Automatic Forest Surveillance Based on Infrared Sensors

Abstract

Sensor networks are of great interest to complement human capabilities when monitoring wide-forest areas. This paper describes a remote system scheme for automatic forest surveillance based on infrared sensors. A complete system for forest fire detection is firstly presented although we focus on processing the images from infrared sensors. The proposed scheme based on infrared image processing performs early detection of any fire threat. With the aim of determining the presence or absence of fire, the proposed algorithms performs the fusion of different detectors which exploit different expected characteristics of a real fire, like persistence and increase. Theoretical results and practical simulations are presented to corroborate the control of the probability of false alarm (PFA). Probability of detection (PD) dependence on signal to noise ratio (SNR) is also evaluated.