Elderly people who live alone can be assisted by home monitoring systems that identify risk scenarios such as falls, fatigue symptoms or burglary. Given that these systems have to manage spatiotemporal data, human intervention is required to validate automatic alarms due to the high number of false positives and the need for context interpretation. The goal of this work was to provide tools to support human action, to identify such potential risk scenarios based on spatiotemporal data visualisation.

Spatiotemporal data visualisation for homecare monitoring of elderly people

COMBI, Carlo
2015-01-01

Abstract

Elderly people who live alone can be assisted by home monitoring systems that identify risk scenarios such as falls, fatigue symptoms or burglary. Given that these systems have to manage spatiotemporal data, human intervention is required to validate automatic alarms due to the high number of false positives and the need for context interpretation. The goal of this work was to provide tools to support human action, to identify such potential risk scenarios based on spatiotemporal data visualisation.
Ambient assisted living; Elderly people; Information visualisation; Temporal reasoning; Visual mining
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/930280
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