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A Context, Location and Preference-Aware System for Safe Pedestrian Mobility

The COVID-19 pandemic poses new challenges in providing safe pedestrian navigation information that helps to reduce the risk of severe illness due to the highly contagious nature of the virus. In this paper, we present an innovative system, dubbed HealthDist, which utilizes the context (e.g., weather conditions), location (e.g., crowded areas) and user’s preferences to support safe mobility. It consists of four modules that allow efficient contact tracing, social distancing, and isolation. HealthDist’s modular design reduces the time and resources needed to provide accurate localization for measuring density in common spaces and measuring potential infection exposure, and recommend outdoor and indoor paths satisfying the user’s preferences. HealthDist’s initial deployment within a university campus demonstrated its capability to provide real time navigation information that reduces the COVID-19 exposure risk while at the same time satisfying the constraints defined by the user.