Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review
Orchard monitoring is a vital direction of scientific research and practical application for increasing fruit production in ecological conditions. Recently, due to the development of technology and the decrease in equipment cost, the use of unmanned aerial vehicles and artificial intelligence algori...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-11-01
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| Series: | Frontiers in Plant Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fpls.2023.1237695/full |
| _version_ | 1827632517795020800 |
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| author | Dan Popescu Loretta Ichim Florin Stoican |
| author_facet | Dan Popescu Loretta Ichim Florin Stoican |
| author_sort | Dan Popescu |
| collection | DOAJ |
| description | Orchard monitoring is a vital direction of scientific research and practical application for increasing fruit production in ecological conditions. Recently, due to the development of technology and the decrease in equipment cost, the use of unmanned aerial vehicles and artificial intelligence algorithms for image acquisition and processing has achieved tremendous progress in orchards monitoring. This paper highlights the new research trends in orchard monitoring, emphasizing neural networks, unmanned aerial vehicles (UAVs), and various concrete applications. For this purpose, papers on complex topics obtained by combining keywords from the field addressed were selected and analyzed. In particular, the review considered papers on the interval 2017-2022 on the use of neural networks (as an important exponent of artificial intelligence in image processing and understanding) and UAVs in orchard monitoring and production evaluation applications. Due to their complexity, the characteristics of UAV trajectories and flights in the orchard area were highlighted. The structure and implementations of the latest neural network systems used in such applications, the databases, the software, and the obtained performances are systematically analyzed. To recommend some suggestions for researchers and end users, the use of the new concepts and their implementations were surveyed in concrete applications, such as a) identification and segmentation of orchards, trees, and crowns; b) detection of tree diseases, harmful insects, and pests; c) evaluation of fruit production, and d) evaluation of development conditions. To show the necessity of this review, in the end, a comparison is made with review articles with a related theme. |
| first_indexed | 2024-03-09T14:46:42Z |
| format | Article |
| id | doaj.art-af66b434d7cd446c9d07a5f40c855a93 |
| institution | Directory Open Access Journal |
| issn | 1664-462X |
| language | English |
| last_indexed | 2024-03-09T14:46:42Z |
| publishDate | 2023-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Plant Science |
| spelling | doaj.art-af66b434d7cd446c9d07a5f40c855a932023-11-27T04:48:37ZengFrontiers Media S.A.Frontiers in Plant Science1664-462X2023-11-011410.3389/fpls.2023.12376951237695Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic reviewDan PopescuLoretta IchimFlorin StoicanOrchard monitoring is a vital direction of scientific research and practical application for increasing fruit production in ecological conditions. Recently, due to the development of technology and the decrease in equipment cost, the use of unmanned aerial vehicles and artificial intelligence algorithms for image acquisition and processing has achieved tremendous progress in orchards monitoring. This paper highlights the new research trends in orchard monitoring, emphasizing neural networks, unmanned aerial vehicles (UAVs), and various concrete applications. For this purpose, papers on complex topics obtained by combining keywords from the field addressed were selected and analyzed. In particular, the review considered papers on the interval 2017-2022 on the use of neural networks (as an important exponent of artificial intelligence in image processing and understanding) and UAVs in orchard monitoring and production evaluation applications. Due to their complexity, the characteristics of UAV trajectories and flights in the orchard area were highlighted. The structure and implementations of the latest neural network systems used in such applications, the databases, the software, and the obtained performances are systematically analyzed. To recommend some suggestions for researchers and end users, the use of the new concepts and their implementations were surveyed in concrete applications, such as a) identification and segmentation of orchards, trees, and crowns; b) detection of tree diseases, harmful insects, and pests; c) evaluation of fruit production, and d) evaluation of development conditions. To show the necessity of this review, in the end, a comparison is made with review articles with a related theme.https://www.frontiersin.org/articles/10.3389/fpls.2023.1237695/fullorchard monitoringunmanned aerial vehicledatasetimage processingneural networkobject detection |
| spellingShingle | Dan Popescu Loretta Ichim Florin Stoican Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review Frontiers in Plant Science orchard monitoring unmanned aerial vehicle dataset image processing neural network object detection |
| title | Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review |
| title_full | Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review |
| title_fullStr | Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review |
| title_full_unstemmed | Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review |
| title_short | Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review |
| title_sort | orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks a systematic review |
| topic | orchard monitoring unmanned aerial vehicle dataset image processing neural network object detection |
| url | https://www.frontiersin.org/articles/10.3389/fpls.2023.1237695/full |
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