Generating Bayesian Network Structures for Self-diagnosis of Sensor Networks in the Context of Ambient Assisted Living for Aging Well View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017-08-12

AUTHORS

Camila Helena Souza Oliveira , Sylvain Giroux , Hubert Ngankam , Hélène Pigot

ABSTRACT

The aging of the population makes it compulsory to develop innovative solutions to foster aging in place. Aiming to offer a solution to this problem, our team works on the development of an autonomic Do-it-Yourself Adaptable Intelligent Domestic Environment (DIY-AIDE) system. In this paper, we propose a self-diagnosis framework that allows the DIY-AIDE system to detect and diagnose its faults. The framework is built based on the Bayesian Network modeling approach. Although powerful, when using BN we have to deal with the construction of the BN structure which happens to be a complex task because of the customized service offered by the DIY-AIDE system. To overcome this challenge, we developed the AAL-based Bayesian Network Construction Algorithm (AAL-BNCA). Through a case study, we show the operation mode of our framework and the performance of AAL-BNCA in diagnosing a system fault in a given assistance scenario. More... »

PAGES

198-210

Book

TITLE

Enhanced Quality of Life and Smart Living

ISBN

978-3-319-66187-2
978-3-319-66188-9

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-66188-9_17

DOI

http://dx.doi.org/10.1007/978-3-319-66188-9_17

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1091160260


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