An Effective Smart Greenhouse Data Preprocessing System for Autonomous Machine Learning

Jongtae Lim, Jae-soo Yoo, Christopher RETITI DIOP EMANE, Y. Kim, Jeong-Hyun Beak
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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
一种有效的智能温室自主机器学习数据预处理系统
最近,正在积极研究将信息通信技术(ICT)与农业相结合,创造新价值的智能农场。为了使国内智能农场技术的生产力达到先进农业国家的水平,需要利用机器学习进行自动化决策。然而,我国目前的智能温室数据采集技术还不足以进行大数据分析或机器学习。在本文中,我们设计并实现了一个智能温室数据预处理系统,用于自主机器学习。该系统将目标数据应用于各种预处理技术。该系统对各种预处理技术的性能进行评价,并存储每种数据的最优预处理技术。采用存储最优预处理技术对新采集的数据进行预处理
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