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http://dx.doi.org/10.6109/jkiice.2016.20.12.2348

Development of a model to analyze the relationship between smart pig-farm environmental data and daily weight increase based on decision tree  

Han, KangHwi (Department of Information and Communication Engineering, Gyeongsang National University)
Lee, Woongsup (Department of Information and Communication Engineering, Gyeongsang National University)
Sung, Kil-Young (Department of Information and Communication Engineering, Gyeongsang National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.20, no.12, 2016 , pp. 2348-2354 More about this Journal
Abstract
In recent days, IoT (Internet of Things) technology has been widely used in the field of agriculture, which enables the collection of environmental data and biometric data into the database. The availability of big data on agriculture results in the increase of the machine learning based analysis. Through the analysis, it is possible to forecast agricultural production and the diseases of livestock, thus helping the efficient decision making in the management of smart farm. Herein, we use the environmental and biometric data of Smart Pig farm to derive the accurate relationship model between the environmental information and the daily weight increase of swine and verify the accuracy of the derived model. To this end, we applied the M5P tree algorithm of machine learning which reveals that the wind speed is the major factor which affects the daily weight increase of swine.
Keywords
Swine; Decision tree; Machine learning; M5P tree algorithm; Smart pig-farm;
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Times Cited By KSCI : 1  (Citation Analysis)
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