User-Centric Proximity Estimation Using Smartphone Radio Fingerprinting

Area of Science:

• Epidemiology
• Computer Science
• Mobile Computing

Background:

• Integrating infectious disease modeling with data collection is vital but challenging.
• Mathematical models require a strong empirical basis to fill data gaps.
• Personal wireless devices offer a way to connect empirical data with contact network modeling.

Purpose of the Study:

• To develop and evaluate user-centric proximity estimation using smartphone radio environment monitoring.
• To define and implement a proximity parameter based on recorded person-radio-environment traces.
• To bridge the gap between real-world human interactions and infectious disease modeling.

Main Methods:

• Development of a smartphone application and back-end services for data collection.
• Implementation of advanced user-centric proximity estimation techniques.
• Evaluation of proximity estimation accuracy in real-world scenarios.

Main Results:

• Demonstrated the feasibility of estimating device proximity (near, medium, far) using smartphone data.
• Achieved reasonable accuracy in proximity estimation in practical case studies.
• Validated the effectiveness of the developed person-radio-environment trace method.

Conclusions:

• Smartphone radio environment monitoring provides a viable method for empirical data collection in contact tracing.
• The developed proximity estimation approach can enhance infectious disease modeling by providing crucial contact data.
• User-centric data collection via personal wireless devices is a promising avenue for epidemiological research.