Abstract
Location information is one of the key enablers to context-aware systems and applications for mobile devices. However, most existing location sensing techniques do not work or will be significantly slowed down without infrastructure support, which limits their applicability in several cases. In this paper, we propose a localization system that works for both indoor and outdoor environments in a completely offline manner. Our system leverages human users'perception of nearby textual signs, without using GPS, Wi-Fi, cellular, and Internet. It enables several important use cases, such as offline localization on wearable devices. Based on real data collected from Google Street View and OpenStreetMap, we examine the feasibility of our approach. The preliminary result was encouraging. Our system was able to achieve higher than 90% accuracy with only 4 iterations even when the speech recognition accuracy is 70%, requiring very small storage space, and consuming 44% less instantaneous power compared to GPS.
Original language | English (US) |
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Title of host publication | HotMobile 2015 - 16th International Workshop on Mobile Computing Systems and Applications |
Publisher | Association for Computing Machinery |
Pages | 87-92 |
Number of pages | 6 |
ISBN (Electronic) | 9781450333917 |
DOIs | |
State | Published - Feb 12 2015 |
Externally published | Yes |
Event | 16th International Workshop on Mobile Computing Systems, HotMobile 2015 - Santa Fe, United States Duration: Feb 12 2015 → Feb 13 2015 |
Publication series
Name | HotMobile 2015 - 16th International Workshop on Mobile Computing Systems and Applications |
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Conference
Conference | 16th International Workshop on Mobile Computing Systems, HotMobile 2015 |
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Country/Territory | United States |
City | Santa Fe |
Period | 2/12/15 → 2/13/15 |
Bibliographical note
Publisher Copyright:Copyright © 2015 ACM.