A Conceptual Design for Threat Detection System in UAM Vertiport Using Video Recognition and Flight Data

In this research, our research team propose an AI & Flight data-based threat detection system that can identify potential threats that may occur during the takeoff and landing stages at Urban Air Mobility (UAM) Vertiports. This system has been developed to detect threats that are currently difficult to detect based on current radar system by image object recognition and its own flight data, and we present a specific methodology that the proposed system can be used for Vertiport. The resulting methodology will provide a threat detection framework for UAM Vertiports, which will improve the overall safety and efficiency of takeoff and landing phase operations in Vertiport if more diverse threats are used to deep learning in the future.