Abstract: Described herein is a mobile device with an optical detector including: at least one illumination source adapted to generate at least one illumination pattern for illuminating an object, where the illumination pattern includes a regular and/or constant and/or periodic pattern; at least one sensor element having a matrix of optical sensors, the optical sensors each having a light-sensitive area, where each optical sensor is configured to generate at least one sensor signal in response to an illumination of the light-sensitive area by at least one light beam propagating from the object to the detector; and at least one evaluation device adapted to determine at least one region of interest.

Abstract: A Wildfire Early Detection System uses Aerial Video Clips of surveilled areas—obtained through a Network of Hardware components including UAVs and Tethered Aerostats equipped with a Camera and an AI-enabled Embedded Computer—and an Aerial Training Dataset, digitally combining variations of Smoke-Plume-Clips with variations of Background-Clips in nine different positions in the first frame of said Background-Clips with a relative size to the background calculated by perspective and programmed to follow the background to stay apparently “static” in the same place relative to the background for all the remaining frames of the Clip. A Computer-Vision Algorithm trained with that Aerial Training Dataset is used to recognize early fire Plumes of Smoke in those Aerial Video Clips with use of a Multiplication-free Neural Network for Wildfire detection, an AddNet based Discriminator CNN, a GANs used as both event detectors and smoke-plume scene synthesis and Block-based detection.