@inbook{Mü2016,
Author = {Müller, Sebastian and Steen, Enno-Edzard and Hein, Andreas},
Title = {Inferring Multi-Person Presence in Home Sensor Networks},

Year = {2016},
Pages = {0},
Month = {2},
Editor = {Wichert, Reiner; Klausing, Helmut},
Publisher = {Springer International Publishing},
Series = {Advanced Technologies and Societal Change},
chapter = {5},
Doi = {10.1007/978-3-319-26345-8_5},
Url = {http://www.springer.com/de/book/9783319263434},
type = {inbook},
note = {We present an evaluation of two approaches to the problem of inferring the presence of multiple persons in networks of binary sensors. This problem is critical for many applications of Ambient Assisted Living that benefit from knowledge of single- and mul},
Abstract = {We present an evaluation of two approaches to the problem of inferring the presence of multiple persons in networks of binary sensors. This problem is critical for many applications of Ambient Assisted Living that benefit from knowledge of single- and multi-person presence and where data is collected using ambient sensors. Both approaches make use of a graph representing sensors and their spatial relations. One approach uses a simple statistical method to derive a minimum number of people present, the other precisely tracks people through the sensor network. Both approaches are evaluated in a low and higher resolution setting on data of two persons inhabiting a laboratory equipped with motion sensors and contact sensors. Although the latter approach performs well tracking multiple persons, its inability to distinguish inactivity and absence make the former approach more suitable for this task, independent of resolution.}
}
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