Ingham, Christopher and Reid, David and Secco, Emanuele Lindo (2025) An Integrated Wireless Video Robotic Aerial System for Emergency Real-Time Monitoring. Journal of Sensors, IoT & Health Sciences, 3 (2). pp. 1-19. ISSN 2584-2560 (Accepted for Publication)
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Abstract
Emergency scenarios are becoming more and more demanding for the National Health Services and for emergency operators such as Police and Fire-Fighters. In this context the rapidity and efficiency of the interventions are mandatory skills. We leverage on current technologies to propose an integrated system where conversational interaction with a Machine Vision System can provide a specific behavior to a mobile vehicle combined with a flying drone in order to execute a specific task such as, for example, having the drone following an operator while intervening in the emergency (i.e. earthquake, fire, flooding, etc.). The paper investigates the use of video object detection using a DJI Mavic Air Drone for real-time applications. The object detection system is provided by CGI Machine Vision, detecting objects and people from live footage. The aim of the proposed architecture is to provide an integrated solution for streaming a live video feed from a camera drone to an edge device running CGI Machine Vision to prove the concept of vehicle-based drones to provide aerial situational awareness to emergency operators and law enforcement officers. The paper presents the design, implementation and testing of the system, as well as the successful proof of concept and real-world demonstration. The research gave positive results and demonstrated the capability, along with recommendations for further refinement and next steps.
| Item Type: | Article |
|---|---|
| Additional Information and Comments: | This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
| Faculty / Department: | Faculty of Human and Digital Sciences > School of Computer Science and the Environment |
| Depositing User: | Emanuele Secco |
| Date Deposited: | 07 Jul 2025 11:02 |
| Last Modified: | 07 Jul 2025 11:02 |
| URI: | https://hira.hope.ac.uk/id/eprint/4678 |
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