Watch from sky: machine-learning-based multi-UAV network for predictive police surveillance

Abstract

This paper presents the watch-from-sky framework, where multiple unmanned aerial vehicles (UAVs) play four roles, i.e., sensing, data forwarding, computing, and patrolling, for predictive police surveillance. Our framework is promising for crime deterrence because UAVs are useful for collecting and distributing data and have high mobility. Our framework relies on machine learning (ML) technology for controlling and dispatching UAVs and predicting crimes. This paper compares the conceptual model of our framework against the literature. It also reports a simulation of UAV dispatching using reinforcement learning and distributed ML inference over a lossy UAV network.

AI for UAV-Assisted IoT Applications : A Comprehensive Review

“…The system is empirically validated to have high localization and tracking accuracy. UAVs are utilized for crime prediction in [81]. These UAVs are classified into three classes, which are utilized for sensing information, computational analysis, and deterrence.…”