Research Article
Open Access
Research on Adaptive Improvement and Promotion Path of Intelligent Agricultural Machinery in Hilly and Mountainous Areas
1
School of Economics and Management, Beijing City University, Beijing 101309, China
* Corresponding Author:
Xuyan Jiang,
[email protected]
Volume 1, Issue 2
2025
Received: 14 July 2025
Accepted: 25 December 2025
Published: 29 December 2025
Article Information
Abstract
Hilly and mountainous areas account for 69% of China’s land area and undertake critical agricultural production tasks, but the poor adaptability of mainstream intelligent agricultural machinery and inefficient promotion models have become key bottlenecks restricting agricultural modernization. This study’s core innovation lies in constructing a ``four-dimensional integrated solution'' (equipment lightweight improvement - dynamic control optimization - hybrid sharing promotion - farmland mechanization-friendly transformation) and quantifying the coupling mechanism between topographic constraints and agricultural machinery performance. By introducing plot shape coefficient and slope volatility into the Terrain Adaptability Index (TAI), a lightweight intelligent harvester with 32% weight reduction and stable operation on 25° slopes was developed, and a Beidou RTK-based dynamic path planning system was also designed. Field tests in Hunan and Chongqing showed that the integrated solution increased operation efficiency by 250% and reduced costs by 59.3% compared with traditional methods. This research provides a systematic technical paradigm and promotion strategy for agricultural intelligence in hilly and mountainous regions worldwide.
Graphical Abstract
Keywords
intelligent agricultural machinery
hilly and mountainous areas
terrain adaptability
path planning
sharing service model
farmland mechanization-friendly transformation
Data Availability Statement
Data will be made available on request.
Funding
This work was supported by the General Project of Beijing Municipal Education Science 14th Five-Year Plan 2025 (Application Research on Enhancing Teaching Capability through Generative AI within the AI-TPACK Framework) under Grant CDGB25543.
Conflicts of Interest
The authors declare no conflicts of interest.
Ethical Approval and Consent to Participate
Not applicable.
References
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APA Style
Wei, Y., Jiang, X., Liu, C., & Li, R. (2025). Research on Adaptive Improvement and Promotion Path of Intelligent Agricultural Machinery in Hilly and Mountainous Areas. Digital Intelligence in Agriculture, 1(2), 110–119. https://doi.org/10.62762/DIA.2025.914623
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TY - JOUR AU - Wei, Yongqiang AU - Jiang, Xuyan AU - Liu, Chang AU - Li, Rui PY - 2025 DA - 2025/12/29 TI - Research on Adaptive Improvement and Promotion Path of Intelligent Agricultural Machinery in Hilly and Mountainous Areas JO - Digital Intelligence in Agriculture T2 - Digital Intelligence in Agriculture JF - Digital Intelligence in Agriculture VL - 1 IS - 2 SP - 110 EP - 119 DO - 10.62762/DIA.2025.914623 UR - https://www.icck.org/article/abs/DIA.2025.914623 KW - intelligent agricultural machinery KW - hilly and mountainous areas KW - terrain adaptability KW - path planning KW - sharing service model KW - farmland mechanization-friendly transformation AB - Hilly and mountainous areas account for 69% of China’s land area and undertake critical agricultural production tasks, but the poor adaptability of mainstream intelligent agricultural machinery and inefficient promotion models have become key bottlenecks restricting agricultural modernization. This study’s core innovation lies in constructing a ``four-dimensional integrated solution'' (equipment lightweight improvement - dynamic control optimization - hybrid sharing promotion - farmland mechanization-friendly transformation) and quantifying the coupling mechanism between topographic constraints and agricultural machinery performance. By introducing plot shape coefficient and slope volatility into the Terrain Adaptability Index (TAI), a lightweight intelligent harvester with 32% weight reduction and stable operation on 25° slopes was developed, and a Beidou RTK-based dynamic path planning system was also designed. Field tests in Hunan and Chongqing showed that the integrated solution increased operation efficiency by 250% and reduced costs by 59.3% compared with traditional methods. This research provides a systematic technical paradigm and promotion strategy for agricultural intelligence in hilly and mountainous regions worldwide. SN - 3069-3187 PB - Institute of Central Computation and Knowledge LA - English ER -
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@article{Wei2025Research,
author = {Yongqiang Wei and Xuyan Jiang and Chang Liu and Rui Li},
title = {Research on Adaptive Improvement and Promotion Path of Intelligent Agricultural Machinery in Hilly and Mountainous Areas},
journal = {Digital Intelligence in Agriculture},
year = {2025},
volume = {1},
number = {2},
pages = {110-119},
doi = {10.62762/DIA.2025.914623},
url = {https://www.icck.org/article/abs/DIA.2025.914623},
abstract = {Hilly and mountainous areas account for 69\% of China’s land area and undertake critical agricultural production tasks, but the poor adaptability of mainstream intelligent agricultural machinery and inefficient promotion models have become key bottlenecks restricting agricultural modernization. This study’s core innovation lies in constructing a ``four-dimensional integrated solution'' (equipment lightweight improvement - dynamic control optimization - hybrid sharing promotion - farmland mechanization-friendly transformation) and quantifying the coupling mechanism between topographic constraints and agricultural machinery performance. By introducing plot shape coefficient and slope volatility into the Terrain Adaptability Index (TAI), a lightweight intelligent harvester with 32\% weight reduction and stable operation on 25° slopes was developed, and a Beidou RTK-based dynamic path planning system was also designed. Field tests in Hunan and Chongqing showed that the integrated solution increased operation efficiency by 250\% and reduced costs by 59.3\% compared with traditional methods. This research provides a systematic technical paradigm and promotion strategy for agricultural intelligence in hilly and mountainous regions worldwide.},
keywords = {intelligent agricultural machinery, hilly and mountainous areas, terrain adaptability, path planning, sharing service model, farmland mechanization-friendly transformation},
issn = {3069-3187},
publisher = {Institute of Central Computation and Knowledge}
}
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