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01-06-2011 | Long Paper

Extracting spatiotemporal human activity patterns in assisted living using a home sensor network

Authors: Dimitrios Lymberopoulos, Athanasios Bamis, Andreas Savvides

Published in: Universal Access in the Information Society | Issue 2/2011

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Abstract

This paper presents an automated methodology for extracting the spatiotemporal activity model of a person using a wireless sensor network deployed inside a home. The sensor network is modeled as a source of spatiotemporal symbols whose output is triggered by the monitored person’s motion over space and time. Using this stream of symbols, the problem of human activity modeling is formulated as a spatiotemporal pattern-matching problem on top of the sequence of symbolic information the sensor network produces, and is solved using an exhaustive search algorithm. The effectiveness of the proposed methodology is demonstrated on a real 30-day dataset extracted from an ongoing deployment of a sensor network inside a home monitoring an elder. The developed algorithm examines the person’s data over these 30 days and automatically extracts the person’s daily pattern.

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Title: Extracting spatiotemporal human activity patterns in assisted living using a home sensor network
Authors: Dimitrios Lymberopoulos
Athanasios Bamis
Andreas Savvides
Publication date: 01-06-2011
Publisher: Springer-Verlag
Published in: Universal Access in the Information Society / Issue 2/2011
Print ISSN: 1615-5289
Electronic ISSN: 1615-5297
DOI: https://doi.org/10.1007/s10209-010-0197-5

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