Flexible WSNs Aims Easy Installation With Noise Reduce Method For Elderly People Care

Much research has been conducted on anomaly detection by wireless sensor networks (WSNs). The existing WSNs require specialized knowledge and skills to install the sensors in environments such as houses and buildings. Therefore, we have developed a flexible WSN based on small sensor devices that can...

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Bibliographic Details
Main Authors: Takanobu Otsuka, Takayuki Ito
Format: Article
Language:English
Published: Atlantis Press 2013-07-01
Series:International Journal of Networked and Distributed Computing (IJNDC)
Subjects:
M2M
Online Access:https://www.atlantis-press.com/article/9038.pdf
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spelling doaj-052204aa95f44b35ae551fdc811013cf2020-11-25T02:32:45ZengAtlantis PressInternational Journal of Networked and Distributed Computing (IJNDC)2211-79462013-07-011310.2991/ijndc.2013.1.3.6Flexible WSNs Aims Easy Installation With Noise Reduce Method For Elderly People CareTakanobu OtsukaTakayuki ItoMuch research has been conducted on anomaly detection by wireless sensor networks (WSNs). The existing WSNs require specialized knowledge and skills to install the sensors in environments such as houses and buildings. Therefore, we have developed a flexible WSN based on small sensor devices that can be easily installed. The users only need to place these sensors at the locations where they want to sense and to provide some information to the server through a web page. Then, these small sensor devices automatically create wireless networks, start communicating with the central server for logging continuous data, and show anomalies by using inference based on a basic Bayesian Network. However, a serious problem is that a large amount of noise data prevents correct inferences. Therefore, in this paper, we propose a method for reducing noise data based on location sampling of real human movements. Our experimental results show that our method is effective in increasing the inference accuracy for detecting anomaly data.https://www.atlantis-press.com/article/9038.pdfWireless Sensor NetworksM2MBayesian NetworkAnomaly Detection
collection DOAJ
language English
format Article
sources DOAJ
author Takanobu Otsuka
Takayuki Ito
spellingShingle Takanobu Otsuka
Takayuki Ito
Flexible WSNs Aims Easy Installation With Noise Reduce Method For Elderly People Care
International Journal of Networked and Distributed Computing (IJNDC)
Wireless Sensor Networks
M2M
Bayesian Network
Anomaly Detection
author_facet Takanobu Otsuka
Takayuki Ito
author_sort Takanobu Otsuka
title Flexible WSNs Aims Easy Installation With Noise Reduce Method For Elderly People Care
title_short Flexible WSNs Aims Easy Installation With Noise Reduce Method For Elderly People Care
title_full Flexible WSNs Aims Easy Installation With Noise Reduce Method For Elderly People Care
title_fullStr Flexible WSNs Aims Easy Installation With Noise Reduce Method For Elderly People Care
title_full_unstemmed Flexible WSNs Aims Easy Installation With Noise Reduce Method For Elderly People Care
title_sort flexible wsns aims easy installation with noise reduce method for elderly people care
publisher Atlantis Press
series International Journal of Networked and Distributed Computing (IJNDC)
issn 2211-7946
publishDate 2013-07-01
description Much research has been conducted on anomaly detection by wireless sensor networks (WSNs). The existing WSNs require specialized knowledge and skills to install the sensors in environments such as houses and buildings. Therefore, we have developed a flexible WSN based on small sensor devices that can be easily installed. The users only need to place these sensors at the locations where they want to sense and to provide some information to the server through a web page. Then, these small sensor devices automatically create wireless networks, start communicating with the central server for logging continuous data, and show anomalies by using inference based on a basic Bayesian Network. However, a serious problem is that a large amount of noise data prevents correct inferences. Therefore, in this paper, we propose a method for reducing noise data based on location sampling of real human movements. Our experimental results show that our method is effective in increasing the inference accuracy for detecting anomaly data.
topic Wireless Sensor Networks
M2M
Bayesian Network
Anomaly Detection
url https://www.atlantis-press.com/article/9038.pdf
work_keys_str_mv AT takanobuotsuka flexiblewsnsaimseasyinstallationwithnoisereducemethodforelderlypeoplecare
AT takayukiito flexiblewsnsaimseasyinstallationwithnoisereducemethodforelderlypeoplecare
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