Apply data mining on location-based healthcare system

Chen Yang Cheng; Ja Hao Chen; Tsuo Hung Lan; Chin Hong Chan; Yu Hsun Huang

doi:10.1007/978-3-642-28807-4_47

Apply data mining on location-based healthcare system

Chen Yang Cheng^*, Ja Hao Chen, Tsuo Hung Lan, Chin Hong Chan, Yu Hsun Huang

^*Corresponding author for this work

Department of Psychiatry

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Scopus citations

Abstract

In recent years, mostly hospital substantially applied Zigbee to establish wireless sensor networks for avoiding human errors and decreasing potential healthcare safety problems. Current researches mostly focused on patients' physiological signals like their heart beats and body temperatures monitoring. However, the patient localization was seldom mentioned, which made the healthcare personnel fail to notice that patients might step into potential dangerous areas and be in danger. For that reason, the main idea of this research is to propose a two-step clustering localization algorithm combining the ZigBee Wireless Sensor Network. With this technology, a real-time monitoring healthcare system could be constructed to enhance the accuracy of tracking patients' location.

Original language	English
Title of host publication	Recent Progress in Data Engineering and Internet Technology
Pages	337-342
Number of pages	6
Edition	VOL. 1
DOIs	https://doi.org/10.1007/978-3-642-28807-4_47
State	Published - 2013
Event	International Conference on Data Engineering and Internet Technology, DEIT 2011 - Bali, Indonesia Duration: 15 Mar 2012 → 17 Mar 2012

Publication series

Name	Lecture Notes in Electrical Engineering
Number	VOL. 1
Volume	156 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	International Conference on Data Engineering and Internet Technology, DEIT 2011
Country/Territory	Indonesia
City	Bali
Period	15/03/12 → 17/03/12

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-642-28807-4_47

Cite this

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title = "Apply data mining on location-based healthcare system",

abstract = "In recent years, mostly hospital substantially applied Zigbee to establish wireless sensor networks for avoiding human errors and decreasing potential healthcare safety problems. Current researches mostly focused on patients' physiological signals like their heart beats and body temperatures monitoring. However, the patient localization was seldom mentioned, which made the healthcare personnel fail to notice that patients might step into potential dangerous areas and be in danger. For that reason, the main idea of this research is to propose a two-step clustering localization algorithm combining the ZigBee Wireless Sensor Network. With this technology, a real-time monitoring healthcare system could be constructed to enhance the accuracy of tracking patients' location.",

author = "Cheng, {Chen Yang} and Chen, {Ja Hao} and Lan, {Tsuo Hung} and Chan, {Chin Hong} and Huang, {Yu Hsun}",

year = "2013",

doi = "10.1007/978-3-642-28807-4_47",

language = "English",

isbn = "9783642288067",

series = "Lecture Notes in Electrical Engineering",

number = "VOL. 1",

pages = "337--342",

booktitle = "Recent Progress in Data Engineering and Internet Technology",

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note = "International Conference on Data Engineering and Internet Technology, DEIT 2011 ; Conference date: 15-03-2012 Through 17-03-2012",

}

Cheng, CY, Chen, JH, Lan, TH, Chan, CH & Huang, YH 2013, Apply data mining on location-based healthcare system. in Recent Progress in Data Engineering and Internet Technology. VOL. 1 edn, Lecture Notes in Electrical Engineering, no. VOL. 1, vol. 156 LNEE, pp. 337-342, International Conference on Data Engineering and Internet Technology, DEIT 2011, Bali, Indonesia, 15/03/12. https://doi.org/10.1007/978-3-642-28807-4_47

Apply data mining on location-based healthcare system. / Cheng, Chen Yang; Chen, Ja Hao; Lan, Tsuo Hung et al.
Recent Progress in Data Engineering and Internet Technology. VOL. 1. ed. 2013. p. 337-342 (Lecture Notes in Electrical Engineering; Vol. 156 LNEE, No. VOL. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Chan, Chin Hong

AU - Huang, Yu Hsun

PY - 2013

Y1 - 2013

N2 - In recent years, mostly hospital substantially applied Zigbee to establish wireless sensor networks for avoiding human errors and decreasing potential healthcare safety problems. Current researches mostly focused on patients' physiological signals like their heart beats and body temperatures monitoring. However, the patient localization was seldom mentioned, which made the healthcare personnel fail to notice that patients might step into potential dangerous areas and be in danger. For that reason, the main idea of this research is to propose a two-step clustering localization algorithm combining the ZigBee Wireless Sensor Network. With this technology, a real-time monitoring healthcare system could be constructed to enhance the accuracy of tracking patients' location.

AB - In recent years, mostly hospital substantially applied Zigbee to establish wireless sensor networks for avoiding human errors and decreasing potential healthcare safety problems. Current researches mostly focused on patients' physiological signals like their heart beats and body temperatures monitoring. However, the patient localization was seldom mentioned, which made the healthcare personnel fail to notice that patients might step into potential dangerous areas and be in danger. For that reason, the main idea of this research is to propose a two-step clustering localization algorithm combining the ZigBee Wireless Sensor Network. With this technology, a real-time monitoring healthcare system could be constructed to enhance the accuracy of tracking patients' location.

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BT - Recent Progress in Data Engineering and Internet Technology

T2 - International Conference on Data Engineering and Internet Technology, DEIT 2011

Y2 - 15 March 2012 through 17 March 2012

ER -

Apply data mining on location-based healthcare system

Abstract

Publication series

Conference

UN SDGs

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