Forest fires are among the recurring natural disasters that have a significant negative impact on life on earth, as they put plant and animal life at risk of extinction. In addition to their direct impact on air pollution and global warming, Wireless sensor networks (WSNs) have aroused the interest of academics and developers for a variety of modern life applications, such as environmental monitoring and forest fires. This paper proposes a framework for a WSN simulation of forest fires' real-time detection and monitoring using flame sensors. The proposed architecture aims to achieve two main goals: to deal with forest fires faster than traditional methods by predicting the mechanism of fire spread with high accuracy using mathematical analysis like extrapolation and curve fitting processes while taking into account the five factors affecting the spread of fire. These factors are the type of environment (fuel), temperature, humidity, and finally wind speed and direction. The second goal is to find a relationship between the density of sensor nodes that are randomly distributed in the region and the accuracy of calculations of fire spread. A simulation of the spread of fire was conducted, and a relationship was found between sensor density and prediction accuracy. It was found that the proposed optimized WSN system can increase the accuracy by 12% compared to its percentage in the case of using the traditional wireless sensor network.

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