Smart Contact Tracing: Research Impact & Media Coverage

Our Smart Contact Tracing collaboration at the University of Guelph connected Bluetooth Low Energy (BLE), machine learning, and privacy-preserving design to a practical challenge during the COVID-19 pandemic: detecting close contacts with everyday smartphones and wearables.

Research Contribution

The research investigated how device placement and changing wireless conditions affect proximity estimates. The smartphone work used learned signal patterns to improve contact detection when phones were carried in pockets or bags; the wearable work studied proximity and interaction duration using BLE smartwatches.

In its 2020 project report, the University of Guelph described accuracy increasing from approximately 56% to 87% in the tested hidden-phone scenarios. This illustrates the practical value of accounting for how people carry devices when designing mobile sensing systems.

The work received NSERC Alliance COVID-19 support and led to papers on smartphone contact tracing, wearable exposure tracking, and the use of personal devices for contact tracing.

Public Visibility & Research Impact

The project reached readers through specialist technology reporting, university research news, and an alumni-magazine archive. These channels brought sensing accuracy and privacy into public discussions of pandemic-response tools, while identifying the researchers behind the work.

• MobileSyrup — University of Guelph’s contact tracing app uses machine learning to boost accuracy (20 June 2020). The technology-news report explains the smartphone approach and names Pai Chet Ng as the lead author, giving the work visibility beyond academic publication.
• University of Guelph News — U of G Contact Tracing App Could Help Improve Accuracy of the Technology (June 2020). The university report connects the prototype to privacy, improved sensing in hidden-phone scenarios, and grant-supported collaboration.
• Portico Magazine — Fall 2020 issue. The university alumni-magazine archive preserves the issue linked in the original project blog, extending the record of the project’s public exposure.
• University of Guelph Research & Innovation — New Smartwatch for Contact Tracing (2 February 2022). This later feature describes the wearable prototype, anonymous BLE signatures, and the importance of proximity and contact duration. It names Pai Chet Ng as a member of the research team.

Related Research

• COVID-19 and Your Smartphone: BLE-Based Smart Contact Tracing — IEEE Systems Journal, 2021.
• Personal Devices for Contact Tracing: Smartphones and Wearables to Fight Covid-19 — IEEE Communications Magazine, 2021.
• Epidemic Exposure Tracking With Wearables: A Machine Learning Approach to Contact Tracing — IEEE Access, 2022.