Artificial Intelligence Best Practices in Smart Agriculture

Faisal Karim Shaikh, Mohsin Ali Memon, Naeem Ahmed Mahoto, Sherali Zeadally, Jamel Nebhen

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Smart agriculture, with the aid of artificial intelligence (AI), is playing a pivotal role to ensure agriculture sustainability. AI techniques are employed in soil and irrigation management, weather forecasting, plant growth, disease prediction, and livestock management, which are considered to be significant domains of agriculture. We review recent AI techniques that have been deployed in these domains. We focus on the various AI algorithms used as well as their performance impact. This review not only highlights the effective use of AI at different layers of a smart agriculture architecture but also identifies future research directions in this field. We found that the deep learning algorithms that have been used in recent studies have performed far better than the conventional machine learning algorithms due to recent technological advances that can efficiently process vast amount of data and enable timely intelligent decisions similar to human decisions.

Original languageEnglish
Pages (from-to)17-24
Number of pages8
JournalIEEE Micro
Volume42
Issue number1
DOIs
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 1981-2012 IEEE.

Keywords

  • Irrigation
  • Livestock
  • Smart Agriculture
  • Soil Management
  • Weather forecasting

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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