Multilayer feedforward networks are universal approximators
Neural Networks
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
Robotics-based location sensing using wireless ethernet
Proceedings of the 8th annual international conference on Mobile computing and networking
The smart floor: a mechanism for natural user identification and tracking
CHI '00 Extended Abstracts on Human Factors in Computing Systems
WLAN Location Determination via Clustering and Probability Distributions
PERCOM '03 Proceedings of the First IEEE International Conference on Pervasive Computing and Communications
Bayesian Based Location Estimation System Using Wireless LAN
PERCOMW '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications Workshops
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
Wireless Geolocation Systems and Services
IEEE Communications Magazine
Extended Kalman Filter for wireless LAN based indoor positioning
Decision Support Systems
Improvement of Kalman filters for WLAN based indoor tracking
Expert Systems with Applications: An International Journal
Kalman filter vs. particle filter in improving K-NN indoor positioning
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
Expert Systems with Applications: An International Journal
A Kalman filter updating method for the indoor moving object database
Expert Systems with Applications: An International Journal
Outdoor exit detection using combined techniques to increase GPS efficiency
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
Positioning a user is an essential ingredient of a location-based system. For the outdoor positioning, GPS is practically used. For the indoor positioning, Active Badge, BAT, Cricket, and so on have been introduced. These methods are very accurate but require special equipments dedicated for positioning. Instead of using special equipments, using existing equipments is more economical. For this reason, positioning methods of using existing wireless LAN access points have recently been introduced. Among the methods employed by them, the fingerprint methods are the most promising. Probabilistic method, K-NN (Nearest Neighbor), and Neural networks are the techniques used by the most location fingerprinting. We are proposing a new technique which is more efficient than these three. Our technique builds a decision tree during the off-line phase and determines a user's location referring to the tree. Time complexity analysis and experimental accuracy analysis of the proposed technique are presented in this paper.