# A context-aware e-bike system to reduce pollution inhalation while   cycling

**Authors:** Shaun Sweeney, Rodrigo Ordonez-Hurtado, Francesco Pilla, Giovanni, Russo, David Timoney, Robert Shorten

arXiv: 1706.00646 · 2018-04-25

## TL;DR

This paper introduces a novel cyber-physical e-bike system that reduces pollution inhalation for cyclists by controlling their breathing rate, demonstrated through real device results.

## Contribution

It presents a new context-aware e-bike system that actively mitigates pollution exposure by adjusting cyclist breathing, a novel approach in urban pollution management.

## Key findings

- System effectively reduces pollution inhalation in real-world tests
- Demonstrates feasibility of controlling breathing rate via e-bike actuation
- Provides a practical solution for cyclist health protection in polluted cities

## Abstract

The effect of transport-related pollution on human health is fast becoming recognised as a major issue in cities worldwide. Cyclists, in particular, face great risks, as they typically are most exposed to tail-pipe emissions. Three avenues are being explored worldwide in the fight against urban pollution: (i) outright bans on polluting vehicles and embracing zero tailpipe emission vehicles; (ii) measuring air-quality as a means to better informing citizens of zones of higher pollution; and (iii) developing smart mobility devices that seek to minimize the effect of polluting devices on citizens as they transport goods and individuals in our cities. Following this latter direction, in this paper we present a new way to protect cyclists from the effect of urban pollution. Namely, by exploiting the actuation possibilities afforded by pedelecs or e-bikes (electric bikes), we design a cyber-physical system that mitigates the effect of urban pollution by indirectly controlling the breathing rate of cyclists in polluted areas. Results from a real device are presented to illustrate the efficacy of our system.

## Full text

_Full body text omitted from this summary view._ Fetch the complete paper as Markdown: https://tomesphere.com/paper/1706.00646/full.md

## Figures

14 figures with captions in the complete paper: https://tomesphere.com/paper/1706.00646/full.md

## References

24 references — full list in the complete paper: https://tomesphere.com/paper/1706.00646/full.md

---
Source: https://tomesphere.com/paper/1706.00646