Back to Search
Start Over
Research and Technology Trend Analysis by Big Data-Based Smart Livestock Technology: a Review
- Source :
- Journal of Biosystems Engineering. 46:386-398
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- 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. Prior research data was collected using “ICT,” “IoT,” “information technology (IT),” “ubiquitous technology,” “smart livestock,” and “big data” as main keywords. 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. 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.
- Subjects :
- Data collection
business.industry
Mechanical Engineering
Big data
Information technology
Environmental economics
Agricultural and Biological Sciences (miscellaneous)
Computer Science Applications
Identification (information)
Agriculture
Information and Communications Technology
Livestock
Business
Engineering (miscellaneous)
Productivity
Subjects
Details
- ISSN :
- 22341862 and 17381266
- Volume :
- 46
- Database :
- OpenAIRE
- Journal :
- Journal of Biosystems Engineering
- Accession number :
- edsair.doi...........73c00d38c59ba5b8fc942e2f8baa705b
- Full Text :
- https://doi.org/10.1007/s42853-021-00115-9