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A Bibliometric Analysis of Convergence of Artificial Intelligence and Blockchain for Edge of Things

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Abstract

The convergence of Artificial Intelligence (AI) and Blockchain technologies has emerged as a powerful paradigm to address the challenges of data management, security, and privacy in the Edge of Things (EoTs) environment. This bibliometric analysis aims to explore the research landscape and trends surrounding the topic of convergence of AI and Blockchain for EoTs to gain insights into its development and potential implications. For this, research published during the past six years (2018-2023) in the Web of Science indexed sources has been considered as it has been a new field. VoSViewer-based full counting methodology has been used to analyze citation, co-citation, and co-authorship based collaborations among authors, organizations, countries, sources, and documents. The full counting method in VoSViewer involves considering all authors or sources with equal weight when calculating various bibliometric indicators. Co-occurrence, timeline, and burst detection analysis of keywords and published articles were also carried out to unravel significant research trends on the convergence of AI and Blockchain for EoTs. Our findings reveal a steady growth in research output, indicating the increasing importance and interest in AI-enabled Blockchain solutions for EoTs. Further, the analysis uncovered key influential researchers and institutions driving advancements in this domain, shedding light on potential collaborative networks and knowledge hubs. Additionally, the study examines the evolution of research themes over time, offering insights into emerging areas and future research directions. This bibliometric analysis contributes to the understanding of the state-of-the-art in convergence of AI and Blockchain for EoTs, highlighting the most influential works and identifying knowledge gaps. Researchers, industry practitioners, and policymakers can leverage these findings to inform their research strategies and decision-making processes, fostering innovation and advancements in this cutting-edge interdisciplinary field.

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Funding

This research was supported by Basic Science Research Program through the Na-tional Research Foundation of Korea (NRF) funded by the Ministry of Education (2021R1I1A3049788) and Brain Pool program funded by the Ministry of Science and ICT through the National Research Foundation of Korea (2019H1D3A1A01101687, 2021H1D3A2A01099390).

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Authors and Affiliations

  1. Department of Computer Science, Christian-Albrechts-Universität zu Kiel, Kiel, 24118, Schleswig-Holstein, Germany

    Deepak Sharma

  2. Blockchain Technology Research Lab, Department of Computer Science and Engineering, Delhi Technological University, Delhi, 110042, New Delhi, India

    Rajeev Kumar

  3. Department of Software Convergence, Andong National University, Andong, Gyeongbuk, 36729, Gyeongsangbuk-do, Republic of Korea

    Ki-Hyun Jung

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  1. Deepak Sharma
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  2. Rajeev Kumar
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Contributions

R.K. wrote the main manuscript text and D.K. prepared figures and tables. K.-H.J. reviewed the manuscript.

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Correspondence to Rajeev Kumar.

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Sharma, D., Kumar, R. & Jung, KH. A Bibliometric Analysis of Convergence of Artificial Intelligence and Blockchain for Edge of Things. J Grid Computing 21, 79 (2023). https://doi.org/10.1007/s10723-023-09716-4

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