Status Checking System of Home Appliances using machine learning

This paper describes status checking system of home appliances based on machine learning, which can be applied to existing household appliances without networking function. Designed status checking system consists of sensor modules, a wireless communication module, cloud server, android application...

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Bibliographic Details
Main Authors: Yoon Chi-Yurl, Kang Shin-Gak
Format: Article
Language:English
Published: EDP Sciences 2017-01-01
Series:MATEC Web of Conferences
Online Access:https://doi.org/10.1051/matecconf/201710808004
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spelling doaj-756fde064f3a4c8396e3b81c344a1d602021-02-02T06:57:32ZengEDP SciencesMATEC Web of Conferences2261-236X2017-01-011080800410.1051/matecconf/201710808004matecconf_icmaa2017_08004Status Checking System of Home Appliances using machine learningYoon Chi-Yurl0Kang Shin-Gak1University of Science and Technology, Information and Communication Network TechnologyETRI, Infrastructure Standard Research Section, Protocol Engineering CenterThis paper describes status checking system of home appliances based on machine learning, which can be applied to existing household appliances without networking function. Designed status checking system consists of sensor modules, a wireless communication module, cloud server, android application and a machine learning algorithm. The developed system applied to washing machine analyses and judges the four-kinds of appliance’s status such as staying, washing, rinsing and spin-drying. The measurements of sensor and transmission of sensing data are operated on an Arduino board and the data are transmitted to cloud server in real time. The collected data are parsed by an Android application and injected into the machine learning algorithm for learning the status of the appliances. The machine learning algorithm compares the stored learning data with collected real-time data from the appliances. Our results are expected to contribute as a base technology to design an automatic control system based on machine learning technology for household appliances in real-time.https://doi.org/10.1051/matecconf/201710808004
collection DOAJ
language English
format Article
sources DOAJ
author Yoon Chi-Yurl
Kang Shin-Gak
spellingShingle Yoon Chi-Yurl
Kang Shin-Gak
Status Checking System of Home Appliances using machine learning
MATEC Web of Conferences
author_facet Yoon Chi-Yurl
Kang Shin-Gak
author_sort Yoon Chi-Yurl
title Status Checking System of Home Appliances using machine learning
title_short Status Checking System of Home Appliances using machine learning
title_full Status Checking System of Home Appliances using machine learning
title_fullStr Status Checking System of Home Appliances using machine learning
title_full_unstemmed Status Checking System of Home Appliances using machine learning
title_sort status checking system of home appliances using machine learning
publisher EDP Sciences
series MATEC Web of Conferences
issn 2261-236X
publishDate 2017-01-01
description This paper describes status checking system of home appliances based on machine learning, which can be applied to existing household appliances without networking function. Designed status checking system consists of sensor modules, a wireless communication module, cloud server, android application and a machine learning algorithm. The developed system applied to washing machine analyses and judges the four-kinds of appliance’s status such as staying, washing, rinsing and spin-drying. The measurements of sensor and transmission of sensing data are operated on an Arduino board and the data are transmitted to cloud server in real time. The collected data are parsed by an Android application and injected into the machine learning algorithm for learning the status of the appliances. The machine learning algorithm compares the stored learning data with collected real-time data from the appliances. Our results are expected to contribute as a base technology to design an automatic control system based on machine learning technology for household appliances in real-time.
url https://doi.org/10.1051/matecconf/201710808004
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AT kangshingak statuscheckingsystemofhomeappliancesusingmachinelearning
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