RSS-based localization algorithm for indoor patient tracking

Wah Ching Lee; Faan Hei Hung; Kim Fung Tsang; Chung Kit Wu; Hao Ran Chi

doi:10.1109/INDIN.2016.7819321

RSS-based localization algorithm for indoor patient tracking

Wah Ching Lee, Faan Hei Hung, Kim Fung Tsang, Chung Kit Wu, Hao Ran Chi

The Hong Kong Polytechnic University

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

7 Citations (Scopus)

Abstract

The application of localization in healthcare system is a crucial topic which helps to locate the position of patent or the elderly in case urgency happens. From this aspect, a wireless technology is adopted to provide an efficient localization monitoring system for patients or the elderly in indoor area. The location of patients can be obtained through the developed algorithm. Fuzzy C-Means clustering (FCM) is one of the applicable techniques to locate the position of patients. However, low accuracy of FCM is the main problem. For this reason, the revised FCM localization algorithm, Calibrated Fuzzy C-Means Clustering Algorithm (C-FCM) is proposed in this investigation based on received signal strength (RSS) in wearable device. The proposed algorithm is evaluated through experiment and it has a percentage improvement of 14% compared with FCM.

Original language	English
Title of host publication	Proceedings - 2016 IEEE 14th International Conference on Industrial Informatics, INDIN 2016
Publisher	IEEE
Pages	1060-1064
Number of pages	5
ISBN (Electronic)	9781509028702
DOIs	https://doi.org/10.1109/INDIN.2016.7819321
Publication status	Published - 13 Jan 2017
Event	14th IEEE International Conference on Industrial Informatics, INDIN 2016 - Palais des Congres du Futuroscope, Poitiers, France Duration: 19 Jul 2016 → 21 Jul 2016

Conference

Conference	14th IEEE International Conference on Industrial Informatics, INDIN 2016
Country/Territory	France
City	Poitiers
Period	19/07/16 → 21/07/16

Keywords

clustering
Fuzzy C-Means
received signal strength (RSS)
wearable healthcare

ASJC Scopus subject areas

Computer Science Applications
Information Systems

More information

10.1109/INDIN.2016.7819321

Cite this

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title = "RSS-based localization algorithm for indoor patient tracking",

abstract = "The application of localization in healthcare system is a crucial topic which helps to locate the position of patent or the elderly in case urgency happens. From this aspect, a wireless technology is adopted to provide an efficient localization monitoring system for patients or the elderly in indoor area. The location of patients can be obtained through the developed algorithm. Fuzzy C-Means clustering (FCM) is one of the applicable techniques to locate the position of patients. However, low accuracy of FCM is the main problem. For this reason, the revised FCM localization algorithm, Calibrated Fuzzy C-Means Clustering Algorithm (C-FCM) is proposed in this investigation based on received signal strength (RSS) in wearable device. The proposed algorithm is evaluated through experiment and it has a percentage improvement of 14% compared with FCM.",

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author = "Lee, {Wah Ching} and Hung, {Faan Hei} and Tsang, {Kim Fung} and Wu, {Chung Kit} and Chi, {Hao Ran}",

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Lee, WC, Hung, FH, Tsang, KF, Wu, CK & Chi, HR 2017, RSS-based localization algorithm for indoor patient tracking. in Proceedings - 2016 IEEE 14th International Conference on Industrial Informatics, INDIN 2016., 7819321, IEEE, pp. 1060-1064, 14th IEEE International Conference on Industrial Informatics, INDIN 2016, Poitiers, France, 19/07/16. https://doi.org/10.1109/INDIN.2016.7819321

RSS-based localization algorithm for indoor patient tracking. / Lee, Wah Ching; Hung, Faan Hei; Tsang, Kim Fung et al.
Proceedings - 2016 IEEE 14th International Conference on Industrial Informatics, INDIN 2016. IEEE, 2017. p. 1060-1064 7819321.

Research output: Chapter in book / Conference proceeding › Conference article published in proceeding or book › Academic research › peer-review

TY - GEN

T1 - RSS-based localization algorithm for indoor patient tracking

AU - Lee, Wah Ching

AU - Hung, Faan Hei

AU - Tsang, Kim Fung

AU - Wu, Chung Kit

AU - Chi, Hao Ran

PY - 2017/1/13

Y1 - 2017/1/13

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AB - The application of localization in healthcare system is a crucial topic which helps to locate the position of patent or the elderly in case urgency happens. From this aspect, a wireless technology is adopted to provide an efficient localization monitoring system for patients or the elderly in indoor area. The location of patients can be obtained through the developed algorithm. Fuzzy C-Means clustering (FCM) is one of the applicable techniques to locate the position of patients. However, low accuracy of FCM is the main problem. For this reason, the revised FCM localization algorithm, Calibrated Fuzzy C-Means Clustering Algorithm (C-FCM) is proposed in this investigation based on received signal strength (RSS) in wearable device. The proposed algorithm is evaluated through experiment and it has a percentage improvement of 14% compared with FCM.

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RSS-based localization algorithm for indoor patient tracking

Abstract

Conference

Keywords

ASJC Scopus subject areas

More information

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