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Oliver Amft, Clemens Lombriser, Thomas Stiefmeier, and Gerhard Tröster. Recognition of user activity sequences using distributed event detection. In EuroSSC 2007: Proceedings of the 2nd European Conference on Smart Sensing and Context, pp. 126–141, Springer, October 2007.
We describe and evaluate a distributed architecture for the online recognition of user activity sequences. In a lower layer, simple heterogeneous atomic activities were recognised on multiple on-body and environmental sensor-detector nodes. The atomic activities were grouped in detection events, depending on the detector location. In a second layer, the recognition of composite activities was performed by an integrator. The approach minimises network communication by local activity aggregation at the detector nodes and transforms the temporal activity sequence into a spatial representation for simplified composite recognition. Metrics for a general description of the architecture are presented. We evaluated the architecture in a worker assembly scenario using 12 sensor-detector nodes. An overall recall and precision of 77% and 79% was achieved for 11 different composite activities. The architecture can be scaled in the number of sensor-detectors, activity events and sequences while being adequately quantified by the presented metrics.
@INPROCEEDINGS{Amft2007-P_EuroSSC,
author = {Oliver Amft and Clemens Lombriser and Thomas Stiefmeier and Gerhard
Tr\"oster},
title = {Recognition of user activity sequences using distributed event detection},
booktitle = {EuroSSC 2007: Proceedings of the 2nd European Conference on Smart
Sensing and Context},
year = {2007},
volume = {4793},
series = {Lecture Notes in Computer Science},
pages = {126--141},
month = {October},
publisher = {Springer},
abstract = {We describe and evaluate a distributed architecture for the online
recognition of user activity sequences. In a lower layer, simple
heterogeneous atomic activities were recognised on multiple on-body
and environmental sensor-detector nodes. The atomic activities were
grouped in detection events, depending on the detector location.
In a second layer, the recognition of composite activities was performed
by an integrator. The approach minimises network communication by
local activity aggregation at the detector nodes and transforms the
temporal activity sequence into a spatial representation for simplified
composite
recognition. Metrics for a general description of the architecture
are presented. We evaluated the architecture in a worker assembly
scenario using 12 sensor-detector nodes. An overall recall and precision
of 77\% and 79\% was achieved for 11 different composite activities.
The architecture can be scaled in the number of sensor-detectors,
activity events and sequences while being adequately quantified by
the presented metrics.},
doi = {10.1007/978-3-540-75696-5_8},
file = {Amft2007-P_EuroSSC.pdf:Amft2007-P_EuroSSC.pdf:PDF},
keywords = {Event detection - activity recognition - distributed detectors - activity
sensing - inertial sensors - wireless sensor networks - smart objects},
owner = {oam},
timestamp = {2007/10/09}
}
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