• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.7
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• pp.1705-1710
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• 2015

There have been lots of researches and developments for smart agriculture that enables higher efficiency and productivity by applying ICT into the agriculture field recently. However, there still remain many difficulties in purchasing foreign equipments or overseas expansion due to lack of international standards that are internationally approved. Such necessity leads to the international standardization activities driven by domestic experts especially in ITU-T SG13. This paper presents several smart agriculture services based on the service approach that can effectively describe use cases. The proposed architecture of service provision was applied to the document that has been consented as the ITU-T Recommendation Y.2238.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.2B
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• pp.252-262
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• 2010

Recently, the USN (Ubiquitous Sensor Network) technology is emerging as an aspect of digital convergence trends which is being rapidly evolving in the whole society. The technological feasibility for the various application services using the USN is researched in numerous industries, but, in the agricultural field, the market of USN application service, technology adoption and commercialization have been delayed. In the agricultural field, the ubiquitous technologies could lead to huge change in the conventional surroundings such as growth environment of livestock, crop cultivation and harvest. In this paper, to offer a integrated management, we construct a u-swinery(ubiquitous swinery) system which is consisted with USN environmental sensors to collect information from physical phenomenon such as luminance, relative humidity, temperature and ammonia gas. Numbers of CCTV were also installed to monitor inside and outside of the swinery. The u-swinery integrated management system can monitor and control the condition of swinery from remote sites. Furthermore, by gathering the cumulative environmental data from the system, the optimal growth condition for the livestock could be created.