Proceedings ArticleDOI
SurroundSense: mobile phone localization via ambience fingerprinting
Martin Azizyan,Ionut Constandache,Romit Roy Choudhury +2 more
- pp 261-272
TLDR
It is argued that the increasing number of sensors on mobile phones presents new opportunities for logical localization, and proposed SurroundSense, a mobile phone based system that explores logical localization via ambience fingerprinting, can achieve an average accuracy of 87% when all sensing modalities are employed.Abstract:
A growing number of mobile computing applications are centered around the user's location. The notion of location is broad, ranging from physical coordinates (latitude/longitude) to logical labels (like Starbucks, McDonalds). While extensive research has been performed in physical localization, there have been few attempts in recognizing logical locations. This paper argues that the increasing number of sensors on mobile phones presents new opportunities for logical localization. We postulate that ambient sound, light, and color in a place convey a photo-acoustic signature that can be sensed by the phone's camera and microphone. In-built accelerometers in some phones may also be useful in inferring broad classes of user-motion, often dictated by the nature of the place. By combining these optical, acoustic, and motion attributes, it may be feasible to construct an identifiable fingerprint for logical localization. Hence, users in adjacent stores can be separated logically, even when their physical positions are extremely close. We propose SurroundSense, a mobile phone based system that explores logical localization via ambience fingerprinting. Evaluation results from 51 different stores show that SurroundSense can achieve an average accuracy of 87% when all sensing modalities are employed. We believe this is an encouraging result, opening new possibilities in indoor localization.read more
Citations
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Journal ArticleDOI
A survey of mobile phone sensing
Nicholas D. Lane,Emiliano Miluzzo,Hong Lu,Daniel Peebles,Tanzeem Choudhury,Andrew T. Campbell +5 more
TL;DR: This article surveys existing mobile phone sensing algorithms, applications, and systems, and discusses the emerging sensing paradigms, and formulates an architectural framework for discussing a number of the open issues and challenges emerging in the new area ofMobile phone sensing research.
Proceedings ArticleDOI
SpotFi: Decimeter Level Localization Using WiFi
TL;DR: SpotFi only uses information that is already exposed by WiFi chips and does not require any hardware or firmware changes, yet achieves the same accuracy as state-of-the-art localization systems.
Proceedings ArticleDOI
Zee: zero-effort crowdsourcing for indoor localization
TL;DR: Zee is presented -- a system that makes the calibration zero-effort, by enabling training data to be crowdsourced without any explicit effort on the part of users.
Journal ArticleDOI
Wi-Fi Fingerprint-Based Indoor Positioning: Recent Advances and Comparisons
Suining He,S.-H. Gary Chan +1 more
TL;DR: This survey overviews recent advances on two major areas of Wi-Fi fingerprint localization: advanced localization techniques and efficient system deployment.
Patent
Intuitive computing methods and systems
TL;DR: A smart phone senses audio, imagery, and/or other stimulus from a user's environment, and acts autonomously to fulfill inferred or anticipated user desires as discussed by the authors, and can apply more or less resources to an image processing task depending on how successfully the task is proceeding or based on the user's apparent interest in the task.
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