A Cooperative Localization Technique for Tracking in Hospitals and Nursing Homes

Nowadays numerous technologies such as WiFi, Bluetooth, cellular networks and magnetometer positioning are employed for tracking patients and assets in hospitals or nursing homes. Each of these techniques has advantages and drawbacks. For example, WiFi localization has relatively good accuracy but cannot be used in case of power outage or in the areas with poor WiFi coverage. Magnetometer positioning or cellular network does not have such problems but they are not as accurate as localization with WiFi. This paper describes technique that simultaneously employs different localization technologies for enhancing stability and average accuracy of localization. The proposed algorithm is based on fingerprinting method paired with data fusion and prediction algorithms for estimating the object location. Significant performance improvement was showed in practical scenarios.

[1]  Garik Markarian,et al.  Enhanced Positioning Techniques for Hybrid Wireless Networks , 2011 .

[2]  Y. Ebihara Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[3]  Henry Tirri,et al.  A Probabilistic Approach to WLAN User Location Estimation , 2002, Int. J. Wirel. Inf. Networks.

[4]  Mikkel Baun Kjærgaard,et al.  Error Estimation for Indoor 802.11 Location Fingerprinting , 2009, LoCA.

[5]  Denis Pomorski,et al.  GPS/IMU data fusion using multisensor Kalman filtering: introduction of contextual aspects , 2006, Inf. Fusion.

[6]  Ig-Jae Kim,et al.  Indoor location sensing using geo-magnetism , 2011, MobiSys '11.

[7]  Fernando Torres Medina,et al.  Hybrid tracking of human operators using IMU/UWB data fusion by a Kalman filter , 2008, 2008 3rd ACM/IEEE International Conference on Human-Robot Interaction (HRI).

[8]  Joel Barnes,et al.  Hybrid Method for Localization Using WLAN , 2005 .

[9]  Paramvir Bahl,et al.  RADAR: an in-building RF-based user location and tracking system , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).