Mobile WiFi Time-of-Arrival-based Localization using ESP32-S2

Contact tracing is an important prevention measure in containing infectious diseases and easing the rate of transmission. However, since traditional contact tracing methods can be labor-intensive and error-prone due to iterative processes and memory bias, there is a need to develop tools and systems that may be able to provide assistance. This study developed a mobile localization and orientation tracking system for digital contact tracing. The devices are lightweight enough to be handheld, while also able to collect relevant data, such as distance measurements, orientation, and date and time. From this, an estimated position and orientation in a given space is acquired through Bayesian grid update. The system was tested in a 12m x 3m segment of unobstructed hallway. In ideal scenarios, it may reach an accuracy of within 0.75m positional error with four responders; however, its average positional error is closer to 2-3m, with three responders. While the system may be viable for certain settings, further research and adjustment will be needed to make such a system usable in varied scenarios.