Weizhao Chen ¹ and Cesar Magana ² , ¹ USA, ² California State University Long Beach, USA

General aviation pilots frequently face fatal accidents due to cognitive overload when manually interpreting complex weather and terrain data mid-flight. To solve this, we developed SkyAware, an active, intelligent flight companion. Built with Flutter, the application integrates the Gemini API, Open Maps Terrain, and AviationWeather data to provide real-time 3D hazard monitoring and conversational safety briefings [1]. Core challenges included accurately synchronizing asynchronous APIs, ensuring AI hazard analysis reliability, and visualizing dense spatial data. We mitigated synchronization latency by implementing predictive forward vectoring. Experimentation using historical NTSB events and live MSFS 2024 telemetry yielded our most important results: an 86% mean AI hazard detection accuracy and a highly responsive 1,340ms average warning latency [2]. The results indicate that SkyAware effectively translates raw metrics into actionable insights, improving pilot decision-making. By proactively preventing alert fatigue, SkyAware empowers safer mid-flight decision-making and save lives in the cockpit.

Real-time data analysis, Aviation assistance, Electronic Flight Bag (EFB) companion, Profound Private pilot tools