The active badge location system
ACM Transactions on Information Systems (TOIS)
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
A Probabilistic Room Location Service for Wireless Networked Environments
UbiComp '01 Proceedings of the 3rd international conference on Ubiquitous Computing
LANDMARC: indoor location sensing using active RFID
Wireless Networks - Special issue: Pervasive computing and communications
A Probabilistic Signal-Strength-Based Evaluation Methodology for Sensor Network Deployment
AINA '05 Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 1
Power-Efficient Access-Point Selection for Indoor Location Estimation
IEEE Transactions on Knowledge and Data Engineering
Bayesian Filtering for Location Estimation
IEEE Pervasive Computing
Deformed fuzzy automata for correcting imperfect strings of fuzzy symbols
IEEE Transactions on Fuzzy Systems
Proximity classification for mobile devices using wi-fi environment similarity
Proceedings of the first ACM international workshop on Mobile entity localization and tracking in GPS-less environments
WiFi localization system based on fuzzy logic to deal with signal variations
ETFA'09 Proceedings of the 14th IEEE international conference on Emerging technologies & factory automation
Localization of wireless sensor network using artificial neural network
ISCIT'09 Proceedings of the 9th international conference on Communications and information technologies
Clustering-based location in wireless networks
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
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This paper describes user location and tracking on indoor scenarios through a wireless network. We propose a fuzzy location algorithm, using fuzzy inference systems, in order to deal with imprecise location based on radio-frequency trilateration estimations, providing high location rates near to 90. This indoor positioning approach is based on the pattern recognition of IEEE 802.11 (WiFi) signal strength measurements using fuzzy logic to deal with the vagueness and uncertainty of the trilateration based on signal strength. User location and tracking are considered in order to provide complete intelligent location based services. Fuzzy location techniques allow increasing location ratios even when the user trilateration can not be as precise as desired. Fuzzy tracking is performed by means of a fuzzy automaton.