AI meets UAVs: A survey on AI empowered UAV perception systems for precision agriculture
AI meets UAVs: A survey on AI empowered UAV perception systems for precision agriculture
复制标题
人工智能邂逅无人机：面向精准农业的人工智能赋能无人机感知系统综述
DOI：
10.1016/j.neucom.2022.11.020
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发表时间：
2022-11-12
期刊：
影响因子：
6
通讯作者：
Chen, Wen-Hua
中科院分区：
文献类型：
--
作者：
Su, Jinya;Zhu, Xiaoyong;Chen, Wen-Hua
精准农业(PA)承诺在降低农业成本和环境足迹的同时提高作物生产率，因此吸引了学术界和工业界越来越多的兴趣。这一管理战略得到了各种先进技术的支持，包括无人机(UAV)传感系统和人工智能(AI)感知算法。特别是，由于无人机传感系统具有低成本、高时空分辨率、灵活性、自动化功能和操作风险最小化等独特优势，自2010年以来已广泛应用于包括功放在内的许多民用应用中。与此同时，人工智能算法(自2012年以来一直在深入学习)也在不同领域引起了越来越多的关注，因为它们能够(半自动)分析前所未有的数据量/速度/种类，随着云计算、图形处理单元和并行计算的进步，这些数据也变得越来越实用。因此，本文对无人机传感系统(如无人机平台、外部传感单元)和人工智能算法(主要是有监督学习算法)在作物整个生命周期中的应用进行了深入的综述，并对无人机和人工智能在农业领域未来发展的挑战和前景进行了全面的综述。据设想，这项审查能够提供及时的技术参考，揭开并促进人工智能支持的无人机感知系统的研究、部署和成功开发，从而有助于应对未来的农业和人类营养挑战。(C)2022爱思唯尔公司保留所有权利。
Precision Agriculture (PA) promises to boost crop productivity while reducing agricultural costs and envi-ronmental footprints, and therefore is attracting ever-increasing interests in both academia and industry. This management strategy is underpinned by various advanced technologies including Unmanned Aerial Vehicle (UAV) sensing systems and Artificial Intelligence (AI) perception algorithms. In particular, due to their unique advantages such as a low cost, high spatio-temporal resolutions, flexibility, automation functions and minimized risk of operation, UAV sensing systems have been extensively applied in many civilian applications including PA since 2010. In parallel, AI algorithms (deep learning since 2012 in par-ticular) are also drawing ever-increasing attention in different fields, since they are able to analyse an unprecedented volume/velocity/variety of data (semi-) automatically, which are also becoming compu-tationally practical with the advancements of cloud computing, Graphics Processing Units and parallel computing. In this survey paper, therefore, a thorough review is performed on recent use of UAV sensing systems (e.g., UAV platforms, external sensing units) and AI algorithms (mainly supervised learning algo-rithms) in PA applications throughout the crop life-cycle, as well as the challenges and prospects for future development of UAVs and AI in agriculture sector. It is envisioned that this review is able to pro-vide a timely technical reference, demystifying and promoting research, deployment and successful exploitation of AI empowered UAV perception systems for PA, and therefore contributing to addressing future agricultural and human nutrition challenges.(c) 2022 Elsevier B.V. All rights reserved.