The Use of Artificial Intelligence Techniques for Signal Discrimination in Fire Detection Systems

Abstract

One of the biggest challenges in the design of fire detection systems is the discrimination between actual fire signatures and noise. This is especially true as the fire size at the time of detection decreases, as the signal to noise ratio decreases accordingly. Smoke detectors, for example, are simply particle detectors calibrated for specific particle size distributions, number densities and refractive indices. Smoke particles are electronically or optically sensed, and when a predetermined signal level is reached, an alarm condition is signalled.