Theme Mapping and Bibliometric Analysis of Two Decades of Smart Farming

被引:4
|
作者
Kushartadi, Tri [1 ]
Mulyono, Aditya Eka [1 ]
Al Hamdi, Azhari Haris [1 ]
Rizki, Muhammad Afif [1 ]
Faidar, Muhammad Anwar Sadat [1 ]
Harsanto, Wirawan Dwi [1 ]
Suryanegara, Muhammad [1 ]
Asvial, Muhamad [1 ]
机构
[1] Univ Indonesia, Dept Elect Engn, Depok 16424, Jawa Barat, Indonesia
关键词
bibliometric; smart farming; clustering; machine learning; text mining; AGRICULTURE; GROWTH; INTERNET; THINGS; POPULATION; CHALLENGES;
D O I
10.3390/info14070396
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The estimated global population for 2050 is 9 billion, which implies an increase in food demand. Agriculture is the primary source of food production worldwide, and improving its efficiency and productivity through an integration with information and communication technology system, so-called "smart farming", is a promising approach to optimizing food supply. This research employed bibliometric analysis techniques to investigate smart farming trends, identify their potential benefits, and analyze their research insight. Data were collected from 1141 publications in the Scopus database in the period 1997-2021 and were extracted using VOS Viewer, which quantified the connections between the articles using the co-citation unit, resulting in a mapping of 10 clusters, ranging from agriculture to soil moisture. Finally, the analysis further focuses on the three major themes of smart farming, namely the IoT; blockchain and agricultural robots; and smart agriculture, crops, and irrigation.
引用
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页数:19
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