[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.6109/jicce.2019.17.1.8

Predicting Crop Production for Agricultural Consultation Service

Lee, Soong-Hee (Department of Information and Communications Engineering, Inje University)
Bae, Jae-Yong (Department of Information and Communications Engineering, Inje University)

Publication Information

Journal of information and communication convergence engineering / v.17, no.1, 2019 , pp. 8-13 More about this Journal

Abstract

Smart Farming has been regarded as an important application in information and communications technology (ICT) fields. Selecting crops for cultivation at the pre-production stage is critical for agricultural producers' final profits because over-production and under-production may result in uncountable losses, and it is necessary to predict crop production to prevent these losses. The ITU-T Recommendation for Smart Farming (Y.4450/Y.2238) defines plan/production consultation service at the pre-production stage; this type of service must trace crop production in a predictive way. Several research papers present that machine learning technology can be applied to predict crop production after related data are learned, but these technologies have little to do with standardized ICT services. This paper clarifies the relationship between agricultural consultation services and predicting crop production. A prediction scheme is proposed, and the results confirm the usability and superiority of machine learning for predicting crop production.

Keywords

Agricultural Consultation Service; Machine Learning; Prediction of Crop Production;

Citations & Related Records

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