The Role of Multi-Source Information Fusion Smart Agricultural Integration Platforms in Enhancing Agricultural Efficiency and Regional Adaptation

Yutan Chen; Weijie Song; Weijie Song; Wenying Zhai; Can Hu; Xiaoqing Yuan

Authors

Yutan Chen Deyang Agricultural College, Deyang 618500, Sichuan, China
Weijie Song Deyang Agricultural College, Deyang 618500, Sichuan, China
Weijie Song Deyang Agricultural College, Deyang 618500, Sichuan, China
Wenying Zhai Deyang Agricultural College, Deyang 618500, Sichuan, China
Can Hu Technology R&D Center, Sichuan Teqi Tea Industry Ltd, Chengdu, Sichuan China
Xiaoqing Yuan Technology R&D Center, Sichuan Teqi Tea Industry Ltd, Chengdu, Sichuan China

Keywords:

Smart agriculture, multi-source information fusion, precision agriculture, agricultural efficiency, regional adaptation, sustainable farming, IoT, artificial intelligence

Abstract

The increasing demand for sustainable and adaptive agriculture has accelerated the adoption of smart farming technologies and digital agricultural systems. This study examines the role of multi-source information fusion smart agricultural integration platforms in enhancing agricultural efficiency and supporting regional agricultural adaptation. Drawing upon the Diffusion of Innovation (DOI) Theory and Technology Acceptance Model (TAM), the study proposes a framework linking integrated agricultural information systems, agricultural efficiency, and regional adaptation outcomes. The study highlights the importance of artificial intelligence (AI), Internet of Things (IoT), remote sensing, and real-time analytics in improving precision farming, operational efficiency, and sustainable agricultural resilience. The findings are expected to provide valuable implications for policymakers, researchers, agricultural technologists, and farming communities in promoting sustainable smart agriculture development.