Indoor Location IoT Analytics “in the wild”: Active and Healthy Ageing Cases

TitleIndoor Location IoT Analytics “in the wild”: Active and Healthy Ageing Cases
Publication TypeBook Chapter
Year of Publication2016
AuthorsKonstantinidis, Evdokimos, Billis Antonis S., Plotegher Leonardo, Conti Giuseppe, and Bamidis Panagiotis D.
Book TitleXIV Mediterranean Conference on Medical and Biological Engineering and Computing, MEDICON
Pagination1225-1230
KeywordsActive and Healthy Ageing, gait analysis, indoor location, IoT analytics
Abstract

Early detection of cognitive and physical status
deterioration for elderly people has been much dependent on gait analysis lately. However, much of the recent literature fo- cuses on gait analysis methodologies exploiting average speed. This presents a serious constraint when gait analysis is supposed to drive context aware applications. To this end, this work ap- plies density based clustering algorithms on gait and trajectory IoT data recorded from real senior homes ("on the wild"). The indoor analytics client analyzes high density regions rendered from locations in real senior homes facilitated by IoT technology consisting of events describing the seniors’ position. These are collected, analyzed and made available by the indoor analytics client taking into account the available processing resources and configuring itself to deliver the analytics outcome even when it is hosted in hardware with constrained resources. Promising re- sults are obtained by analyzing a whole week's data in two sen- iors’ homes. The algorithm performance and accuracy with re- spect to the number of points included in the analysis are presented and discussed.

URLhttp://link.springer.com/10.1007/978-3-319-32703-7_236
DOI10.1007/978-3-319-32703-7_236