Low-Cost METAR for Aeronautics: AI & Computer Vision

We propose to co-develop a low-cost Meteorological Aerodrome Report (METAR) system that uses artificial intelligence (AI) and computer vision to fuse camera feeds with local weather-station data, generating real-time observations and nowcasting for regional aerodromes and airports. The project is at Technology Readiness Level (TRL) 2–3 and builds on robust prior work in ground-based cloud-type classification and segmentation from my background in physics and meteorology and my ongoing Doctor of Philosophy (PhD) research in computer science. Beyond aeronautics and aviation safety, the same methods extend to solar photovoltaic (PV) forecasting and to resilient, sustainable, and smart cities. We are seeking research collaborators and co-funding to commercialise this work through pilots, testbeds, and validation.