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- Title
元宇宙视域下畜牧业智能化路径探索.
- Authors
杨帆; 林青宁; 王琦; 毛世平
- Abstract
The metaverse, as a prominent paradigm in the future digital world, presents a viable framework for the transformation and advancement of the livestock industry. Grounded in the metaverse perspective, this paper explored the pathway for the implementation of intelligent livestock farming, and discussed the current state and existing challenges in the intelligentization of the livestock industry. It proposed an intelligent pathway supported by technologies such as blockchain, artificial intelligence (AI) and the internet of things (IoT). The realization pathway for intelligent livestock farming primarily encompassed the following aspects: firstly, implementing intelligent livestock farming through the utilization of big data and IoT technologies, involving systematic data collection and precise analysis to optmize production efficiency and monitor the health status of animals; secondly, adopting blockchain technology to record the origin, production process, and distribution chain of livestock products, thereby establishing a fully traceable product quality assurance system; thirdly, utilizing virtual education platforms for livestock industry training and education, assisting users in acquiring knowledge and skills within a virtual environment, ultimately enhancing technological innovation capabilities; and finally, leveraging the dual roles of government and market to activate elements such as funds, talent and technology, thereby propelling technological innovation and industry transformation and upgrading in the livestock sector. Based on these considerations, it was anticipated that the guidance of digital technology should lead to the high-quality development of the livestock industry.
- Subjects
TECHNOLOGICAL innovations; ARTIFICIAL intelligence; ANIMAL industry; SHARED virtual environments; LIVESTOCK development; BLOCKCHAINS; DIGITAL technology
- Publication
Journal of Agricultural Science & Technology (1008-0864), 2024, Vol 26, Issue 8, p1
- ISSN
1008-0864
- Publication type
Article
- DOI
10.13304/j.nykjdb.2023.0406