Tools
Tools
Johnson, T. 
ORCID: 0000-0002-1702-0943, Woodward, K. ORCID: 0000-0003-3302-1345 and Kanjo, E. ORCID: 0000-0002-1720-0661,
2024.
Emotion on the edge: air quality sensors decoded as a real-world emotion indicator.
In:
2024 IEEE International Conference on Pervasive Computing and Communications (PerCom).
Institute of Electrical and Electronics Engineers (IEEE), pp. 267-272.
ISBN 9798350304367
|
Text
1879559_Johnson.pdf - Post-print Download (12MB) | Preview |
Abstract
As the research community increasingly focuses on quantifying emotional states in real-world scenarios, there is a growing need for edge computing. In this work, we present a novel approach to on-device emotion classification through the development of a low-cost hand-held device. This device incorporates a range of environmental air quality factors, including Particulate Matter, Nitrogen Dioxide, Carbon Monoxide, Ammonia, and Noise. Our research addresses the current limitations in the field of emotional state measurement by leveraging environmental air quality data, which has been previously linked to affective states. This on-device approach not only offers an alternative to resource-intensive emotion recognition methods but also contributes to the development of more practical and affordable solutions for emotion assessment. The preliminary results of our device's performance in real-world scenarios suggest its effectiveness in quantifying emotional states through air quality factors, with the model achieving 95% accuracy demonstrating accurate on-device classification without the need for external high-processing power.
| Item Type: | Chapter in book | ||||||
|---|---|---|---|---|---|---|---|
| Description: | Paper presented at 22nd International Conference on Pervasive Computing and Communications (PerCom 2024), Biarritz, France, 11-15 March 2024. | ||||||
| Creators: | Johnson, T., Woodward, K. and Kanjo, E. | ||||||
| Publisher: | Institute of Electrical and Electronics Engineers (IEEE) | ||||||
| Date: | 23 April 2024 | ||||||
| ISBN: | 9798350304367 | ||||||
| Identifiers: |
|
||||||
| Divisions: | Schools > School of Science and Technology | ||||||
| Record created by: | Laura Ward | ||||||
| Date Added: | 03 Apr 2024 08:27 | ||||||
| Last Modified: | 30 Apr 2024 07:19 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/51185 |
Actions (login required)
 |
Edit View |
Views
Views per month over past year
Downloads
Downloads per month over past year
