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.