A Systematic Review of Current Trends in Artificial Intelligence for Smart Farming to Enhance Crop Yield

M. H. Widianto, Mochamad Iqbal Ardimansyah, Husni Iskandar Pohan, Davy Ronald Hermanus
{"title":"A Systematic Review of Current Trends in Artificial Intelligence for Smart Farming to Enhance Crop Yield","authors":"M. H. Widianto, Mochamad Iqbal Ardimansyah, Husni Iskandar Pohan, Davy Ronald Hermanus","doi":"10.18196/jrc.v3i3.13760","DOIUrl":null,"url":null,"abstract":"Current technology has been widely applied for development, one of which has an Artificial Intelligence (AI) applied to Smart Farming. AI can give special capabilities to be programmed as needed. In cooperation with agricultural systems, AI is part of improving the quality of agriculture. This technology is no stranger to being applied in basic fields such as agriculture. This smart technology is needed to increase crop yields for various regions by utilizing the current trends paper. This is necessary because less land is available for agriculture, and there is a greater need for food sources. Therefore, this systematic review aims to collect the current trends in AI studies for Smart Farming papers using the latest year features from 2018-2022. This paper is handy for researchers and industry in looking for the latest papers on research to enhance crop yields. The authors utilized Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) of 534 articles from IEEE, ACM, MDPI, IAES, and ScienceDirect. After going through a careful process, 67 papers were found that were judged according to the criteria. After the authors got some of the current trends, the author has discussed several factors regarding the results obtained to enhance crop yields, such as Weather, Soil, Irrigation, Unmanned Aerial Vehicle (UAV), Pest Control, Weed Control, and Disease Control.","PeriodicalId":443428,"journal":{"name":"Journal of Robotics and Control (JRC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Robotics and Control (JRC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.18196/jrc.v3i3.13760","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8

Abstract

Current technology has been widely applied for development, one of which has an Artificial Intelligence (AI) applied to Smart Farming. AI can give special capabilities to be programmed as needed. In cooperation with agricultural systems, AI is part of improving the quality of agriculture. This technology is no stranger to being applied in basic fields such as agriculture. This smart technology is needed to increase crop yields for various regions by utilizing the current trends paper. This is necessary because less land is available for agriculture, and there is a greater need for food sources. Therefore, this systematic review aims to collect the current trends in AI studies for Smart Farming papers using the latest year features from 2018-2022. This paper is handy for researchers and industry in looking for the latest papers on research to enhance crop yields. The authors utilized Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) of 534 articles from IEEE, ACM, MDPI, IAES, and ScienceDirect. After going through a careful process, 67 papers were found that were judged according to the criteria. After the authors got some of the current trends, the author has discussed several factors regarding the results obtained to enhance crop yields, such as Weather, Soil, Irrigation, Unmanned Aerial Vehicle (UAV), Pest Control, Weed Control, and Disease Control.
智能农业提高作物产量的人工智能发展趋势综述
目前的技术已经得到了广泛的应用发展,其中就有人工智能(AI)应用于智慧农业。人工智能可以根据需要提供特殊功能。与农业系统合作,人工智能是提高农业质量的一部分。这项技术在农业等基础领域的应用并不陌生。利用当前的趋势,需要这种智能技术来提高各个地区的作物产量。这是必要的,因为可用于农业的土地越来越少,而对食物来源的需求越来越大。因此,本系统综述旨在利用2018-2022年的最新年份特征收集智能农业论文中人工智能研究的当前趋势。这篇论文对研究人员和工业界寻找有关提高作物产量的最新研究论文很有帮助。作者使用了来自IEEE、ACM、MDPI、IAES和ScienceDirect的534篇文章的首选报告项进行系统评价和荟萃分析(PRISMA)。经过仔细的审查,选出了67篇符合标准的论文。在作者了解了当前的一些趋势之后,作者讨论了有关提高作物产量的结果的几个因素,如天气、土壤、灌溉、无人机(UAV)、害虫控制、杂草控制和疾病控制。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
6.30
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信