Abstract

The concept of “smart agriculture” relies on the integration of sensors within an Internet of Things (IoT) network. Machine learning (ML) algorithms are integrated at various levels of the IoT system design to augment its functionality and enhance its capability. This article is a bibliometric review of 42 articles published between 2018 and 2022 using the Web of Science database. The results of the review showed an exponential growth in the use of ML algorithms in IoT systems for different agriculture applications. Additionally, two key research questions are addressed in this article, one being the development of IoT -ML-enabled smart agriculture over the past five years, and the second being the main research gaps for applications of machine learning and IoT in smart agriculture. The article concludes with a discussion of the results and future directions for research in the field.

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