An Effective Forest Fire Detection Framework Using Heterogeneous Wireless Multimedia Sensor Networks

With improvements in the area of Internet Things (IoT), surveillance systems have recently become more accessible. At same time, optimizing energy requirements smart sensors, especially for data transmission, has always been very important and efficiency IoT subject numerous studies. For environmental monitoring scenarios, it is possible to extract accurate information using multimedia sensors. However, transmission an expensive operation. In this study, a novel hierarchical approach presented detection forest fires. The proposed framework introduces new which scalar sensors are used hierarchically minimize visual data. A lightweight deep learning model also developed devices at edge network improve accuracy reduce traffic between sink. evaluated real testbed, simulations, 10-fold cross-validation terms accuracy. Based on results our experiments, validation system 98.28%, saving 29.94%. model’s close best performing architectures when existing studies considered. suitability computing, superior ones with reduced computational size.