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http://dx.doi.org/10.9708/jksci.2022.27.02.171

A study on Digital Agriculture Data Curation Service Plan for Digital Agriculture  

Lee, Hyunjo (Dept. of Computer Engineering, Jeonbuk National University)
Cho, Han-Jin (Dept. of Energy IT Engineering, Far East University)
Chae, Cheol-Joo (Dept. of General Education, Korea National College of Agriculture and Fisheries)
Publication Information
Journal of the Korea Society of Computer and Information / v.27, no.2, 2022 , pp. 171-177 More about this Journal
Abstract
In this paper, we propose a service method that can provide insight into multi-source agricultural data, way to cluster environmental factor which supports data analysis according to time flow, and curate crop environmental factors. The proposed curation service consists of four steps: collection, preprocessing, storage, and analysis. First, in the collection step, the service system collects and organizes multi-source agricultural data by using an OpenAPI-based web crawler. Second, in the preprocessing step, the system performs data smoothing to reduce the data measurement errors. Here, we adopt the smoothing method for each type of facility in consideration of the error rate according to facility characteristics such as greenhouses and open fields. Third, in the storage step, an agricultural data integration schema and Hadoop HDFS-based storage structure are proposed for large-scale agricultural data. Finally, in the analysis step, the service system performs DTW-based time series classification in consideration of the characteristics of agricultural digital data. Through the DTW-based classification, the accuracy of prediction results is improved by reflecting the characteristics of time series data without any loss. As a future work, we plan to implement the proposed service method and apply it to the smart farm greenhouse for testing and verification.
Keywords
Digital agriculture; Agricultural data; Curation; Clustering; Agricultural environment data;
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Times Cited By KSCI : 4  (Citation Analysis)
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