  This work presents a computer model to discriminate sensor activation in
multi-occupancy environments based on proximity interaction. Current
proximity-based and indoor location methods allow the estimation of the
positions or areas where inhabitants carry out their daily human activities.
The spatial-temporal relation between location and sensor activations is
described in this work to generate a sensor interaction matrix for each
inhabitant. This enables the use of classical HAR models to reduce the
complexity of the multi-occupancy problem. A case study deployed with UWB and
binary sensors is presented.
