Analysis of Bluetooth RSSI for Proximity Detection of Ship Passengers

Abstract

Concern about the health of people who traveled onboard was raised during the COVID-19 outbreak on the Diamond Princess cruise ship. The ship’s narrow space offers an environment conducive to the virus’s spread. Close contact isolation remains one of the most critical current measures to stop the virus’s rapid spread. Contacts can be identified efficiently by detecting intelligent devices nearby. The smartphone’s Bluetooth RSSI signal is essential data for proximity detection. This paper analyzes Bluetooth RSSI signals available to the public and compares RSSI signals in two distinct poses: standing and sitting. These features can improve accuracy and provide an essential basis for creating algorithms for proximity detection. This allows for improved accuracy in identifying close contacts and can help ships sustainably manage persons onboard in the post-epidemic era.