Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture
The integration of unmanned aerial vehicles (UAVs) with artificial intelligence (AI) and machine learning (ML) has fundamentally transformed precision agriculture by enhancing efficiency, sustainability, and data-driven decision making. In this paper, we present a comprehensive overview of the integ...
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MDPI AG
2024-11-01
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| Series: | Drones |
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| Online Access: | https://www.mdpi.com/2504-446X/8/11/664 |
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| author | Juhi Agrawal Muhammad Yeasir Arafat |
| author_facet | Juhi Agrawal Muhammad Yeasir Arafat |
| author_sort | Juhi Agrawal |
| collection | DOAJ |
| description | The integration of unmanned aerial vehicles (UAVs) with artificial intelligence (AI) and machine learning (ML) has fundamentally transformed precision agriculture by enhancing efficiency, sustainability, and data-driven decision making. In this paper, we present a comprehensive overview of the integration of multispectral, hyperspectral, and thermal sensors mounted on drones with AI-driven algorithms to transform modern farms. Such technologies support crop health monitoring in real time, resource management, and automated decision making, thus improving productivity with considerably reduced resource consumption. However, limitations include high costs of operation, limited UAV battery life, and the need for highly trained operators. The novelty of this study lies in the thorough analysis and comparison of all UAV-AI integration research, along with an overview of existing related works and an analysis of the gaps. Furthermore, practical solutions to technological challenges are summarized to provide insights into precision agriculture. This paper also discusses the barriers to UAV adoption and suggests practical solutions to overcome existing limitations. Finally, this paper outlines future research directions, which will discuss advances in sensor technology, energy-efficient AI models, and how these aspects influence ethical considerations regarding the use of UAVs in agricultural research. |
| format | Article |
| id | doaj-art-d64d36905bcb491cbd0fbab429066b49 |
| institution | OA Journals |
| issn | 2504-446X |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj-art-d64d36905bcb491cbd0fbab429066b492025-08-20T02:28:04ZengMDPI AGDrones2504-446X2024-11-0181166410.3390/drones8110664Transforming Farming: A Review of AI-Powered UAV Technologies in Precision AgricultureJuhi Agrawal0Muhammad Yeasir Arafat1School of Computer Science, University of Petroleum & Energy Studies, Prem Nagar, Dehradun 248007, IndiaIT Research Institute, Chosun University, Gwangju 61452, Republic of KoreaThe integration of unmanned aerial vehicles (UAVs) with artificial intelligence (AI) and machine learning (ML) has fundamentally transformed precision agriculture by enhancing efficiency, sustainability, and data-driven decision making. In this paper, we present a comprehensive overview of the integration of multispectral, hyperspectral, and thermal sensors mounted on drones with AI-driven algorithms to transform modern farms. Such technologies support crop health monitoring in real time, resource management, and automated decision making, thus improving productivity with considerably reduced resource consumption. However, limitations include high costs of operation, limited UAV battery life, and the need for highly trained operators. The novelty of this study lies in the thorough analysis and comparison of all UAV-AI integration research, along with an overview of existing related works and an analysis of the gaps. Furthermore, practical solutions to technological challenges are summarized to provide insights into precision agriculture. This paper also discusses the barriers to UAV adoption and suggests practical solutions to overcome existing limitations. Finally, this paper outlines future research directions, which will discuss advances in sensor technology, energy-efficient AI models, and how these aspects influence ethical considerations regarding the use of UAVs in agricultural research.https://www.mdpi.com/2504-446X/8/11/664artificial intelligencecrops monitoringmachine learningprecision agricultureremote sensingsmart agriculture |
| spellingShingle | Juhi Agrawal Muhammad Yeasir Arafat Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture Drones artificial intelligence crops monitoring machine learning precision agriculture remote sensing smart agriculture |
| title | Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture |
| title_full | Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture |
| title_fullStr | Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture |
| title_full_unstemmed | Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture |
| title_short | Transforming Farming: A Review of AI-Powered UAV Technologies in Precision Agriculture |
| title_sort | transforming farming a review of ai powered uav technologies in precision agriculture |
| topic | artificial intelligence crops monitoring machine learning precision agriculture remote sensing smart agriculture |
| url | https://www.mdpi.com/2504-446X/8/11/664 |
| work_keys_str_mv | AT juhiagrawal transformingfarmingareviewofaipowereduavtechnologiesinprecisionagriculture AT muhammadyeasirarafat transformingfarmingareviewofaipowereduavtechnologiesinprecisionagriculture |