Demo Abstract: Infrastructure-Free Smartphone Indoor Localization Using Room Acoustic Responses

Wenjie Luo, Dongfang Guo, Chaojie Gu, Yuting Wu, Qun Song, Zhenyu Yan, Rui Tan
November, 2021
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Sytem overview

Abstract

Smartphone indoor location awareness is increasingly demanded by a variety of mobile applications. The existing solutions for accurate smartphone indoor localization rely on additional devices or pre-installed infrastructure (e.g., dense WiFi access points, Bluetooth beacons). In this demo, we present EchoLoc, an infrastructure-free smartphone indoor localization system using room acoustic response to a chirp emitted by the phone. EchoLoc consists of a mobile client for echo data collection and a cloud server hosting a deep neural network for location inference. EchoLoc achieves 95% accuracy in recognizing 101 locations in a large public indoor space and a median localization error of 0.5m in a typical lab area.

Publication
In The 19th ACM Conference on Embedded Networked Sensor Systems (SenSys), November 15-17, 2021, Coimbra, Portugal
Demo
Wenjie Luo
Wenjie Luo
Ph.D

My research interests lie in improving the performance/efficiency of artificial intelligence (AI) powered Internet of things (IoT) systems.