CollabDrone: A Collaborative Spatiotemporal-Aware Drone Sensing System Driven by Social Sensing Signals

摘要

While autonomous unmanned aerial vehicles (UAVs) have attained a reputable stance in modern disaster response applications, their practical adoptions are impeded due to various constraints (e.g., requiring manual input, battery life). In this paper, we develop a novel spatiotemporal aware drone sensing system that is driven by harnessing social media signals, a process known as social sensing. Social sensing has emerged as a new sensing paradigm where humans act as "sensors" to report their observations about the physical world. However, maneuvering drones with "social signals" introduces a new realm of challenges. The first challenge is to drive the drones by leveraging noisy and unreliable social media signals. The second challenge is to optimize the drone deployment by exploring the highly dynamic and latent correlations among event locations. In this paper, we present CollabDrone that devises a new spatiotemporal correlation inference model and game-theoretic drone dispatching mechanism to address the above challenges. The evaluation results on a real-world case study show that CollabDrone significantly outperforms current drone and social sensing baselines in terms of accuracy and deadline hit rate.