Mind The Gap: Real-time Decentralized Distance Estimation using Ultrasound and Bluetooth across Multiple Smartphones
Devansh R. Agrawal (1), Peter Lyon (2), Martin Frobisher (3), Andy, Doherty (3), Ben Allen (3), Freddie Rawlins (1) ((1) Hack Partners, (2) Yak, Consultancy, (3) NetworkRail)

TL;DR
This paper presents a real-time, decentralized method for estimating distances between smartphones using ultrasound and Bluetooth, achieving high accuracy without extra hardware or calibration, suitable for social distancing.
Contribution
First implementation of a hardware-agnostic, real-time decentralized distance estimation system using ultrasound and Bluetooth across multiple smartphones.
Findings
Median absolute error of 8.5 cm in distance measurement
Operates in real-time without internet or calibration
Validated on over 20 phone models with 25,000 users
Abstract
Robust, low-cost solutions are needed to maintain social distancing guidelines during the COVID-19 pandemic. We establish a method to measure the distance between multiple phones across a large number of closely spaced smartphones with a median absolute error of 8.5~cm. The application works in real-time, using Time of Flight of near-ultrasound signals, providing alerts with sufficient responsiveness to be useful for distancing while devices are in users pockets and they are moving at walking speed. The approach is decentralized, requires no additional hardware, and can operate in the background without an internet connection. We have no device-specific requirements nor need any manual calibration or device synchronization. It has been tested with over 20 different phones models, from both the Android and iOS systems in the past 5 years. To the best of our knowledge, this is the first…
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Taxonomy
TopicsIndoor and Outdoor Localization Technologies · Context-Aware Activity Recognition Systems · Bluetooth and Wireless Communication Technologies
