Abstract. Fires are an important factor in shaping Earth's ecosystems. Plant and animal life, in almost every land habitat, are at least partially dependant on the effects of fire. However, their destructive force, which many times has proven itself uncontrollable, is one of our greatest concerns, effectively originating several policies in the most important industrialised regions of the globe. This paper aims to comprehensively characterise the Forest Fire Finder (FFF), a forest fire detection system based mainly upon a spectroscopic technique called Differential Optical Absorption Spectroscopy (DOAS). The system is designed and configured with the goal of detecting higher-than-the-horizon smoke columns by measuring and comparing scattered sunlight spectra. The article covers hardware and software, as well as their interactions and specific algorithms for day mode operation. An analysis of data retrieved from several installations deployed in the course of the last five years, is also presented. Finally, this document features a discussion on the most prominent future improvements planned for the system, as well as its ramifications and adaptations, such as a thermal imaging system for short range fire seeking or environmental quality control.
Early Forest Fire Detection System using Wireless Sensor Network and Deep Learning
