论文标题
从天空观看：基于机器学习的多UAV网络，用于预测警察监视
Watch from sky: machine-learning-based multi-UAV network for predictive police surveillance
论文作者
论文摘要
本文介绍了from-kky的手表，其中多个无人驾驶飞机（UAV）扮演四个角色，即感应，数据转发，计算和巡逻，以进行预测性警察的监视。我们的框架对犯罪威慑很有希望，因为无人机可用于收集和分发数据并具有很高的流动性。我们的框架依靠机器学习（ML）技术来控制和派遣无人机和预测犯罪。本文将我们框架的概念模型与文献进行了比较。它还报告了使用强化学习和分布式ML推断在有损失的无人机网络上进行分配的无人机调度的模拟。
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.
