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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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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