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Tracking requirements for augmented reality
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WLAN Location Determination via Clustering and Probability Distributions
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Error characteristics and calibration-free techniques for wireless LAN-based location estimation
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The Horus WLAN location determination system
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Sub-area localization: a simple calibration free approach
Proceedings of the 13th ACM international conference on Modeling, analysis, and simulation of wireless and mobile systems
FM radio for indoor localization with spontaneous recalibration
Pervasive and Mobile Computing
Managing workplace resources in office environments through ephemeral social networks
UIC'10 Proceedings of the 7th international conference on Ubiquitous intelligence and computing
Dynamic channel model LMS updating for RSS-based localization
HAIS'11 Proceedings of the 6th international conference on Hybrid artificial intelligent systems - Volume Part II
Social linking and physical proximity in a mobile location-based service
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Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies
Autonomous WLAN sensors for ad hoc indoor localization
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part II
Linking people through physical proximity in a conference
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ACM Transactions on Intelligent Systems and Technology (TIST) - Special Sections on Paraphrasing; Intelligent Systems for Socially Aware Computing; Social Computing, Behavioral-Cultural Modeling, and Prediction
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In this work we present a calibration-free system for locating wireless local area network devices, based on the radio frequency characteristics of such networks. Calibration procedures are applied in a great number of proposed location techniques and are considered to be not practical or a considerable barrier to wider adoption of such methods. Thus, we addressed issues related to some aspects of location systems through, an architecture based on wireless sniffers and by constructing a location model based on signal propagation models, in which its parameters are calculated in real time. This guarantee good self-sufficiency and adaptation capacity to the proposed system, once it does not need human intervention to work, neither from the network administrator or the wireless user being located. Moreover, a probabilistic method was used for estimating wireless devices positions, based on the previous constructed model. We later demonstrate the feasibility of our approach by reporting results of field tests in which the proposed technique was implemented and validated in a real-world indoor environment.