Exploring the Integration of Industry 4.0 Technologies in Agriculture: A Comprehensive Bibliometric Review

Benedetta Fasciolo (), Luigi Panza and Franco Lombardi
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Benedetta Fasciolo: Department of Management and Production Engineering, Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy
Luigi Panza: Department of Management and Production Engineering, Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy
Franco Lombardi: Department of Management and Production Engineering, Politecnico di Torino, Corso Duca Degli Abruzzi 24, 10129 Torino, Italy

Sustainability, 2024, vol. 16, issue 20, 1-20

Abstract: While it is essential to increase agricultural production to meet the needs of a growing global population, this task is becoming increasingly difficult due to the environmental challenges faced in recent decades. A promising solution to enhance the efficiency and sustainability of agricultural production is the integration of Industry 4.0 technologies, such as IoT, UAVs, AI, and Blockchain. However, despite their potential, there is a lack of comprehensive bibliometric analyses that cover the full range of these technologies in agriculture. This gap limits understanding of their integration and impact. This study aims to provide a holistic bibliometric analysis of the integration of Industry 4.0 technologies in agriculture, identifying key research trends and gaps. We analyzed relevant literature using the Scopus database and VOSviewer software (version 1.6.20, Centre for Science and Technology Studies, Leiden University, The Netherlands)and identified five major thematic clusters within Agriculture 4.0. These clusters were examined to understand the included technologies and their roles in promoting sustainable agricultural practices. The study also identified unexplored technologies that present opportunities for future research. This paper offers a comprehensive overview of the current research landscape in Agriculture 4.0, highlighting areas for innovation and development, and serves as a valuable resource for enhancing sustainable agricultural practices through technological integration.

Keywords: agriculture; industry 4.0; IoT; robotics; blockchain; digital twin; machine learning (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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