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Research and Technology Trend Analysis by Big Data-Based Smart Livestock Technology: a Review

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Abstract

Purpose

This study introduces the global research and technological trends related to various kinds of Information and Communications Technologies (ICTs) used and applied in the livestock industry by improving productivity via breeding, disease and optimal environment control, and smart business management.

Method

Prior research data was collected using “ICT,” “IoT,” “information technology (IT),” “ubiquitous technology,” “smart livestock,” and “big data” as main keywords.

Results

Most livestock farms in Korea adopt smart livestock technology that are mostly used in the 1st or 1.5th generations, while continuous developments are being carried out for technologies of the 2nd and 3rd generations. In the livestock house, camera vision, radio-frequency identification (RFID), beacon sensors, and environmental sensors are used in livestock farms and houses to collect information compiled into a database to introduce an automated system for livestock management.

Conclusion

The data collected from each individual and farm can enable precise breeding and ultimately improve the productivity and efficiency of smart livestock systems. It is necessary to prepare a systematic system at the national level for data collection, ownership, and sharing to improve the productivity and efficiency of the smart livestock system.

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Funding

This study was supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) through the Smart Animal Farming Industry Technology Development Program funded by the Ministry of Agriculture, Food, and Rural Affairs (MAFRA) (Grant No. 320097–1).

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Correspondence to Changyeun Mo.

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Conflict of Interest

The authors declare no competing interests.

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Cite this article

Kim, MJ., Mo, C., Kim, H.T. et al. Research and Technology Trend Analysis by Big Data-Based Smart Livestock Technology: a Review. J. Biosyst. Eng. 46, 386–398 (2021). https://doi.org/10.1007/s42853-021-00115-9

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  • DOI: https://doi.org/10.1007/s42853-021-00115-9

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