Multi-drone Surveillance

Surveillance and remote sensing are amongst the top industries for monitoring human behavior and changes in the environment with the objectives of public safety and security as well as infrastructure protection. Video-based surveillance market is expected to reach over 68 billion dollars by 2023. Technologies like satellite remote sensing (SRS) and distributed camera sensor networks (CSNs) are used in many applications to provide large scale and localized monitoring, respectively. However, as shown in Fig. 1, both technologies provide two extremes for surveillance with respect to accuracy versus intrusive deployment and maintenance. SRS provides slow large-scale monitoring, while CSNs require widespread deployment and constant human intervention for setup and maintenance, which may not be feasible particularly in harsh environments. On the one hand, SRS cannot be used for fine-grain monitoring, such as monitoring of structural objects, with high accuracy, which limits its usage in many applications that require close monitoring and context detection. On the other hand, traditional sensor networks (SNs) are spreading in countless number of Internet of Things (IoT) applications to provide automatic monitoring of objects, humans, and/or infrastructure. SNs, however, require permanent deployment of large magnitude of localized sensors, intrusively to the environment in many cases, and also require constant human intervention to manage and maintain. The proliferation of low-cost UAVs is emerging to provide innovative ways of low altitude sensing with zero-deployment (i.e., no fixed deployment requirements) that can fundamentally change the way such applications are designed.

The smart IoT systems research group (SIoTS-RG) have been conducting research in this area since 2012 with diverse focus on multi-drone surveillance techniques and applications, including smart coverage for different types of targets such as point, dimensional and directional targets, energy-efficient trajectory planning and navigation, and distributed machine learning inference over multi-drone systems. The group has been successful in securing several grants in this area as detailed in the projects page.