Modeling Pervasive Context-Aware Museum Guide Service (PCMGS)
No Thumbnail Available
Date
2009-12
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Addis Ababa University
Abstract
Enhancement of hardware technology with advancement in application of pervasive
computing shapes mobile users to seek devices on their disposal which may accomplish
their day-to-day activities. Pervasive environments are dedicated to serve their users
through embedded and/or independent physical devices. These environments have
knowledgebase to learn from. By incorporating the incoming user and environment
context with the stored knowledgebase, they prepare services on behalf of their users.
The number of users of such environments is different with respect to the area of
application where the pervasive system gets deployed. If there is more than one user in
the environment, interest of each as of their personal profile should be considered.
Among the promising application domains of pervasive computing, tourism is the one
that is functional with multi-users (large number of tourists to be served at a time).
Having little or no information about the area they are visiting, tourists are potential
beneficiaries of pervasive guide systems. To this end, this paper reports our research
effort that models a pervasive context-aware museum guide service along with its
implementation detail. Our model discovers visitor preferences or prepares list of selected
heritages from the museum customized as to visitor’s profile, analyzes each preference or
proposed heritage to assure if it is liked by the visitor or not, and then monitors
associating guide service with the analyzed heritages. The research theme of our model
grounds on visitor satisfaction and design of expressive museum environment which are
directly related with quality of guide service.
Keywords: Pervasive Computing, Context-awareness, Museum Guide Service,
Preference Discovery, Preference Analysis, Quality of Guide Service.
Description
Keywords
Pervasive Computing; Context-Awareness; Museum Guide Service; Preference Discovery; Preference Analysis; Quality of Guide Service