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Mobile robotics in smart farming: current trends and applications
In recent years, precision agriculture and smart farming have been deployed by leaps and bounds as arable land has become increasingly scarce. According to the Food and Agriculture Organization (FAO), by the year 2050, farming in the world should grow by about one-third above current levels. Therefo...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10500442/ https://www.ncbi.nlm.nih.gov/pubmed/37719082 http://dx.doi.org/10.3389/frai.2023.1213330 |
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author | Yépez-Ponce, Darío Fernando Salcedo, José Vicente Rosero-Montalvo, Paúl D. Sanchis, Javier |
author_facet | Yépez-Ponce, Darío Fernando Salcedo, José Vicente Rosero-Montalvo, Paúl D. Sanchis, Javier |
author_sort | Yépez-Ponce, Darío Fernando |
collection | PubMed |
description | In recent years, precision agriculture and smart farming have been deployed by leaps and bounds as arable land has become increasingly scarce. According to the Food and Agriculture Organization (FAO), by the year 2050, farming in the world should grow by about one-third above current levels. Therefore, farmers have intensively used fertilizers to promote crop growth and yields, which has adversely affected the nutritional improvement of foodstuffs. To address challenges related to productivity, environmental impact, food safety, crop losses, and sustainability, mobile robots in agriculture have proliferated, integrating mainly path planning and crop information gathering processes. Current agricultural robotic systems are large in size and cost because they use a computer as a server and mobile robots as clients. This article reviews the use of mobile robotics in farming to reduce costs, reduce environmental impact, and optimize harvests. The current status of mobile robotics, the technologies employed, the algorithms applied, and the relevant results obtained in smart farming are established. Finally, challenges to be faced in new smart farming techniques are also presented: environmental conditions, implementation costs, technical requirements, process automation, connectivity, and processing potential. As part of the contributions of this article, it was possible to conclude that the leading technologies for the implementation of smart farming are as follows: the Internet of Things (IoT), mobile robotics, artificial intelligence, artificial vision, multi-objective control, and big data. One technological solution that could be implemented is developing a fully autonomous, low-cost agricultural mobile robotic system that does not depend on a server. |
format | Online Article Text |
id | pubmed-10500442 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105004422023-09-15 Mobile robotics in smart farming: current trends and applications Yépez-Ponce, Darío Fernando Salcedo, José Vicente Rosero-Montalvo, Paúl D. Sanchis, Javier Front Artif Intell Artificial Intelligence In recent years, precision agriculture and smart farming have been deployed by leaps and bounds as arable land has become increasingly scarce. According to the Food and Agriculture Organization (FAO), by the year 2050, farming in the world should grow by about one-third above current levels. Therefore, farmers have intensively used fertilizers to promote crop growth and yields, which has adversely affected the nutritional improvement of foodstuffs. To address challenges related to productivity, environmental impact, food safety, crop losses, and sustainability, mobile robots in agriculture have proliferated, integrating mainly path planning and crop information gathering processes. Current agricultural robotic systems are large in size and cost because they use a computer as a server and mobile robots as clients. This article reviews the use of mobile robotics in farming to reduce costs, reduce environmental impact, and optimize harvests. The current status of mobile robotics, the technologies employed, the algorithms applied, and the relevant results obtained in smart farming are established. Finally, challenges to be faced in new smart farming techniques are also presented: environmental conditions, implementation costs, technical requirements, process automation, connectivity, and processing potential. As part of the contributions of this article, it was possible to conclude that the leading technologies for the implementation of smart farming are as follows: the Internet of Things (IoT), mobile robotics, artificial intelligence, artificial vision, multi-objective control, and big data. One technological solution that could be implemented is developing a fully autonomous, low-cost agricultural mobile robotic system that does not depend on a server. Frontiers Media S.A. 2023-08-31 /pmc/articles/PMC10500442/ /pubmed/37719082 http://dx.doi.org/10.3389/frai.2023.1213330 Text en Copyright © 2023 Yépez-Ponce, Salcedo, Rosero-Montalvo and Sanchis. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Artificial Intelligence Yépez-Ponce, Darío Fernando Salcedo, José Vicente Rosero-Montalvo, Paúl D. Sanchis, Javier Mobile robotics in smart farming: current trends and applications |
title | Mobile robotics in smart farming: current trends and applications |
title_full | Mobile robotics in smart farming: current trends and applications |
title_fullStr | Mobile robotics in smart farming: current trends and applications |
title_full_unstemmed | Mobile robotics in smart farming: current trends and applications |
title_short | Mobile robotics in smart farming: current trends and applications |
title_sort | mobile robotics in smart farming: current trends and applications |
topic | Artificial Intelligence |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10500442/ https://www.ncbi.nlm.nih.gov/pubmed/37719082 http://dx.doi.org/10.3389/frai.2023.1213330 |
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