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http://dx.doi.org/10.12791/KSBEC.2021.30.1.019

Identification of Sweet Pepper Greenhouse by Analysis of Environmental Data in Greenhouse  

Kim, Na-eun (Department of Bio-Systems Engineering, Graduate School of Gyeonsang National University)
Lee, Kyoung-geun (Gyeongsangnam-do Agricultural Research & Extension Services)
Lee, Deog-hyun (Department of Bio-Systems Engineering, Graduate School of Gyeonsang National University)
Moon, Byeong-eun (Institute of Smart Farm, Gyeongsang National University)
Park, Jae-sung (Institute of Smart Farm, Gyeongsang National University)
Kim, Hyeon-tae (Department of Bio-Industrial Machinery Engineering, Gyeongsang National University(Institute of Smart Farm))
Publication Information
Journal of Bio-Environment Control / v.30, no.1, 2021 , pp. 19-26 More about this Journal
Abstract
In this study, analysis was performed to identify three greenhouses located in the same area using principal component analysis (PCA) and linear discrimination analysis (LDA). The environmental data in the greenhouse were from 3 farms in the same area, and the values collected at 1 hour intervals for a total of 4 weeks from April 1 to April 28 were used. Before analyzing the data, it was pre-processed to normalize the data, and the analysis was performed by dividing it into 80% of the training data and 20% of the test data. As a result of PCA and LDA analysis, it was found that PCA classification accuracy was 57.51% and LDA classification was 67.06%, indicating that it can be classified by greenhouse. Based on the farmhouse data classified in advance, the data of the new environment can be classified into specific groups to determine the tendency of the data. Such data is judged to be a way to increase the utilization of data by facilitating identification.
Keywords
big data; classification; LDA; smart farm; PCA;
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