The Kalman filter: an introduction to concepts
Autonomous robot vehicles
Adaptive stream resource management using Kalman Filters
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
A Survey of Outlier Detection Methodologies
Artificial Intelligence Review
Sensor-assisted wi-fi indoor location system for adapting to environmental dynamics
MSWiM '05 Proceedings of the 8th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Exploiting Environmental Properties for Wireless Localization and Location Aware Applications
PERCOM '08 Proceedings of the 2008 Sixth Annual IEEE International Conference on Pervasive Computing and Communications
EnTracked: energy-efficient robust position tracking for mobile devices
Proceedings of the 7th international conference on Mobile systems, applications, and services
Energy-accuracy trade-off for continuous mobile device location
Proceedings of the 8th international conference on Mobile systems, applications, and services
Improving energy efficiency of location sensing on smartphones
Proceedings of the 8th international conference on Mobile systems, applications, and services
Continuous tracking within and across camera streams
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Place lab: device positioning using radio beacons in the wild
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Energy efficient continuous location determination for pedestrian information systems
MobiDE '12 Proceedings of the Eleventh ACM International Workshop on Data Engineering for Wireless and Mobile Access
Improvements to the SMO algorithm for SVM regression
IEEE Transactions on Neural Networks
Delay-Tolerant positioning for location-based logging with mobile devices
UCAmI'12 Proceedings of the 6th international conference on Ubiquitous Computing and Ambient Intelligence
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Recent advances in GPS and WiFi-based positioning technologies for mobile phones have triggered many location-based services. However, GPS positioning quickly drains a phone's battery and cannot be used indoors. On the other hand, WiFi positioning provides energy-efficient indoor and outdoor positioning with reasonable accuracy. However, WiFi positioning sometimes makes large errors caused by various reasons, e.g., the movement of reference WiFi access points. In this paper we attempt to detect and correct such errors automatically by performing outlier detection in time series. So, we solve this problem by comparing a user's current measurement at time T with her coordinate point at time T predicted from her past coordinate history, and judging whether the current measurement is correct or not by computing the distance between the measurement location and the predicted location. However, it is difficult to predict the user's coordinates accurately with a single prediction method (predictor) because the user's context (e.g., migration speed and sparseness of past coordinates) greatly affects predictor performance. We thus design a context-aware error detection method by employing an ensemble of predictors that have different strengths and weaknesses.