Scholarlink

Purpose <p>Agriculture is undergoing a profound transformation driven by technological advancements that are reshaping farming practices. Among the diverse array of digital innovations, digital twin technology is creating a virtual model that mirrors the characteristics, behaviors, and processes of a physical entity (crop) or system (the entire farm). It uses real-time data from sensors to replicate real-world objects in a digital environment for monitoring, analysis, and optimization. While this technology has primarily been used in industrial settings, it is increasingly being explored for agricultural applications. However, adapting digital twin technology from industrial to agricultural contexts presents unique challenges due to the distinct nature of agricultural systems.</p> Methods <p>This review explores the basic characteristics of agricultural digital twins and their analytical approaches, highlighting the benefits of integrating other digital innovations with digital twins. It also discusses the unique challenges encountered when adapting industrial digital twin solutions to agricultural contexts, given the complex nature of agricultural systems. Furthermore, the review explores the potential applications and prospects of digital twins in advancing sustainable farming practices.</p> Results <p>The findings highlight the potential of digital twin technology in agriculture, offering improved real-time control, precision in farm operations, and the possibility of self-regulating systems. However, successful implementation necessitates substantial adaptation to address challenges such as variability in biological processes, environmental influences, data integration complexities, and infrastructure constraints. The challenges of adapting digital twin technology from industrial to agricultural applications and strategies to overcome them are discussed in detail.</p> Conclusion <p>Although the adoption of digital twin technology in agriculture is still in its early stages, it has the potential to revolutionize smart farming. The benefits of digital twins, including continuous monitoring and control systems, precise cloud-controlled farm operations, and autonomous self-learning systems for smart farms, position them as a next-generation technology in agriculture.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

From Bytes to Farm: Transferability of Industrial Digital Twins in Agricultural Systems

  • 期刊论文

  • 发表日期：

    2025年2月12日

查看全文
  • V. S. Manivasagam

摘要

Purpose

Agriculture is undergoing a profound transformation driven by technological advancements that are reshaping farming practices. Among the diverse array of digital innovations, digital twin technology is creating a virtual model that mirrors the characteristics, behaviors, and processes of a physical entity (crop) or system (the entire farm). It uses real-time data from sensors to replicate real-world objects in a digital environment for monitoring, analysis, and optimization. While this technology has primarily been used in industrial settings, it is increasingly being explored for agricultural applications. However, adapting digital twin technology from industrial to agricultural contexts presents unique challenges due to the distinct nature of agricultural systems.

Methods

This review explores the basic characteristics of agricultural digital twins and their analytical approaches, highlighting the benefits of integrating other digital innovations with digital twins. It also discusses the unique challenges encountered when adapting industrial digital twin solutions to agricultural contexts, given the complex nature of agricultural systems. Furthermore, the review explores the potential applications and prospects of digital twins in advancing sustainable farming practices.

Results

The findings highlight the potential of digital twin technology in agriculture, offering improved real-time control, precision in farm operations, and the possibility of self-regulating systems. However, successful implementation necessitates substantial adaptation to address challenges such as variability in biological processes, environmental influences, data integration complexities, and infrastructure constraints. The challenges of adapting digital twin technology from industrial to agricultural applications and strategies to overcome them are discussed in detail.

Conclusion

Although the adoption of digital twin technology in agriculture is still in its early stages, it has the potential to revolutionize smart farming. The benefits of digital twins, including continuous monitoring and control systems, precise cloud-controlled farm operations, and autonomous self-learning systems for smart farms, position them as a next-generation technology in agriculture.