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http://dx.doi.org/10.9723/jksiis.2020.25.6.015

Big Data Model for Analyzing Plant Growth Environment Informations and Biometric Informations  

Lee, JongYeol (금오공과대학교 소프트웨어공학과)
Moon, ChangBae (금오공과대학교 ICT융합특성화연구센터)
Kim, ByeongMan (금오공과대학교 소프트웨어공학과)
Publication Information
Journal of Korea Society of Industrial Information Systems / v.25, no.6, 2020 , pp. 15-23 More about this Journal
Abstract
While research activities in the agricultural field for climate change are being actively carried out, smart agriculture using information and communication technology has become a new trend in line with the Fourth Industrial Revolution. Accordingly, research is being conducted to identify and respond to signs of abnormal growth in advance by monitoring the stress of crops in various outdoor environments and soil conditions. There are also attempts to analyze data collected in real time through various sensors using artificial intelligence techniques or big data technologies. In this paper, we propose a big data model that is effective in analyzing the growth environment informations and biometric information of crops by using the existing relational database for big data analysis. The performance of the model was measured by the response time to a query according to the amount of data. As a result, it was confirmed that there is a maximum time reduction effect of 23.8%.
Keywords
Big data model; Growth environment informations; Biometric informations; Smart-agriculture; Plants growth index;
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Times Cited By KSCI : 2  (Citation Analysis)
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