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Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis


Citation

Mohd Zawawi, Muhammad Akmal and Jusoh, Mohd Fauzie and Muhammad, Marinah and Naher, Laila and Abdul Latif, Nurul Syaza and Abdul Muttalib, Muhammad Firdaus and Radzuan, Mohd Nazren and Nugroho, Andri Prima (2023) Knowledge mapping trends of Internet of Things (IoT) in plant disease and insect pest study: a visual analysis. Pertanika Journal of Science & Technology, 31 (4). pp. 1-12. ISSN 0128-7680; ESSN: 2231-8526

Abstract

The study and literature on the Internet of Things (IoT) and its applications in agriculture for smart farming are increasing worldwide. However, the knowledge mapping trends related to IoT applications in plant disease, pest management, and control are still unclear and rarely reported. The primary aim of the present study is to identify the current trends and explore hot topics of IoT in plant disease and insect pest research for future research direction. Peer review articles published from Web of Science (WoS) Core Collection (2010-2021) were identified using keywords, and extracted database was analysed scientifically via Microsoft Excel 2019, VOSviewer and R programming software. A total of 231 documents with 5321 cited references authored by 878 scholars showed that the knowledge on the studied area has been growing positively and rapidly for the past ten years. India and China are the most productive countries, comprising more than half (52%) of the total access database on the subject area in WoS. IoT application has been integrated with other knowledge domains, such as machine learning, deep learning, image processing, and artificial intelligence, to produce excellent crop and pest disease monitoring research. This study contributes to the current knowledge of the research topic and suggests possible hot topics for future direction.


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Additional Metadata

Item Type: Article
Divisions: Faculty of Engineering
DOI Number: https://doi.org/10.47836/pjst.31.4.02
Publisher: Universiti Putra Malaysia Press
Keywords: Disease detection; Internet of Things; Pest; Visualisation analysis; Web of science
Depositing User: Ms. Che Wa Zakaria
Date Deposited: 11 Aug 2023 08:49
Last Modified: 11 Aug 2023 08:49
Altmetrics: http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.47836/pjst.31.4.02
URI: http://psasir.upm.edu.my/id/eprint/102064
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