The goal of the HealthDist app is to provide users with information that can reduce personal infection risk by several orders of magnitude, making it safer and less stressful for users while being on campus and interacting with others.
HealthDist app will utilize a highly accurate (meter precision) proximity detector to provide users with information about the distance of nearby individuals, as well as a radar detector to provide information about potential encounters with moving, even out of view, individuals in their vicinity (path/trajectory prediction).
HealthDist app will act as a potential viral reader, providing quantifying the potential inoculum exposure (PIE, number 15 minutes periods at six feet of a social encounter) assessment to the individual user. The app makes use of the data that it collects about time and distance during the day, and current epidemiological risk modeling to quantify viral risk both in real time and as a cumulative for the day on campus.
HealthDist will support effective contact tracing based on users’ movements (trajectories of high accuracy ~1m), which are stored and encrypted on each individual user’s smartphone and are backed-up on their computers along with their other confidential information.
Indoor localization of high accuracy is achieved by combining fingerprinting and Bluetooth Low Energy (BLE) beacon signals.
Individual positions are periodically reported to and not stored on the secure server, which carries out the proximity stateless detection
Reporting density to an individual device or to a bulletin board works in similar fashion as in proximity detection with the addition of providing the id or the bounding box of the shared space area.
Requesting access to common space area and reserving a timeslot by an individual submits a request to the secure server by providing the id or the bounding box of the shared space area.
In this participatory service, individuals may choose to upload their positions and movements, encrypted and anonymized using the keys generated by the smartphones, periodically to the trusted server while they are in a building and in common spaces.
It uses the collected data of time and distance during the day to calculate the PVL, which is the integral of distance to others, time and activity, and state of Personal Protective Equipment (PPE) in predicted viral exposure of all others that were infected.
The contact tracing service has two detection modes: i) direct detection, and ii) indirect detection.