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先进的无人机-无线传感器网络系统,用于精准农业中的智能监测。

Advanced UAV-WSN System for Intelligent Monitoring in Precision Agriculture.

机构信息

Faculty of Automatic Control and Computers, University Politehnica of Bucharest, 060042 Bucharest, Romania.

出版信息

Sensors (Basel). 2020 Feb 3;20(3):817. doi: 10.3390/s20030817.

Abstract

The growing need for food worldwide requires the development of a high-performance, high-productivity, and sustainable agriculture, which implies the introduction of new technologies into monitoring activities related to control and decision-making. In this regard, this paper presents a hierarchical structure based on the collaboration between unmanned aerial vehicles (UAVs) and federated wireless sensor networks (WSNs) for crop monitoring in precision agriculture. The integration of UAVs with intelligent, ground WSNs, and IoT proved to be a robust and efficient solution for data collection, control, analysis, and decisions in such specialized applications. Key advantages lay in online data collection and relaying to a central monitoring point, while effectively managing network load and latency through optimized UAV trajectories and in situ data processing. Two important aspects of the collaboration were considered: designing the UAV trajectories for efficient data collection and implementing effective data processing algorithms (consensus and symbolic aggregate approximation) at the network level for the transmission of the relevant data. The experiments were carried out at a Romanian research institute where different crops and methods are developed. The results demonstrate that the collaborative UAV-WSN-IoT approach increases the performances in both precision agriculture and ecological agriculture.

摘要

全球对粮食日益增长的需求要求发展高性能、高生产力和可持续的农业,这意味着需要将新技术引入与控制和决策相关的监测活动中。在这方面,本文提出了一种基于无人机 (UAV) 和联合无线传感器网络 (WSN) 协作的分层结构,用于精准农业中的作物监测。UAV 与智能地面 WSN 和物联网的集成被证明是一种强大且高效的解决方案,可用于此类专业应用中的数据收集、控制、分析和决策。其主要优势在于在线数据收集和中继到中央监控点,同时通过优化的 UAV 轨迹和现场数据处理来有效管理网络负载和延迟。协作考虑了两个重要方面:设计用于高效数据收集的 UAV 轨迹,以及在网络级别实施有效的数据处理算法(共识和符号聚合近似),以传输相关数据。实验是在罗马尼亚的一个研究所进行的,该研究所开发了不同的作物和方法。结果表明,协同 UAV-WSN-IoT 方法可提高精准农业和生态农业的性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2998/7038696/5a3bdfd19b31/sensors-20-00817-g001.jpg

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