize the damage and harmful effects caused by wild animals, weather conditions, etc. to the system. Numerous trials conducted in real tropical forest sites found that the proposed system is effective in alerting forest fires with lower latency than the existing systems.

GIS application in analysis of threat of forest fires and landslides in the Svrljiski Timok basin (Serbia)

“…In this way, the highest degree risk zones have been determined, which should first be taken into consideration when establishing monitoring systems, fire barriers, etc. Sensors can be installed in the endangered areas to monitor the area and at the same time to be alarms that would give a signal to the fire and local services to suppress and prevent such situations (Barmpoutis et al, 2020;Dampage et al, 2022). Similar sensors provided positive results in the natural park of Sierra Mariola in Spain (Molina-Pico et al, 2016).…”

“…На овај начин су одређене ризичне зоне највишег степена, на које би требало прво обратити пажњу приликом установљавања система мониторинга, противпожарних препрека и слично. На угроженим просторима могу се поставити сензори који би вршили мониторинг простора и уједно били и узбуњивачи који би дали сигнал ватрогасним и локалним службама за сузбијање и спречавање оваквих ситуација (Barmpoutis et al, 2020;Dampage et al, 2022). Овакви сезнори дали су позитивне резултате у природном парку Мариола у Шпанији (Molina-Pico et al, 2016).…”

An energy-aware and Q-learning-based area coverage for oil pipeline monitoring systems using sensors and Internet of Things

“…However, the growing advances in these networks have led to new technologies such as the Internet of Things (IoT) 7 , 8 . The IoT has created new opportunities to communicate things around us, such as lamp switches 9 , oil and gas transmission pipelines, industrial machines 10 , home equipment 11 , cars, and the human body using the Internet platform 12 , 13 . Today, this new technology is applied in various industrial and engineering fields such as pipeline monitoring systems.…”

Wireless sensor networks for forest fire monitoring: Issues and Challenges

“…Ash from such fires depletes much of the nutrients from the soil, which results in less growth of flora and leads to soil erosion. Hence, it leads to disasters like landslides and floods [2]. The loss of timber and medicinal herbs due to fires results in economic losses, affecting the health and livelihood of people who depend on forests and live in the vicinity.…”

“…Though there were many such procedures adopted traditionally but somehow, they are not competent enough. Such traditional approaches for detecting forest fires included human monitoring by watchtowers, image acquisition[3]-[5] or even satellite imaging and which is even followed today, but each method had severe drawbacks like latency, inefficiency, cost, and greater power consumption, etc [2]. Therefore, this problem should be addressed with some recent efficient technologies.…”