mlsanityData to 7 Oct 2026

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

arXiv 2203.02892 ↗First posted 6 Mar 2022cs.LG cs.AI cs.MAcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 25 references that are in the map. First posted on arXiv 6 Mar 2022.

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References · 7

  1. 2017Proximal Policy Optimization Algorithmscited by 14,441
  2. 2018Real-world Anomaly Detection in Surveillance Videoscited by 570
  3. 2020Communication-Computation Trade-Off in Resource-Constrained Edge Inferencecited by 60
  4. 2019Mobile Edge Intelligence and Computing for the Internet of Vehiclescited by 22
  5. 2021Packet-Loss-Tolerant Split Inference for Delay-Sensitive Deep Learning in Lossy Wireless Networkscited by 7
  6. 2017Deep Learning for Real Time Crime Forecastingcited by 5
  7. 2018Design of Ad Hoc Wireless Mesh Networks Formed by Unmanned Aerial Vehicles with Advanced Mechanical Automationcited by 1

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