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Technologies Driving the Shift to Smart Farming: A Review

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journal contribution
submitted on 2023-08-30, 10:16 and posted on 2023-08-30, 10:41 authored by Nabila ElBeheiry, Robert S. Balog

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.

Other Information

Published in: IEEE Sensors Journal
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1109/jsen.2022.3225183

Funding

Open Access funding provided by the Qatar National Library.

History

Language

  • English

Publisher

IEEE

Publication Year

  • 2022

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License

Institution affiliated with

  • Texas A&M University at Qatar