Information processing and enabling technologies for agricultural energy Internet applications

  • Xiurong Zhang*
  • , Xuanye Zhao
  • , Hamed Badihi
  • , Ammar Al-Bazi
  • , Zhengmao Li
  • , Dawei Qiu
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

This study provides a systematic exposition of the Agricultural Energy Internet (AEI), offering an in-depth analysis within the context of smart agriculture. This work elucidates the evolutionary pathway and emerging trends of AEI, along with the technologies underpinning its implementation. Through a systematic analysis of literature published over the past five years, the study focuses on three key research domains: (1) agricultural electrification, (2) rural energy systems, and (3) smart agriculture, thereby mapping the current research landscape of AEI. Representative studies across different developmental stages are examined to trace the evolution of AEI and its future directions, revealing a clear shift toward integrated multi-scale system-level energy modeling and large-scale AI-driven optimization. This study systematically delineates the technical architecture and evolutionary trajectory of the AEI. Finally, drawing on recent high-impact publications, three frontier research directions are identified: (1) generative AI for smart agriculture, (2) high-efficiency carbon capture technologies, and (3) low-cost energy harvesting systems.
Original languageEnglish
Number of pages18
JournalInformation Processing in Agriculture
Early online date22 Jan 2026
DOIs
Publication statusE-pub ahead of print - 22 Jan 2026

Bibliographical note

Copyright © 2026 The Author(s). Published by Elsevier B.V. on behalf of China Agricultural University. This is an open access article under the CC BY-NC-ND
license ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ).

Keywords

  • Agricultural Energy Internet
  • Low-carbon
  • Microgrid
  • Photovoltaic
  • Smart Agriculture

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