Danger warning via fuzzy inference in an RFID-deployed environment

doi:10.1007/s12652-011-0047-1

機構典藏 > College of Engineering > Graduate Institute & Department of Computer Science and Information Engineering > Journal Article > Item 987654321/92811

Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/92811

Title:	Danger warning via fuzzy inference in an RFID-deployed environment
Authors:	Hsu, Hui-Huang;Chen, Bo-Kai;Lin, Chi-Yi;Leonard Barolli;Makoto Takizawa
Contributors:	淡江大學資訊工程學系
Keywords:	RFID;Fuzzy inference;User feedback;Home safety;Ambient intelligence
Date:	2011-12
Issue Date:	2013-10-23 10:43:24 (UTC+8)
Publisher:	Heidelberg: Springer
Abstract:	The population structure of some developed countries has been changed. Aged population with fewer kids is the main problem. To relieve the burden for caring elder people and kids at home, automatic mechanisms for homecare are needed. In this research, we focus on home safety with the elders and the kids. We aim at developing a RFID-based system that can detect the movement of the user at home. When the user approaches a dangerous location or a dangerous object, the system issues a warning to the caregiver to prevent possible dangerous situations. An active RFID tag is placed at each location and near each object. The user carries an RFID reader which detects the signal strengths of all tags and transmits them to the system in real time. The system issues a warning to the caregiver when the dangerous degree for a dangerous location/object is above the predefined level. A dangerous situation can be prevented if the caregiver watches out beforehand. The dangerous degree is determined through fuzzy inference on the user age and the signal strengths which reflect the distance of the user to a dangerous location/object. Fuzzy membership functions and fuzzy rules are defined in this system. A feedback mechanism is also designed to provide personalized services, which simply modifies the default fuzzy membership function of the corresponding location or object. Experimental results demonstrate that the system is promising in this application.
Relation:	Journal of Ambient Intelligence & Humanized Computing 2(4), pp.285-292
DOI:	10.1007/s12652-011-0047-1
Appears in Collections:	[Graduate Institute & Department of Computer Science and Information Engineering] Journal Article

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