Real-time processing of high-resolution video and 3D model-based tracking for remote towers
This work addresses the problem of real-time video processing for air traffic controllers in remote towers, offering incremental improvements in efficiency and resilience.
The paper tackles the challenge of real-time processing of high-resolution video (over 25 million pixels at 30 fps) for remote tower operations by implementing decoupled processes and parallel computing on a single workstation, resulting in efficient and resilient software that provides relevant enhancements to air traffic controllers.
High quality video data is a core component in emerging remote tower operations as it inherently contains a huge amount of information on which an air traffic controller can base decisions. Various digital technologies also have the potential to exploit this data to bring enhancements, including tracking ground movements by relating events in the video view to their positions in 3D space. The total resolution of remote tower setups with multiple cameras often exceeds 25 million RGB pixels and is captured at 30 frames per second or more. It is thus a challenge to efficiently process all the data in such a way as to provide relevant real-time enhancements to the controller. In this paper we discuss how a number of improvements can be implemented efficiently on a single workstation by decoupling processes and utilizing hardware for parallel computing. We also highlight how decoupling the processes in this way increases resilience of the software solution in the sense that failure of a single component does not impair the function of the other components.