Smoke Detection Using Particle Filter in Near-Infrared Range

Abstract

This study aims to explore methods for the active, early detection of smoke from the initial stage of a fire or a smoldering fire. Methods to detect smoke and fires from images have been tested, but in the case of environments where the visible light provides insufficient illumination for surveillance, the necessary light levels and contrast cannot be obtained, giving rise to the possibility that the system will not perform adequately. It is shown that by using a depth camera to project a discrete pattern of near infrared light into an area, paired with a camera with spectral sensitivity tuned to the same band of wavelengths to detect when that pattern is attenuated, it is possible to sense changes in the concentration of particles such as smoke and mist. In the study, fire tests were carried out using three fire sources and, using a NIR projector and NIR camera, clusters of particles that indicates a rising plume of smoke were visualized. Then, smoke candidates using a particle filter were found, and it was shown that it is possible to detect smoke from the candidates tracked.