Smart Media Journal (스마트미디어저널)

THE KOREAN INSTITUTE OF SMART MEDIA (한국스마트미디어학회)
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An Effective Smart Greenhouse Data Preprocessing System for Autonomous Machine Learning

자율 기계 학습을 위한 효과적인 스마트 온실 데이터 전처리 시스템

  • 임종태 (충북대학교 정보통신공학부) ;
  • ;
  • 김윤아 (충북대학교 빅데이터학과) ;
  • 백정현 (국립농업과학원 농업공학부) ;
  • 유재수 (충북대학교 정보통신공학부)
  • Received : 2022.11.28
  • Accepted : 2023.01.06
  • Published : 2023.02.28
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Abstract

Recently, research on a smart farm that creates new values by combining information and communication technology(ICT) with agriculture has been actively done. In order for domestic smart farm technology to have productivity at the same level of advanced agricultural countries, automated decision-making using machine learning is necessary. However, current smart greenhouse data collection technologies in our country are not enough to perform big data analysis or machine learning. In this paper, we design and implement a smart greenhouse data preprocessing system for autonomous machine learning. The proposed system applies target data to various preprocessing techniques. And the proposed system evaluate the performance of each preprocessing technique and store optimal preprocessing technique for each data. Stored optimal preprocessing techniques are used to perform preprocessing on newly collected data

최근 정보통신기술을 농업과 접목해 새로운 가치를 창출하는 스마트팜 연구가 활발하게 진행되고 있다. 국내 스마트팜 기술이 농업 선진국 수준의 생산성을 가지기 위해서는 기계 학습을 활용한 자동화된 의사결정이 필요하다. 그러나 현재의 스마트 온실 데이터 수집 기술은 빅데이터 분석이나 기계 학습을 수행하기에 충분하지 않다. 본 논문에서는 자율 기계 학습을 위한 스마트 온실 데이터 전처리 시스템을 설계하고 구현한다. 제안하는 시스템은 대상 데이터를 다양한 전처리 기법에 적용하고 평가를 수행하여 최적 전처리 기법을 탐색하고 저장한다. 이렇게 탐색 된 최적 전처리 기법은 새롭게 수집된 데이터에 대하여 전처리를 수행하는데 활용된다.

Keywords

Acknowledgement

본 논문은 농촌진흥청 연구사업 (세부과제번호: PJ016247012023)의 지원, 정부(과학기술정보통신부)의 재원으로 한국연구재단의 지원(No.2022R1A2B5B02002456), 그리고 산업통상자원부의 재원으로 한국산업기술진흥원의 지원(P0008421)을 받아 수행된 연구결과임

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