Intelligent agricultural mechanization: A new era engine for agricultural development

Abstract. In recent years, the rapid advancement of technology and the increasing demand for efficient agricultural practices have propelled significant progress in the field of intelligent agricultural mechanization. This paper aims to comprehensively explore this important topic by analyzing the key role of intelligent agricultural mechanization in modern agriculture, examining its technological applications, and identifying prevailing challenges. Intelligent agricultural mechanization involves the integration of cutting-edge technologies such as artificial intelligence, machine learning, and the Internet of Things (IoT) into agricultural machinery and processes, revolutionizing traditional farming methods. Through an in-depth study of relevant literature, it elucidates how intelligent agricultural mechanization can significantly enhance agricultural production efficiency by minimizing resource waste, reducing labor costs, and increasing crop yields. Furthermore, the paper explores the broader implications of these advancements for sustainable development. The research results presented herein seek to provide robust theoretical support and practical guidance for advancing agricultural modernization. In this paper, future development trends are also discussed, including the potential for further innovations and the role of policy and regulatory frameworks in facilitating the adoption of intelligent agricultural mechanization.

Authors

Institutions

Publication Details

Journal
Applied and Computational Engineering
Published
2024-11-08
DOI
https://doi.org/10.54254/2755-2721/102/20240988
Citations
1
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
0.60
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Intelligent agricultural mechanization: A new era engine for agricultural development

Wei Xiang
1 citations
Applied and Computational Engineering
Smart Agriculture and AI
0.60
article

Intelligent agricultural mechanization: A new era engine for agricultural development

Wei Xiang
article en
1 citations

Abstract

Abstract. In recent years, the rapid advancement of technology and the increasing demand for efficient agricultural practices have propelled significant progress in the field of intelligent agricultural mechanization. This paper aims to comprehensively explore this important topic by analyzing the key role of intelligent agricultural mechanization in modern agriculture, examining its technological applications, and identifying prevailing challenges. Intelligent agricultural mechanization involves the integration of cutting-edge technologies such as artificial intelligence, machine learning, and the Internet of Things (IoT) into agricultural machinery and processes, revolutionizing traditional farming methods. Through an in-depth study of relevant literature, it elucidates how intelligent agricultural mechanization can significantly enhance agricultural production efficiency by minimizing resource waste, reducing labor costs, and increasing crop yields. Furthermore, the paper explores the broader implications of these advancements for sustainable development. The research results presented herein seek to provide robust theoretical support and practical guidance for advancing agricultural modernization. In this paper, future development trends are also discussed, including the potential for further innovations and the role of policy and regulatory frameworks in facilitating the adoption of intelligent agricultural mechanization.

Applied and Computational EngineeringVol. 102(1)
Shanghai Jinyuan Senior High School (CN)
Zero hunger
Openalex Percentile: Top 21%
Smart Agriculture and AI
0.60
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.