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. © Springer-Verlag Berlin Heidelberg 2007.
|Title of host publication||2nd European Conference on Smart Sensing and Context, EuroSSC 2007, 23 October 2007 through 25 October 2007, Kendal|
|Place of Publication||Berlin|
|Publication status||Published - 2007|
|Name||Lecture notes in computer science|