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

arXiv: https://arxiv.org/abs/2211.10355 · HTML: https://mlsanity.com/paper/2211.10355/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 31 references that are in the map.
- First posted on arXiv 3 Nov 2022.

## Builds on (most cited first, 2 of 2)

- [Survey of Security and Privacy Issues of Internet of Things](https://mlsanity.com/paper/1501.02211/) (2015)
- [MoSen: Activity Modelling in Multiple-Occupancy Smart Homes](https://mlsanity.com/paper/2101.00235/) (2021)

## Abstract (arXiv)

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.