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Personalized adaptive system for elderly care in smart home using fuzzy inference system

Kurnianingsih Kurnianingsih (Politeknik Negeri Semarang, Semarang, Indonesia)
Lukito Edi Nugroho (Universitas Gadjah Mada, Yogyakarta, Indonesia)
Widyawan Widyawan (Universitas Gadjah Mada, Yogyakarta, Indonesia)
Lutfan Lazuardi (Universitas Gadjah Mada, Yogyakarta, Indonesia)
Anton Satria Prabuwono (King Abdulaziz University, Rabigh, Saudi Arabia)
Teddy Mantoro (Sampoerna University, Jakarta, Indonesia)

International Journal of Pervasive Computing and Communications

ISSN: 1742-7371

Article publication date: 3 September 2018

Issue publication date: 3 September 2018

Abstract

Purpose

The decline of the motoric and cognitive functions of the elderly and the high risk of changes in their vital signs lead to some disabilities that inconvenience them. This paper aims to assist the elderly in their daily lives through personalized and seamless technologies.

Design/methodology/approach

The authors developed a personalized adaptive system for elderly care in a smart home using a fuzzy inference system (FIS), which consists of a predictive positioning system, reflexive alert system and adaptive conditioning system. Reflexive sensing is obtained from a body sensor and environmental sensor networks. Three methods comprising the FIS generation algorithm – fuzzy subtractive clustering (FSC), grid partitioning and fuzzy c-means clustering (FCM) – were compared to obtain the best prediction accuracy.

Findings

The results of the experiment showed that FSC produced the best F1-score (96 per cent positioning accuracy, 94 per cent reflexive alert accuracy, 96 per cent air conditioning accuracy and 95 per cent lighting conditioning accuracy), whereas others failed to predict some classes and had lower validation accuracy results. Therefore, it is concluded that FSC is the best FIS generation method for our proposed system.

Social implications

Personalized and seamless technologies for elderly implies life-share awareness, stakeholder awareness and community awareness.

Originality/value

This paper presents a model of personalized adaptive system based on their preferences and medical reference, which consists of a predictive positioning system, reflexive alert system and adaptive conditioning system.

Keywords

Acknowledgements

Conflict of interest: The author declares no potential conflicts of interest.

Citation

Kurnianingsih, K., Nugroho, L.E., Widyawan, W., Lazuardi, L., Prabuwono, A.S. and Mantoro, T. (2018), "Personalized adaptive system for elderly care in smart home using fuzzy inference system", International Journal of Pervasive Computing and Communications, Vol. 14 No. 3/4, pp. 210-232. https://doi.org/10.1108/IJPCC-D-18-00002

Publisher

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Emerald Publishing Limited

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