It is known that smart sensor units are one of the main components of the cyber-physical system. One of the tasks, which have been entrusted to such units, are targeting and tracking of movable objects. The algorithm of targeting on such objects using observation equipment has been considered. This algorithm is able to continuously monitor observation results, predict the direction with the highest probability of movement and form a set of commands to maximize the approximation of a moving object to the center of an information frame. The algorithm has been verified on an experimental physical model using a drone. The object recognition module has been developed using YOLOv3 architecture. iOS application has been developed in order to communicate with the drone through WIFI hotspot using UDP commands. Advanced filters have been added to increase the quality of recognition results. The results of experimental research on the mobile platform confirmed the functioning of the targeting algorithm in real-time.
- A. Melnyk, (2016, November). Cyber-physical systems multilayer platform and research framework. Advances in Cyber-Physical Systems [Online]. Available: http://science.lpnu.ua/acps/all-volumes-and-issues/volume-1-number-1-201... platform-and
- O. Botchkaryov, V. Golembo, Y. Paramud, V. Yazuk, Cyber-physical systems: technologies of data collection [Text]: monography — O. Botchkaryov, V. Golembo, Y. Paramud, V. Yazuk. Editorial chiev: prof. A. Melnyk, Lviv: “Magnolia 2006”, 2019. — pp.10—12 (in Ukrainian)
- A. Koubaa, B. Qureshi, (2018, March). DroneTrack: Cloud- Based Real-Time Object Tracking using Unmanned Aerial Vehicles, IEEE Access [Online]. Available: https://ieeexplore.ieee.org/abstract/document/8306379
- A. Koubaa, B. Qureshi, (2018, March). DroneTrack: Cloud- Based Real-Time Object Tracking using Unmanned Aerial Vehicles, IEEE Access [Online]. Available: https://ieeexplore.ieee.org/abstract/document/8306379
- G. Ding, L. Zhang, Y. Lin, T. Tsiftsis, Y. Yao (2018, January). An Amateur Drone Surveillance System Based on the Cognitive Internet of Things, IEEE Communications Magazine [Online].Available: https://ieeexplore.ieee.org/document/8255734
- P. Pons, J. Jaen, A. Catala (2015, November). Developing a depth-based tracking system for interactive playful environments with animals, ACE ’15: Proceedings of the 12th International Conference on Advances in Computer Entertainment Technology [Online].Available: https://dl.acm.org/doi/10.1145/2832932.2837007
- R. Canals, A. Roussel, J. Famechon (2002, August). A biprocessor-oriented vision-based target tracking system, IEEE Transactions on Industrial Electronics [Online]. Available: https://ieeexplore.ieee.org/abstract/document/993283
- Apple (2019, October), “CoreMl documentation” [Online]. Available: https://developer.apple.com/documentation/coreml
- J. Redmon, A. Farhadi (2018, April) “YOLOv3: An Incremental Improvement” arXiv 2018 [Online]. Available: https://pjreddie.com/media/files/papers/YOLOv3.pdf, Apr.
- D. Kushnir, Y. Paramud, (2019, November). Methods for real-time object searching and recognizing in video images on ios mobile platform. Computer Systems and Networks Volume 1, Number 1. [Online]. 1(1), pp. 24–34 Available: https://doi.org/10.23939/csn2019.01.024 (in Ukrainian).