Robotics-based location sensing using wireless ethernet
Proceedings of the 8th annual international conference on Mobile computing and networking
Practical robust localization over large-scale 802.11 wireless networks
Proceedings of the 10th annual international conference on Mobile computing and networking
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Towards smart surroundings: enabling techniques and technologies for localization
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
Efficient indoor proximity and separation detection for location fingerprinting
Proceedings of the 1st international conference on MOBILe Wireless MiddleWARE, Operating Systems, and Applications
Composcan: adaptive scanning for efficient concurrent communications and positioning with 802.11
Proceedings of the 6th international conference on Mobile systems, applications, and services
Brief encounters: Sensing, modeling and visualizing urban mobility and copresence networks
ACM Transactions on Computer-Human Interaction (TOCHI)
Zone-based rss reporting for location fingerprinting
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
A taxonomy for radio location fingerprinting
LoCA'07 Proceedings of the 3rd international conference on Location-and context-awareness
A calibration-free localization solution for handling signal strength variance
MELT'09 Proceedings of the 2nd international conference on Mobile entity localization and tracking in GPS-less environments
Indoor location fingerprinting with heterogeneous clients
Pervasive and Mobile Computing
Smartphone-based Wi-Fi tracking system exploiting the RSS peak to overcome the RSS variance problem
Pervasive and Mobile Computing
A Multisensor Architecture Providing Location-based Services for Smartphones
Mobile Networks and Applications
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In the area of pervasive computing a key concept is context-awareness. One type of context information is location information of wireless network clients. Research in indoor localization of wireless network clients based on signal strength is receiving a lot of attention. However, not much of this research is directed towards handling the issue of adapting a signal strength based indoor localization system to the hardware and software of a specific wireless network client, be it a tag, PDA or laptop. Therefore current indoor localization systems need to be manually adapted to work optimally with specific hardware and software. A second problem is that for a specific hardware there will be more than one driver available and they will have different properties when used for localization. Therefore the contribution of this paper is twofold. First, an automatic system for evaluating the fitness of a specific combination of hardware and software is proposed. Second, an automatic system for adapting an indoor localization system based on signal strength to the specific hardware and software of a wireless network client is proposed. The two contributions can then be used together to either classify a specific hardware and software as unusable for localization or to classify them as usable and then adapt them to the signal strength based indoor localization system.