Skip to content. | Skip to navigation

Personal tools

Navigation

Intelligent Mobile Surveillance through Swarming Drones

Description of Intelligent Mobile Surveillance through Swarming Drones research project

Intelligent Mobile Surveillance through Swarming Drones

Intelligent Mobile Surveillance through Swarming Drones

The advent of small drones/Unmanned Aerial Vehicles (UAVs) equipped with remote visual sensing capabilities have played crucial roles in many surveillance applications such as border patrol, disaster response and rescuing, crowd control, traffic monitoring, and wildfire surveillance. Deploying a swarm of small UAVs for a surveillance application can not only reduce the cost but also provide scalable and flexible visual sensing capability than single UAV systems. Different from traditional surveillance systems with fixed-location cameras, the sensing, control, and communication components for swarming UAVs are tightly coupled, which calls for novel design to seamlessly integrate these components. A UAV-based mobile surveillance system captures visual observations from the environment and performs analysis on the observations to understand the behaviors of the captured objects.

The overall objective of this research is to establish and demonstrate intelligent mobile surveillance systems through swarming UAVs that significantly augment existing ground surveillance systems by providing enhanced sensing quality, short response time, and intelligent decisions to users. This objective will be achieved through synergistic integration of research components in video processing and analysis, intelligent systems and control, and wireless communications and networking.

Related Publications


  1. J. Joseph, M. Radmanesh, M. N. Sadat, R. Dai, M. Kumar, “UAV Path Planning for Data Ferrying with Communication Constraints”, IEEE Consumer Communications Networking Conference (CCNC), Las Vegas, NV, USA, 2020.
  2. R. Dai, S. Fotedar, M. Radmanesh, M. Kumar, "Quality-Aware UAV Coverage and Path Planning in Geometrically Complex Environments"Ad Hoc Networks (Elsevier), vol. 73, pp. 95-105, May 2018.
  3. K. Scott, R. Dai, and J. Zhang, "Online-Relaying-Based Image Communication in Unmanned Aerial Vehicle Networks"IEEE International Conference on Communications (ICC), May 2017.
  4. K. Scott, R. Dai, M. Kumar, "Occlusion-aware Coverage for Efficient Visual Sensing in Unmanned Aerial Vehicle Networks", IEEE Global Communications Conference (GLOBECOM), Dec. 2016.