Applying IoT Sensors and Big Data to Improve Precision Crop Production: A Review

Author:

Alahmad Tarek1ORCID,Neményi Miklós1,Nyéki Anikó1ORCID

Affiliation:

1. Department of Biosystems Engineering and Precision Technology, Albert Kázmér Mosonmagyaróvár Faculty of Agricultural and Food Sciences, Széchenyi István University, H-9200 Mosonmagyaróvár, Hungary

Abstract

The potential benefits of applying information and communication technology (ICT) in precision agriculture to enhance sustainable agricultural growth were discussed in this review article. The current technologies, such as the Internet of Things (IoT) and artificial intelligence (AI), as well as their applications, must be integrated into the agricultural sector to ensure long-term agricultural productivity. These technologies have the potential to improve global food security by reducing crop output gaps, decreasing food waste, and minimizing resource use inefficiencies. The importance of collecting and analyzing big data from multiple sources, particularly in situ and on-the-go sensors, is also highlighted as an important component of achieving predictive decision making capabilities in precision agriculture and forecasting yields using advanced yield prediction models developed through machine learning. Finally, we cover the replacement of wired-based, complicated systems in infield monitoring with wireless sensor networks (WSN), particularly in the agricultural sector, and emphasize the necessity of knowing the radio frequency (RF) contributing aspects that influence signal intensity, interference, system model, bandwidth, and transmission range when creating a successful Agricultural Internet of Thing Ag-IoT system. The relevance of communication protocols and interfaces for presenting agricultural data acquired from sensors in various formats is also emphasized in the paper, as is the function of 4G, 3G, and 5G technologies in IoT-based smart farming. Overall, these research sheds light on the significance of wireless sensor networks and big data in the future of precision crop production

Funder

Széchenyi István University

Publisher

MDPI AG

Subject

Agronomy and Crop Science

Reference122 articles.

1. Cukier, K., and Mayer-Schönberger, V. (2014). The Best Writing on Mathematics 2014, Princeton University Press.

2. Big Data and AI Revolution in Precision Agriculture: Survey and Challenges;Bhat;IEEE Access,2021

3. Precision Agriculture—A Worldwide Overview;Zhang;Comput. Electron. Agric.,2002

4. Long-Term Impact of a Precision Agriculture System on Grain Crop Production;Yost;Precis. Agric.,2017

5. Khosla, R. (2010, January 1–6). Precision Agriculture: Challenges and Opportunities in a Flat World. Proceedings of the 19th World Congress of Soil Science, Soil Solutions for a Changing World, Brisbane, QLD, Australia.

Cited by 19 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3