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.