Scalable positioning of commodity mobile devices using audio signals

The positioning should happen in a scalable manner without requiring specialized hardware and

without requiring specialized infrastructure (except basic Wi-Fi or cellular access). At events

like meetings, talks, or conferences, a position map can aid spontaneous communication among

users based on their relative position in two ways. First, it enables users to choose message

recipients based on their relative position, which also enables the position-based distribution of

documents. Second, it enables senders to attach their position to messages, which can facilitate

interaction between speaker and audience in a lecture hall and enables the collection of feedback

based on users’ location.

In this thesis, we present Sonoloc, a mobile app and system that, by relying on acoustic

signals, allows a set of commodity smart devices to determine their relative positions. Sonoloc

can position any number of devices within acoustic range with a constant number of acoustic

signals emitted by a subset of devices. Our experimental evaluation with up to 115 devices in

real rooms shows that – despite substantial background noise – the system can locate devices

with an accuracy of tens of centimeters using no more than 15 acoustic signals.