The anatomy of a context-aware application
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
An Acoustic Identification Scheme for Location Systems
ICPS '04 Proceedings of the The IEEE/ACS International Conference on Pervasive Services
Fine-grained network time synchronization using reference broadcasts
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Acoustic Modems for Ubiquitous Computing
IEEE Pervasive Computing
Audio location: accurate low-cost location sensing
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Using sound source localization in a home environment
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
A hybrid positioning system for technology-independent location-aware computing
Software—Practice & Experience
On the feasibility of real-time phone-to-phone 3D localization
Proceedings of the 9th ACM Conference on Embedded Networked Sensor Systems
Nomatic: location by, for, and of crowds
LoCA'06 Proceedings of the Second international conference on Location- and Context-Awareness
SwordFight: enabling a new class of phone-to-phone action games on commodity phones
Proceedings of the 10th international conference on Mobile systems, applications, and services
Low cost crowd counting using audio tones
Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems
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Sound source localization will play a major role in the new location-aware applications envisioned in Ubiquitous Computing. We describe the design and performance of three architectures and corresponding protocols that use a variation of the Time-of-Flight method for localizing three different kinds of devices, namely 802.11-enabled PDAs, 3G cell phones, and PDAs without network connectivity. The quantitative assessment is based on the deployment made with 6 sensors in, a 20x9m room, sewing over 10,000 localization requests. Our experiments indicate that all architectures achieve localization within 70cm of the actual position 90% of the time. The accuracy is further improved to 40cm 90% of the time when geometric factors are taken into consideration. The effects of noise and obstructions are also analyzed. Within 1m localization error realistic noise degrades the accuracy by 6 to 10%. The presence of obstacles, such as humans and cement columns, has no observable effect on the performance.