AI meets UAVs: A survey on AI empowered UAV perception systems for precision agriculture

Precision Agriculture (PA) promises to boost crop productivity while reducing agricultural costs and environmental footprints, and therefore is attracting ever-increasing interests in both academia and industry. This management strategy is underpinned by various advanced technologies including Unman...

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Published inNeurocomputing (Amsterdam) Vol. 518; pp. 242 - 270
Main Authors Su, Jinya, Zhu, Xiaoyong, Li, Shihua, Chen, Wen-Hua
Format Journal Article
LanguageEnglish
Published Elsevier B.V 21.01.2023
Subjects
Deep learning
Machine learning
Precision agriculture
Remote sensing
Smart agriculture
Unmanned Aerial Vehicle (UAV)
Deep learning
Precision agriculture
Smart agriculture
Unmanned Aerial Vehicle (UAV)
Remote sensing
Machine learning
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Abstract Precision Agriculture (PA) promises to boost crop productivity while reducing agricultural costs and environmental 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 particular) 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 computationally 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 algorithms) 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 provide 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.
AbstractList Precision Agriculture (PA) promises to boost crop productivity while reducing agricultural costs and environmental 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 particular) 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 computationally 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 algorithms) 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 provide 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.
Author Su, Jinya
Zhu, Xiaoyong
Li, Shihua
Chen, Wen-Hua
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  email: W.Chen@lboro.ac.uk
  organization: Department of Aeronautical and Automotive Engineering, Loughborough University, Loughborough LE11 3TU, UK
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Keywords Deep learning
Precision agriculture
Smart agriculture
Unmanned Aerial Vehicle (UAV)
Remote sensing
Machine learning
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Snippet Precision Agriculture (PA) promises to boost crop productivity while reducing agricultural costs and environmental footprints, and therefore is attracting...
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StartPage 242
SubjectTerms Deep learning
Machine learning
Precision agriculture
Remote sensing
Smart agriculture
Unmanned Aerial Vehicle (UAV)
Title AI meets UAVs: A survey on AI empowered UAV perception systems for precision agriculture
URI https://dx.doi.org/10.1016/j.neucom.2022.11.020
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