A Bibliometric and Word Cloud Analysis on the Role of the Internet of Things in Agricultural Plant Disease Detection

Author:

Patil Rutuja Rajendra1ORCID,Kumar Sumit1ORCID,Rani Ruchi2ORCID,Agrawal Poorva3ORCID,Pippal Sanjeev Kumar4ORCID

Affiliation:

1. Symbiosis Institute of Technology, Pune, Symbiosis International (Deemed University), Pune 412115, Maharashtra, India

2. Department of Computer Science, Indian Institute of Information Technology, Kottayam 686635, Kerala, India

3. Symbiosis Institute of Technology, Nagpur, Symbiosis International (Deemed University), Pune 440008, Maharashtra, India

4. Department of Technology, NSBT, MGM University, Aurangabad 431005, Maharashtra, India

Abstract

Agriculture has observed significant advancements since smart farming technology has been introduced.The Green Movement played an essential role in the evolution of farming methods. The use of smart farming is accelerating at an unprecedented rate because it benefits both farmers and consumers by enabling more effective crop budgeting. The Smart Agriculture domain uses the Internet of Things, which helps farmers to monitor irrigation management, estimate crop yields, and manage plant diseases. Additionally, farmers can learn about environmental trends and, as a result, which crops to cultivate and how to apply fungicides and insecticides. This research article uses the primary and subsidiary keywords related to smart agriculture to query the Scopus database. The query returned 146 research articles related to the keywords inputted, and an analysis of 146 scientific publications, including journal articles, book chapters, and patents, was conducted. Node XL, Gephi, and VOSviewer are open-source tools for visualizing and exploring bibliometric networks. New facets of the data are revealed, facilitating intuitive exploration. The survey includes a bibliometric analysis as well as a word cloud analysis. This analysis focuses on publication types and publication regions, geographical locations, documents by year, subject area, association, and authorship. The research field of IoT in agricultural plant disease detection articles is found to frequently employ English as the language of publication.

Publisher

MDPI AG

Subject

Artificial Intelligence,Applied Mathematics,Industrial and Manufacturing Engineering,Human-Computer Interaction,Information Systems,Control and Systems Engineering

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