AECT: Accurate Energy Efficient Contact Tracing Using Smart Phones for Infectious Disease Detection

Abstract

Contact tracing is an important technique to reduce the impact of infectious diseases in smart cities. Smart phones equipped proximity sensors can be used to enable contact tracing, however accuracy of detection and energy efficiency is a key challenge. To address this challenge, we propose an accurate energy-efficient contact tracing (AECT) algorithm that detects which users came in contact with an infected user by performing computations at the server-side. Additionally, the AECT algorithm uses the wireless scan method, which calculates proximity based on pseudo-range multilateration and makes relevant comparisons with the matching score (MS) method based on the computation of received signal strength indication (RSSI) metric. Simulation results demonstrate that the scan method (AECT) is highly accurate and outperforms the scan method, highlighting that real distance is a better metric in contact tracing than a proxy for distance such as RSSI. Lastly, simulation results also demonstrate that the scan method (AECT) is 16 times more energy-efficient than the baseline 1 Hz frequency method, and we recommend it as a method of choice for performing contact tracing against infectious diseases such as COVID-19.