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Discriminating sensor activation in activity recognition within multi-occupancy environments based on nearby interaction

Published 3 Nov 2022 in eess.SP and cs.AI | (2211.10355v1)

Abstract: 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.

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