Technologies Driving the Shift to Smart Farming: A Review

被引:30
作者
ElBeheiry, Nabila [1 ]
Balog, Robert S. [1 ]
机构
[1] Texas A&M Univ, Dept Elect & Comp Engn, College Stn, TX 77843 USA
关键词
Actuators; automation; data analysis; deep learning (DL); Internet of Things (IoT); irrigation systems; low-power wide area network (LPWAN); machine learning (ML); microcontrollers; remote monitoring; robotics; smart farming (SF); wireless sensor networks (WSNs); OF-THE-ART; BIG DATA; SENSOR; AGRICULTURE; SYSTEM; OPTIMIZATION; NETWORK;
D O I
10.1109/JSEN.2022.3225183
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
As today's agriculture industry is facing numerous challenges, including climate changes, encroachment of the urban environment, and lack of qualified farmers, there is a need for new practices to ensure sustainable agriculture and food supply. Consequently, there is an emphasis on upgrading farming practices by shifting toward smart farming (SF)-utilizing advanced information and communication technologies to improve the quantity and quality of the crop with minimal labor interference. SF has gained lots of interest in recent years utilizing a variety of technological innovations in the field, which imposes a challenge on farmers and technology integrators to identify suitable technologies and best practices for a particular application. This article provides a survey of the most recent SF scientific literature to identify common practices toward technology integration, challenges, and solutions. The survey was conducted on 588 papers published on the IEEE database following Cochrane methods to ensure appropriate analysis and interpretation of results. The papers' contributions were analyzed to identify necessary technologies that constitute SF, and consequently, research themes were identified. The identified themes are sensors, communication, big data, actuators and machines, and data analysis. Besides presenting an in-depth analysis of each identified theme, this article discusses integrating more than one technology in systems to achieve independency. The most common SF systems are remote monitoring, autonomous, and intelligent decision-making systems.
引用
收藏
页码:1752 / 1769
页数:18
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