A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce
Every nation's economic development depends heavily on agriculture. Fulfilling the current population's need for food is becoming increasingly difficult because of factors including population growth, frequent climate change, and a lack of resources. However, the agriculture sector's...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-09-01
|
| Series: | Scientific African |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468227623002545 |
| _version_ | 1797676245311291392 |
|---|---|
| author | Guduru Dhanush Narendra Khatri Sandeep Kumar Praveen Kumar Shukla |
| author_facet | Guduru Dhanush Narendra Khatri Sandeep Kumar Praveen Kumar Shukla |
| author_sort | Guduru Dhanush |
| collection | DOAJ |
| description | Every nation's economic development depends heavily on agriculture. Fulfilling the current population's need for food is becoming increasingly difficult because of factors including population growth, frequent climate change, and a lack of resources. However, the agriculture sector's biggest problems are a lack of trained workers, urbanization, and a lack of available labour. Automation in agriculture is essential to provide food, fibre, and fuels to the rapidly growing population. Since harvesting is a critical step in farming, the authors present a systematic review of machine vision systems and artificial intelligence algorithms for detecting and harvesting agricultural produce in this article. The areas that are being concentrated on include machine vision systems, vision sensors, and different image processing and artificial intelligence algorithms utilized for detection and harvesting. Review of various image types and vision sensors used in machine vision systems for automated detection and harvesting. It demonstrates how several 3D methods, which were used to obtain the position, orientation, and 3D point cloud of the fruit or crop, function and compare them. Furthermore, it compares various image processing and artificial intelligence algorithms deployed in precision agriculture for detection and harvesting. This article shows how knowledge-based agriculture can boost agriculture produce and quality. |
| first_indexed | 2024-03-11T22:26:13Z |
| format | Article |
| id | doaj.art-c5c50689c75e47c394df8ce5c4fc5859 |
| institution | Directory Open Access Journal |
| issn | 2468-2276 |
| language | English |
| last_indexed | 2024-03-11T22:26:13Z |
| publishDate | 2023-09-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Scientific African |
| spelling | doaj.art-c5c50689c75e47c394df8ce5c4fc58592023-09-24T05:16:06ZengElsevierScientific African2468-22762023-09-0121e01798A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produceGuduru Dhanush0Narendra Khatri1Sandeep Kumar2Praveen Kumar Shukla3Department of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, IndiaDepartment of Mechatronics, Manipal Institute of Technology, Manipal Academy of Higher Education, Manipal 576104, India; Corresponding author: Phone: +91-9460533888.Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Vijaywada 522302, IndiaDepartment of Computer and Communication Engineering, Manipal University Jaipur, Jaipur 303007, Rajasthan, IndiaEvery nation's economic development depends heavily on agriculture. Fulfilling the current population's need for food is becoming increasingly difficult because of factors including population growth, frequent climate change, and a lack of resources. However, the agriculture sector's biggest problems are a lack of trained workers, urbanization, and a lack of available labour. Automation in agriculture is essential to provide food, fibre, and fuels to the rapidly growing population. Since harvesting is a critical step in farming, the authors present a systematic review of machine vision systems and artificial intelligence algorithms for detecting and harvesting agricultural produce in this article. The areas that are being concentrated on include machine vision systems, vision sensors, and different image processing and artificial intelligence algorithms utilized for detection and harvesting. Review of various image types and vision sensors used in machine vision systems for automated detection and harvesting. It demonstrates how several 3D methods, which were used to obtain the position, orientation, and 3D point cloud of the fruit or crop, function and compare them. Furthermore, it compares various image processing and artificial intelligence algorithms deployed in precision agriculture for detection and harvesting. This article shows how knowledge-based agriculture can boost agriculture produce and quality.http://www.sciencedirect.com/science/article/pii/S2468227623002545Machine visionVision sensorsFruit detectionCrop harvesting |
| spellingShingle | Guduru Dhanush Narendra Khatri Sandeep Kumar Praveen Kumar Shukla A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce Scientific African Machine vision Vision sensors Fruit detection Crop harvesting |
| title | A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce |
| title_full | A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce |
| title_fullStr | A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce |
| title_full_unstemmed | A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce |
| title_short | A comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce |
| title_sort | comprehensive review of machine vision systems and artificial intelligence algorithms for the detection and harvesting of agricultural produce |
| topic | Machine vision Vision sensors Fruit detection Crop harvesting |
| url | http://www.sciencedirect.com/science/article/pii/S2468227623002545 |
| work_keys_str_mv | AT gudurudhanush acomprehensivereviewofmachinevisionsystemsandartificialintelligencealgorithmsforthedetectionandharvestingofagriculturalproduce AT narendrakhatri acomprehensivereviewofmachinevisionsystemsandartificialintelligencealgorithmsforthedetectionandharvestingofagriculturalproduce AT sandeepkumar acomprehensivereviewofmachinevisionsystemsandartificialintelligencealgorithmsforthedetectionandharvestingofagriculturalproduce AT praveenkumarshukla acomprehensivereviewofmachinevisionsystemsandartificialintelligencealgorithmsforthedetectionandharvestingofagriculturalproduce AT gudurudhanush comprehensivereviewofmachinevisionsystemsandartificialintelligencealgorithmsforthedetectionandharvestingofagriculturalproduce AT narendrakhatri comprehensivereviewofmachinevisionsystemsandartificialintelligencealgorithmsforthedetectionandharvestingofagriculturalproduce AT sandeepkumar comprehensivereviewofmachinevisionsystemsandartificialintelligencealgorithmsforthedetectionandharvestingofagriculturalproduce AT praveenkumarshukla comprehensivereviewofmachinevisionsystemsandartificialintelligencealgorithmsforthedetectionandharvestingofagriculturalproduce |