Unmanned aerial vehicles (or drones) are increasingly creating challenges for managing the safety of aircraft that share the airspace with them. The collection and use of forensic data associated with drones and surrounding physical contexts is key to effective incident investigations. The research is focusing on the architecture and concept of operations for European unmanned traffic management, and the ability to preserve such vital information as evidence for forensic investigations.

DroneBox: Automated Adaptive Collection of UAV Flight Data

Exciting News!

EngageKTN Round 2.

In recognition of the successful collaboration and engagement with NATS (between 1 July 2019 - 30 June 2020), we have been awarded another project titled "Safe drone flight - assuring telemetry data integrity in U-Space scenarios", which was kickstarted on 1 July 2020. In this round, NATS will be leading on the exploration and exploitation of the technical feasibility of various research ideas and research concepts from the papers listed below, and beyond.

Article of the Week.

This week also saw the LiveBox architecture we proposed in the project recognised as "article of the week", according to the IEEE Access journal. In the article, we articulated a conceptual architecture to implement forensic-ready drone data. The architecture has been evaluated technically during the project by Danny Barthaud and will form a basis for the next phase of safety in drone flights research!

The Open University Dr. Yijun Yu [contact] Mr. Danny Barthaud [contact] Prof. Bashar Nuseibeh Prof. Blaine Price Prof. Andrea Zisman Prof. Arosha Bandara NATS Dr. Anthony P. Rushton Dr. David L. Bush Dr. Jacob Blamey Dr. Gavin Moir Dr. George S. Koudis

Publications Yu, Yijun; Barthaud, Danny; Price, Blaine; Bandara, Arosha; Zisman, Andrea and Nuseibeh, Bashar (2019). LiveBox: A Self-Adaptive Forensic-Ready Service for Drones. IEEE Access, Volume 7, pp. 148401 - 148412. Maia, Paulo; Vieira, Lucas; Chagas, Matheus; Yu, Yijun; Zisman, Andrea and Nuseibeh, Bashar. Cautious Adaptation of Defiant Components. In: The 34th IEEE/ACM International Conference on Automated Software Engineering (ASE 2019) (Lawall, Julia and Marinov, Darko eds.), 11-15 Nov 2019, San Diego, California, USA. Maia, Paulo; Vieira, Lucas; Chagas, Matheus; Yu, Yijun; Zisman, Andrea and Nuseibeh, Bashar (2019). Dragonfly: a Tool for Simulating Self-Adaptive Drone Behaviours. In: SEAMS '19 Proceedings of the 14th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, IEEE pp. 107--113. Luo, Yixing; Yu, Yijun; Jin, Zhi and Zhao, Haiyan (2019). Environment-Centric Safety Requirements forAutonomous Unmanned Systems. In: 27th IEEE International Requirements Engineering Conference (RE'19), 23-27 Sep 2019, Jeju, Korea, IEEE. Luo, Yixing; Yu, Yijun; Jin, Zhi; Li, Yao; Ding, Zuohua; Zhou, Yuan and Liu, Yang (2020). Privacy-Aware UAV Flights through Self-Configuring Motion Planning. In: International Conference on Robotics and Automation, 31 May - 4 Jun 2020, Paris, France.