Sensor Aggregation and Integration in Healthcare Location Based Services

Complex and dynamic working environments such as health care facilities consist of staff, patients and equipment constantly moving in response to changing medical requirements. Knowing the current location of people and equipment is essential for the smooth running of a facility, yet creating a global view through tracking is a challenging task. It is clear that many common hospital situations can be improved with real-time access to the various actors' location information. One of the main problems with implementing such services is that current location based applications tend to be proprietary and the data generated closed. The realisation of ubiquitous location based services demands the exploration of hybrid models and methods that can utilise existing and subsequent infrastructures in novel and complimentary ways. We describe a number of hospital scenarios that use location-based services and make available all the location data gathered. We propose that by aggregating location data by a range of acquisition methods it is possible to improve the performance of location applications and readily adapt to the introduction of new location detection technologies

[1]  Gaetano Borriello,et al.  The location stack , 2004 .

[2]  Matthias Weitlaner,et al.  Ubiquitous Computing for Hospital Applications: RFID-Applications to Enable Research in Real-Life Environments , 2005, COMPSAC.

[3]  Aaron J. Quigley,et al.  Proximation: Location-Awareness Though Sensed Proximity and GSM Estimation , 2005, LoCA.

[4]  Aaron Quigley,et al.  RFID Enabled Awareness of Participant ’ s Context in eMeetings , 2006 .

[5]  Paddy Nixon,et al.  Hybridising events and knowledge as a basis for building autonomic systems , 2007 .

[6]  Li Liu,et al.  RFID Application in Hospitals: A Case Study on a Demonstration RFID Project in a Taiwan Hospital , 2006, Proceedings of the 39th Annual Hawaii International Conference on System Sciences (HICSS'06).

[7]  Bill N. Schilit,et al.  Place Lab: Device Positioning Using Radio Beacons in the Wild , 2005, Pervasive.

[8]  A. Quigley,et al.  BlueStar, a privacy centric location aware system , 2004, PLANS 2004. Position Location and Navigation Symposium (IEEE Cat. No.04CH37556).

[9]  Mark Sullivan,et al.  Sensor Fusion-Based Middleware for Assisted Living , 2006 .

[10]  Graeme Stevenson,et al.  ConStruct -- A Decentralised Context Infrastructure for Ubiquitous Computing Environments , 2005 .

[11]  Bobby Bodenheimer,et al.  The Process of Motion Capture: Dealing with the Data , 1997, Computer Animation and Simulation.

[12]  Andy Hopper,et al.  The active badge location system , 1992, TOIS.

[13]  Adrian K. Clear,et al.  Integrating Multiple Contexts and Ontologies in a Pervasive Computing Framework , 2006, C&O@ECAI.

[14]  Andy Hopper,et al.  A new location technique for the active office , 1997, IEEE Wirel. Commun..

[15]  Dieter Fox,et al.  Bayesian Filtering for Location Estimation , 2003, IEEE Pervasive Comput..

[16]  Hari Balakrishnan,et al.  Tracking moving devices with the cricket location system , 2004, MobiSys '04.