# NSense: A People-centric, non-intrusive Opportunistic Sensing Tool for Contextualizing Nearness

## TL;DR

NSense is a non-intrusive, people-centric sensing tool designed to infer social interaction patterns to promote social well-being, validated through experiments in realistic settings.

## Contribution

The paper introduces NSense, a novel tool that captures and infers social interactions using non-intrusive sensing, advancing social well-being applications.

## Key findings

- NSense accurately infers social interaction context.
- Experimental validation shows reliable performance in realistic settings.
- Trace data is publicly available for further research.

## Abstract

In the context of social well-being and context awareness several eHealth applications have been focused on tracking activities, such as sleep or specific fitness habits, with the purpose of promoting physical well-being with increasing success. Sensing technology can, however, be applied to improve social well-being, in addition to physical well-being. This paper addresses NSense, a tool that has been developed to capture and to infer social interaction patterns aiming to assist in the promotion of social well-being. Experiments carried out under realistic settings validate the NSense performance in terms of its capability to infer social interaction context based on our proposed computational utility functions. Traces obtained during the experiments are available via the CRAWDAD international trace repository.