Abstract
Every year forest fires destroy millions of hectares of land worldwide. Detecting forest fire ignition in the early stages is fundamental to avoid forest fires catastrophes. In this approach, Wireless Sensor Network is explored to develop a monitoring system to send alert to authorities when a fire ignition is detected. The study of sensors allocation is essential in this type of monitoring system since its performance is directly related to the position of the sensors, which also defines the coverage region. In this paper, a mathematical model is proposed to solve the sensor allocation problem. This model considers the sensor coverage limitation, the distance, and the forest density interference in the sensor reach. A Genetic Algorithm is implemented to solve the optimisation model and minimise the forest fire hazard. The results obtained are promising since the algorithm could allocate the sensor avoiding overlaps and minimising the total fire hazard value for both regions considered.
Highlights
Forest fires are a global problem, especially in the Mediterranean region
Portugal is by far the Mediterranean country that has suffered the most due to forest fires, registering on average of 141,007 ha burned per year between 2009 and 2018 [1,2]
Wireless sensor network (WSN) is a current technology used in several fields [9]
Summary
Forest fires are a global problem, especially in the Mediterranean region. Portugal is by far the Mediterranean country that has suffered the most due to forest fires, registering on average of 141,007 ha burned per year between 2009 and 2018 [1,2]. The Mediterranean region was considered highly fire-adapted due to historical occupation context, the contemporary societies have not fully adapted to balancing fire hazard risk and resource needs on the region [3,4] Today, this type of environmental catastrophe has severe damage for flora and fauna and for economics and loss of human lives. Modules of wireless sensors will be spread in the forest to collect data about humidity, temperature, UV index, and flame presence. These data are evaluated by an intelligent and autonomous system and alerts messages are sent when a fire ignition is identified. This paper concentrates efforts to determine the optimal position for sensor allocation considering the sensor coverage limitation, the distance and the forest density interference in the sensor reach
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