The Future of Artificial Intelligence in Agricultural Field: A Bibliometric Analysis

The Future of Artificial Intelligence in Agricultural Field: A Bibliometric Analysis

Ahmed Karmaoui (Université Moulay Ismail, Meknès, Morocco)
DOI: 10.4018/978-1-6684-4649-2.ch003
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Abstract

Artificial intelligence (AI) is well known for diverse applications in many fields including agriculture. The use of AI in the agricultural field has allowed for optimization in real-time and with less cost and effort. This chapter presents a bibliometric analysis of the future of AI in agriculture. This analysis was carried out using the online Scopus tool and VOSviewer software. The outputs show an increasing trend of documents from 1979 to 2021 and 2020 is the most productive year in terms of quantity. Computer science, engineering, Agricultural and Biological sciences, and environmental science are the main subjects while the United States, China, and India are the most influential in the field. United States, China, and India are the most influential in the field, while article and conference papers are the top two doctypes. For the trend, research in this field is turning toward machine learning, the Internet of things, deep learning, agricultural robots, learning algorithms, big data, data analysis, image processing, support vector machines, and automation.
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Data And Methodology

This chapter presents a bibliometric analysis of the future of AI in agriculture. This analysis was carried out using the online Scopus tool and VOSviewer software. The approach used in this study concerns the diffusion of knowledge (Liu et al., 2017). It was conducted in a large number of studies to explore international collaboration, the co-authorship, the evolution of publications in time (Karmaoui, 2023), the trending analysis (Sereno et al., 2022),

Key Terms in this Chapter

Artificial Intelligence (AI): are advanced computing technologies, introduced by John McCarthy since 1955 and are used in many economic fields including agriculture. They helped to achieve human tasks in real time and with low effort and cost.

Deep Learning: a set of methods for modeling and processing data in a field

The Internet of Things (IoT): refers to physical objects or technologies that assures the connections and exchange of data between systems using primarily internet.

Machine Learning: a scientific branch of artificial intelligence is a computer programming that allows to computers to learn to learn.

Artificial Neural Networks (ANNs): named also neural networks refers to an algorithm or a hardware that simulate or inspired by the human brain functioning.

Antenna: is a device allowing the exchange of electromagnetic waves such as GPS antenna.

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