AI-based technology for automatically diagnosing power facilities in-vehicle

Extreme weather events such as typhoons, heavy snow, and torrential rain frequently cause failures in power distribution facilities, resulting in significant social and economic consequences, including large-scale blackouts, wildfires, and explosions. A notable example is the 2018 Camp Fire in California, USA, which was linked to aging distribution infrastructure and inadequate maintenance, leading to devastating outcomes. This study presents a technology that utilizes optical imaging and AI-based systems installed on vehicles to automatically detect, track, and capture high-resolution images of power distribution facilities while diagnosing equipment defects in real time. The proposed system employs advanced AI algorithms to identify defects such as cracks, corrosion, and erosion, addressing the growing challenges posed by climate-induced damage. By automating the inspection of power distribution facilities, this AI-driven diagnostic system mitigates the risks associated with extreme weather events, helps prevent large-scale disasters such as wildfires, and improves the reliability of power system management. Furthermore, transitioning from traditional manual inspection methods to automated diagnostics reduces safety risks and significantly improves industrial safety, efficiency, and sustainability.