RSS-based localization algorithm for indoor patient tracking

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

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

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 languageEnglish
Title of host publicationProceedings - 2016 IEEE 14th International Conference on Industrial Informatics, INDIN 2016
PublisherIEEE
Pages1060-1064
Number of pages5
ISBN (Electronic)9781509028702
DOIs
Publication statusPublished - 13 Jan 2017
Event14th IEEE International Conference on Industrial Informatics, INDIN 2016 - Palais des Congres du Futuroscope, Poitiers, France
Duration: 19 Jul 201621 Jul 2016

Conference

Conference14th IEEE International Conference on Industrial Informatics, INDIN 2016
Country/TerritoryFrance
CityPoitiers
Period19/07/1621/07/16

Keywords

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

ASJC Scopus subject areas

  • Computer Science Applications
  • Information Systems

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