=Paper=
{{Paper
|id=Vol-3930/paper3
|storemode=property
|title=Internet of Things systems and Big data analytics for Smart Agriculture: A bibliometric analysis
|pdfUrl=https://ceur-ws.org/Vol-3930/paper3.pdf
|volume=Vol-3930
|authors=Angeliki Arampatzi,Maria Kamariotou,Kostas E. Psannis,Fotis Kitsios
|dblpUrl=https://dblp.org/rec/conf/haicta/ArampatziKPK24
}}
==Internet of Things systems and Big data analytics for Smart Agriculture: A bibliometric analysis==
https://ceur-ws.org/Vol-3930/paper3.pdf
Internet of Things systems and Big data analytics for
Smart Agriculture: A bibliometric analysis⋆
Angeliki Arampatzi1,∗,†, Maria Kamariotou1,†, Kostas E. Psannis1,† and Fotis Kitsios1,†
1
University of Macedonia, Department of Applied Informatics, 156 Egnatia street, Thessaloniki, Greece
Abstract
By giving farmers access to real-time data on crop yields, soil moisture, and weather patterns, the Internet
of Things (IoT) has grown in importance and transformed the agricultural sector. The goal of this study is
to present a bibliometric analysis of the most recent advancements in Scopus-based research on IoT for
smart agriculture during the previous several years. The study's findings may offer insightful information
to academics, professionals, policymakers, and funding agencies that want a thorough understanding of the
goals and trends going forward in this field. The findings of this research can offer great chances for
collaboration and make it easier to get current information on smart agriculture.
Keywords
Internet of things, Smart agriculture, IoT systems, Big Data Analytics, Sustainability 1
1. Introduction
The current high supply of food is being sustained by a fast growing demand for food production.
The agriculture industry is under a great deal of stress [1-3]. The agriculture industry is facing
increased difficulties as a result of conventional methods, traditional farming practices,
environmental changes brought on by rising global temperatures and altered climatic circumstances
[4-7].
To lessen these difficulties, the agriculture sector must use contemporary technology and
techniques [8-11]. IoT is one of the most innovative technologies in wireless communications today.
IoT is essentially a massive internet-based network that links devices for improved productivity [12-
15]. Modern farming techniques are changing dramatically as a result of the application of the IoT
in the agriculture industry [16-23].
Thus, the goal of this systematic review is to locate literature on the advancement of IoT in
agriculture that has been scientifically proven, with a focus on the points raised.
2. Methodology
A three-phased literature review process proposed by Webster and Watson (2002) [24] was used
to identify studies. Initially, the databases and keywords for the basic search were chosen by
conducting a search of the existing literature reviews. After that, a backward search was conducted
to look through the chosen papers' references, and lastly, a forward search was used to look through
the chosen papers in order to increase their amount. Following the screening process, the papers
were categorized based on their substance.
⋆ Short Paper Proceedings, Volume I of the 11th International Conference on Information and Communication Technologies in
Agriculture, Food & Environment (HAICTA 2024), Karlovasi, Samos, Greece, 17-20 October 2024.
∗
Corresponding author.
†
These authors contributed equally.
a.arampatzi@uom.edu.gr (A. Arampatzi); mkamariotou@uom.edu.gr (M. Kamariotou); kpsannis@uom.edu.gr (K.
Psannis); kitsios@uom.gr (F. Kitsios)
0009-0007-5607-8842 (A. Arampatzi); 0000-0002-7873-9265 (M. Kamariotou); 0000-0003-0020-6394 (K. Psannis); 0000-
0001-7269-5567 (F. Kistios)
© 2024 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
ceur-ws.org 14
ISSN 1613-0073
Proceedings
In order to situate the current literature review in relation to what is currently known about the
topic of IoT and smart agriculture and to investigate prior research in this domain, the literature
review publications from 2021 to 2024 [25-26] are examined. The main goals of these papers were to
define the Internet of Things' characteristics in an agricultural setting and to discuss the latest IoT-
based technologies and how the agriculture industry uses them.
