Highly mobile people (HMPs) require flexible, reactive service delivery due to their regularly changing location and activities and the lack of a wired network connection. A mobile service delivery system should be able to detect relevant events that occur such as change of location, availability of new last-minute specials, sales opportunities and safety issues and then reactively take action in response to these events. This work describes a situation management ontology based framework for delivering such a system. Issues addressed include HMP and service states and events, context, situations and situation-action rules, and syntactically and semantically compatible XML ontologies for their specification. A generic situation management ontology is developed in OWL using the ontology development tool, Protégé. This ontology is combined with domain specific classes in the travel domain to create a travel situation management ontology that can be used as the basis for a ubiquitous mobile travel service application. Using a typical independent traveller scenario, the travel situation management ontology is instantiated to demonstrate its effectiveness. The flexibility of the generic situation management ontology is demonstrated by creating an academic situation management ontology by simply replacing a small number of domain specific classes. A framework is also proposed that is based on the situation management ontology, distributed, co-operating software agents, and context based filtering, and is suitable for mobile service delivery. The example framework uses the situation management ontologies developed in this work and action rules to link situation specification to situation detection and action. The ontologies and action rules are semantically consistent and are specified in the XML based, industry standard language, OWL, thus drawing together previous independent work in a number of diverse disciplines.
| Identifer | oai:union.ndltd.org:ADTP/289591 |
| Creators | O'Brien, Paul Francis |
| Source Sets | Australiasian Digital Theses Program |
| Detected Language | English |
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