Lorcan Coyle's Home on Tinterweb

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Complex and dynamic working environments such as healthcare 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.

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Location detection systems that use tags are a popular means of determining a user's location. These systems are characterised as requiring the user to carry an identity tag that is detected by sensors, which typically use some form of triangulation to determine location. Although estimates for precision for these systems are published by the respective manufacturers the customer experience can vary widely. This paper proposes an evaluation framework which will allow different systems to be compared more directly. This framework is specifically targeted at evaluating the experiences of tagging humans, which can cause particular difficulties due to the fact that many tag-based systems use communication frequencies that cannot pass easily through the human body.

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Location-aware systems provide customised services or applications according to users' locations. While much research has been carried out in developing models to represent location information and spatial relationships, it is usually limited to modelling simple environments (cf. [13,19,3]). This paper proposes a unified space model for more complex environments (e.g., city plan or forest). This space model provides a flexible, expressive, and powerful spatial representation. It also proposes a new data structure - an integrated lattice and graph model - to express comprehensive spatial relationships. This structure not only provides multiple graphs at different abstraction levels, but it also collapses the whole map into smaller local graphs. This mechanism is beneficial in reducing the complexity of creating and maintaining a map and improving the efficiency of path finding algorithms.

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