The active badge location system
ACM Transactions on Information Systems (TOIS)
The Cricket location-support system
MobiCom '00 Proceedings of the 6th annual international conference on Mobile computing and networking
Location-Based E-Campus Web Services: From Design to Deployment
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
An Open Architecture for Developing Mobile Location-Based Applications over the Internet
ISCC '01 Proceedings of the Sixth IEEE Symposium on Computers and Communications
A Friis-Based Calibrated Model for WiFi Terminals Positioning
WOWMOM '05 Proceedings of the Sixth IEEE International Symposium on World of Wireless Mobile and Multimedia Networks
On Building a Reflective Middleware Service for Location-Awareness
RTCSA '05 Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
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Location-based service is one of the most popular buzzwords in the field of U-city. Positioning a user is an essential ingredient of a location-based system on a U-city. For the outdoor positioning, GPS based practical solutions have been introduced. However, GPS measurement error is too big to be used for U-campus services because the size of a campus is relatively smaller than a city. We propose Relative-Interpolation Method in order to improve the correctness of outdoor positioning. Besides, indoor positioning is necessary for U-campus while GPS signal is not available inside buildings. For the indoor positioning, Cricket, Active Badge, and so on have been introduced. These methods require special equipments dedicated for positioning. Our method does not require such equipments because it determines the user's position based on the receiver signal strength indicators (RSSI) from access points (AP) which are already installed for WLAN. The algorithm we are using for indoor positioning is a kind of finger prints method. However our algorithm builds a decision treeinstead of a look-up table in the off-linephase. Therefore, our method is faster than existing indoor positioning methods in the real-timephase. We have integrated our indoor and outdoor positioning methods and implemented a prototype of our indoor-outdoor positioning method on a laptop. Our experimental results are discussed in this paper.