Energy Optimization in Wireless Sensor Networks for Forest Fire Detection: A Study of Sleep Scheduling Techniques

Abstract

Wireless Sensor Networks (WSNs) have gained significant interest in forest fire applications due to their potential for real-time monitoring, early detection, and quick reaction. However, energy consumption poses a challenge as sensor nodes primarily rely on batteries. Efficient energy management is crucial to extend network lifespan, reduce maintenance frequency, and ensure continuous monitoring. This paper proposes the use of sleep-based concepts in WSNs for forest fire detection to optimize energy consumption. The study utilizes the Omnet++ simulation platform to model and simulate a realistic WSN deployed in a forest fire detection scenario. It analyses power consumption patterns, evaluates different MAC protocols, and explores sleep scheduling optimization.