Scalable floor localization using barometer on smartphone

• Published in: Wireless communications and mobile computing Vol. 16; no. 16; pp. 2557 - 2571
• Main Authors: Ye, Haibo, Gu, Tao, Tao, Xianping, Lu, Jian
• Format: Journal Article
• Language: English
• Published: Oxford Hindawi Limited 01.11.2016
• Subjects: barometer; crowdsourcing; floor localization; mobile phone localization
• ISSN: 1530-8669; 1530-8677
• DOI: 10.1002/wcm.2706

Traditional fingerprint‐based localization techniques mainly rely on infrastructure support such as GSM and Wi‐Fi. They require war‐driving, which is both time‐consuming and labor‐intensive. With recent advances of smartphone sensors, sensor‐assisted localization techniques are emerging. However, they often need user‐specific training and more power intensive sensing, resulting in infeasible solutions for real deployment. In this paper, we present Barometer‐based floor Localization system (B‐Loc), a novel floor localization system to identify the floor level in a multi‐floor building on which a mobile user is located. It makes use of the barometer on smartphone. B‐Loc does not rely on any Wi‐Fi infrastructure and requires neither war‐driving nor prior knowledge of the buildings. Leveraging on crowdsourcing, B‐Loc builds the barometer fingerprint map, which contains the barometric pressure value for each floor level to locate users' floor levels. We conduct both simulation and field studies to demonstrate the accuracy, scalability, and robustness of B‐Loc. Our simulation shows that B‐Loc can locate the user fast and the field study in a 10‐floor building shows that B‐Loc achieves an accuracy of over 98%. Copyright © 2016 John Wiley & Sons, Ltd. In this paper, we present Barometer‐based floor Localization system (B‐Loc), a novel floor localization system to identify the floor level in a multi‐floor building on which a mobile user is located. It makes use of the barometer on smartphone. B‐Loc does not rely on any Wi‐Fi infrastructure and requires neither war‐driving nor prior knowledge of the buildings. Leveraging on crowdsourcing, B‐Loc builds the barometer fingerprint map, which contains the barometric pressure value for each floor level to locate users’ floor levels. The result from both simulation and field studies demonstrates the accuracy, scalability, and robustness of B‐Loc.