Integration of AIS Data for Efficient Drone Navigation in Maritime Real-Time Ship Inspection Missions

The increasing use of drones for maritime inspections in near-coastal areas has highlighted the need for more sophisticated tools that can assist operators in optimizing mission planning and flight paths. Despite advancements in drone technology, challenges remain in efficiently combining available data to enhance range, increase available inspection time, and overall mission effectiveness. This paper proposes a novel application that integrates Automatic Identification System (AIS) data into the drone navigation and mission planning process. By leveraging real-time AIS data, including ship positions, speeds, and headings, the system provides dynamic waypoint suggestions to operators, facilitating more precise and efficient path planning. Additionally, the integration of wind correction factors into the flight planning algorithm further enhances battery management, allowing for extended mission durations. Through simulations and real-world experiments, the proposed system demonstrates significant improvements in mission planning efficiency, drone range, and inspection time, offering a promising solution for the growing demands of maritime inspections.