Benefits of Dynamically Reconfigurable Activity Recognition in Distributed Sensing Environments
Clemens Lombriser, Oliver Amft, Piero Zappi, Luca Benini, Gerhard Tröster · Atlantis ambient and pervasive intelligence · 2011
The automatic detection of complex human activities in daily life using distributed ambient and on-body sensors is still an open research challenge. A key issue is to construct scalable systems that can capture the large diversity and variety of human activities. Dynamic system reconfiguration is a possible solution to adaptively focus on the current scene and thus reduce recognition complexity. In this work, we evaluate potential energy savings and performance gains of dynamic reconfiguration in a case study using 28 sensors recording 78 activities performed within four settings. Our results show that reconfiguration improves recognition performance by up to 11.48 %, while reducing energy consumption when turning off unneeded sensors by 74.8 %. The granularity of reconfiguration trades off recognition performance for energy savings. These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.