A Probabilistic Room Location Service for Wireless Networked Environments

By Paul C. Castro, Patrick Chiu, Ted Kremenek, Richard R. Muntz. Ubiquitous Computing, 2001

584 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/7acb05f68ec2b517dfe0ad782b3d59b1e43a0896

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In Computer Networks and Communications

In Computer Vision and Pattern Recognition

In Electrical and Electronic Engineering

Citations in the corpus

Robotics-Based Location Sensing Using Wireless Ethernet (2002, background): “Nibble [ 5 ] is a system that uses a Bayesian network to estimate a device’s location.”
MoteTrack: a robust, decentralized approach to RF-based location tracking (2005, background): “This design allows the system to function despite significant failures of the radio beacon infrastructure.”
A survey of context modelling and reasoning techniques (2010, methodology): “use Bayesian networks for sensor fusion [59], in particular considering location information.”
A Survey of Augmented Reality Technologies, Applications and Limitations (2010, methodology): “Several techniques are researched by Bahl and Padmanabhan [21], Castro et al. [41] and vendors like InnerWireless 11 , AeroScout 12 and Ekahau 13 offer integrated systems for personnel and equipment tracking in for instance hospitals.”
Pedestrian localisation for indoor environments (2008, background): “describe map-building as “tedious” [34].”
The Cricket indoor location system (2005, methodology): “Several indoor location systems use this technique to determine a mobile node’s position based on the RF signal strength of access points [6, 15, 56, 41, 79, 109].”
Modeling of indoor positioning systems based on location fingerprinting (2004, methodology): “Recent developments have been emphasizing the algorithms used for estimating the location (that associate the fingerprints with the location coordinates) [1], [5].”
Enhancing Location Privacy in Wireless LAN Through Disposable Interface Identifiers: A Quantitative Analysis (2003, background): “…digital Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for pro.t or commercial advantage and that copies bear this notice and the full citation on the .rst page.”
Survey of Wireless Indoor Positioning Techniques and Systems (2007, methodology): “Nibble [40], one of the first systems of this generation, used a probabilistic approach (based on Bayesian network) to estimate a device’s location.”
A Statistical Modeling Approach to Location Estimation (2002, methodology): “There are several empirical methods for location estimation, such as RADAR [2], Nibble [ 8 ], RadioCamera [15], and the ones developed in the robotics community (see [28] and the references therein).”
Localization Algorithms and Strategies for Wireless Sensor Networks: Monitoring and Surveillance Techniques for Target Tracking (2009, methodology): “The Nibble system improves up on RADAR by taking the probabilistic nature of the problem into account (Castro et al. 2001).”
Modeling Context Information in Pervasive Computing Systems (2002, background): “The need to address the varying quality of context information has been widely recognized [14,15,12,11,7], yet none of the existing work addresses the problem in an adequate or general way.”