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From Reality to Virtuality: Revolutionizing Livestock Farming Through Digital Twins.

Authors :
Arulmozhi, Elanchezhian
Deb, Nibas Chandra
Tamrakar, Niraj
Kang, Dae Yeong
Kang, Myeong Yong
Kook, Junghoo
Basak, Jayanta Kumar
Kim, Hyeon Tae
Source :
Agriculture; Basel; Dec2024, Vol. 14 Issue 12, p2231, 22p
Publication Year :
2024

Abstract

The impacts of climate change on agricultural production are becoming more severe, leading to increased food insecurity. Adopting more progressive methodologies, like smart farming instead of conventional methods, is essential for enhancing production. Consequently, livestock production is swiftly evolving towards smart farming systems, propelled by rapid advancements in technology such as cloud computing, the Internet of Things, big data, machine learning, augmented reality, and robotics. A Digital Twin (DT), an aspect of cutting-edge digital agriculture technology, represents a virtual replica or model of any physical entity (physical twin) linked through real-time data exchange. A DT conceptually mirrors the state of its physical counterpart in real time and vice versa. DT adoption in the livestock sector remains in its early stages, revealing a knowledge gap in fully implementing DTs within livestock systems. DTs in livestock hold considerable promise for improving animal health, welfare, and productivity. This research provides an overview of the current landscape of digital transformation in the livestock sector, emphasizing applications in animal monitoring, environmental management, precision agriculture, and supply chain optimization. Our findings highlight the need for high-quality data, comprehensive data privacy measures, and integration across varied data sources to ensure accurate and effective DT implementation. Similarly, the study outlines their possible applications and effects on livestock and the challenges and limitations, including concerns about data privacy, the necessity for high-quality data to ensure accurate simulations and predictions, and the intricacies involved in integrating various data sources. Finally, the paper delves into the possibilities of digital twins in livestock, emphasizing potential paths for future research and progress. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20770472
Volume :
14
Issue :
12
Database :
Complementary Index
Journal :
Agriculture; Basel
Publication Type :
Academic Journal
Accession number :
181960033
Full Text :
https://doi.org/10.3390/agriculture14122231