The terms "Internet of Things", “Big data” and "smart agriculture" were used to search the Scopus
database for articles that had been published in peer-reviewed journals. The chosen articles weren't
restricted to any one time frame. The review did not cover books, book chapters, conference
proceedings, technical reports, or working papers. Lastly, only articles published were written in
English.
There were 133 articles published, due to language restrictions and publication source. 108 articles
that were pertinent to the purpose of this work were found after their titles were skimmed. After
looking over their abstracts, 60 were approved. Many of the studies were disqualified because it was
unable to obtain their entire text. To confirm these, a fast investigation was carried out. This second
synopsis made it clear that each one had to be mentioned. Thus, 44 papers were reviewed in their
entirety. A total of 47 articles were revealed after 3 more articles from the forward and backward
searches were added (Figure 1).
Figure 1: Article selection process
The authors, amount of citations, publication year, and keywords were used to categorize the
papers [27].
3. Results
Around 2022, as researchers began looking at IoT technologies that could have an impact on
smart agriculture after realizing how important this sector was, the strong practice of IoT in smart
agriculture emerged. Such a discovery emphasizes the field's significance as well as its ongoing
advancement (Figure 2).
15
Figure 2: Number of papers per year
Twenty-four peer-reviewed journals have published the papers. Agronomy and Sustainability
have each published two papers, while IEEE Access has published three papers. The distribution of
publications according to journals is shown in Table 1.
Table 1
Leading journals
Journal name Cite score Publisher
IEEE Access 9 IEEE
Agronomy 4.3 Wiley
Sustainability 5.8 MDPI
The most frequently cited articles in the field of smart agriculture are included in Table 2 of this
dataset. We obtained the total number of citations for each of these works using Scopus. Next, the
year of publication for each work was taken out of the present year (2024) to determine its age.
Table 2
Top cited papers
Number of citations
Title of paper Age of the paper (in years)
(Retrieved from Scopus)
Internet-of-Things (IoT)-
based smart agriculture: 613 7
Toward making the fields talk
Internet of things for smart
agriculture: Technologies, 340 8
practices and future direction
Internet of Things for the
Future of Smart Agriculture: A
276 3
Comprehensive Survey of
Emerging Technologies
Recent advancements and
challenges of Internet of
267 2
Things in smart agriculture: A
survey
Review of the internet of
things communication
98 3
technologies in smart
agriculture and challenges
16
The 47 papers' most popular keywords and the connections between them were shown using
VOSviewer. Figure 3 displays the network visualization that illustrates the relationship between the
keywords, while Figure 4 displays the heat map. The three most popular keywords are "agricultural
robots," "smart agriculture," and "internet of things" and are located in the yellow area. Additional
terms like "data storage," "drones," "blockchain," and "wireless communication".
Figure 3: Co-keyword network
Figure 4: Heat map
17
4. Conclusions
The following list of limitations pertains to this paper. First, the terms "Internet of Things" and
"smart agriculture" must appear in the paper's title and abstract in order for the article to be found
in a database. There are undoubtedly publications that concentrate on the topic of IoT in smart
agriculture but do not include these keywords in their title. Additionally, the dataset only contained
articles from peer-reviewed journals; yet, relevant papers from conference proceedings and book
chapters are also present. Another drawback is that the search was limited to English publications,
potentially omitting publications written in other languages. The most cited papers, the most active
researchers, or the most active institutions may therefore yield different results when using journals
or publications from other sources.
In terms of theoretical implications, this paper is a bibliometric analysis that offers a broad overview
of a field of study, its development, and the relationships between studies in order to serve as a
foundation for further research by highlighting problems across the research domains of smart
agriculture strategies. This literature study could be expanded upon by future scholars, who could
also include more bibliometric analyses, such co-author or co-citation.
Declaration on Generative AI
The author(s) have not employed any Generative AI tools.
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