{"id":{"repo_id":"hull","oai_identifier":"oai:hull-repository.worktribe.com:4209258"},"canonical_url":"https://search.dev.ndltd.org/etd/hull/oai:hull-repository.worktribe.com:4209258","repository":{"repo_id":"hull","name":"University of Hull","base_url":"https://hull-repository.worktribe.com/oaiprovider"},"display":{"title":"Hybrid framework for dynamic position determination in multisensor environments","abstract":"Information about a user's context is crucial in obtaining the goal of ubiquitous computing. This thesis introduces a new approach in for looking at a special case of context; location information. Making devices location-aware is the first step of providing context-based services. Existing technologies for position determination are ill suited in terms of interoperability and heterogeneity. Furthermore, they rely either on vast and often expensive infrastructures to perform the position estimation or alternatively the mobile device is burdened with the responsibility of localising itself. Both of the current approaches have their trade-offs. The basis of this work is to maximise the availability of positioning services allowing mobility between different environments and surroundings while minimising the vulnerabilities of existing approaches.The work presents a managed positioning environment for indoor and outdoor surroundings, in which accuracy and precision can be improved by using a mix of fixed sensors and the sensing capabilities of mobile devices in a way that it allows the transformation of proximity data into absolute coordinates. It is believed that this also improves the availability of the positioning service as partial, imprecise or incomplete data is utilised rather than discarded. The usage of wireless local area networks along with PDAs, mobile phones and similar devices, as opposed to custom sensors ensures that maintenance and administrative costs are kept to a minimum. Furthermore, a dynamic feedback system is proposed in order minimise deployment and initialisation effort by allowing refining of location information in fixed sensors.","abstract_html":"Information about a user's context is crucial in obtaining the goal of ubiquitous computing. This thesis introduces a new approach in for looking at a special case of context; location information. Making devices location-aware is the first step of providing context-based services. Existing technologies for position determination are ill suited in terms of interoperability and heterogeneity. Furthermore, they rely either on vast and often expensive infrastructures to perform the position estimation or alternatively the mobile device is burdened with the responsibility of localising itself. Both of the current approaches have their trade-offs. The basis of this work is to maximise the availability of positioning services allowing mobility between different environments and surroundings while minimising the vulnerabilities of existing approaches.The work presents a managed positioning environment for indoor and outdoor surroundings, in which accuracy and precision can be improved by using a mix of fixed sensors and the sensing capabilities of mobile devices in a way that it allows the transformation of proximity data into absolute coordinates. It is believed that this also improves the availability of the positioning service as partial, imprecise or incomplete data is utilised rather than discarded. The usage of wireless local area networks along with PDAs, mobile phones and similar devices, as opposed to custom sensors ensures that maintenance and administrative costs are kept to a minimum. 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This thesis introduces a new approach in for looking at a special case of context; location information. Making devices location-aware is the first step of providing context-based services. Existing technologies for position determination are ill suited in terms of interoperability and heterogeneity. Furthermore, they rely either on vast and often expensive infrastructures to perform the position estimation or alternatively the mobile device is burdened with the responsibility of localising itself. Both of the current approaches have their trade-offs. The basis of this work is to maximise the availability of positioning services allowing mobility between different environments and surroundings while minimising the vulnerabilities of existing approaches.The work presents a managed positioning environment for indoor and outdoor surroundings, in which accuracy and precision can be improved by using a mix of fixed sensors and the sensing capabilities of mobile devices in a way that it allows the transformation of proximity data into absolute coordinates. It is believed that this also improves the availability of the positioning service as partial, imprecise or incomplete data is utilised rather than discarded. The usage of wireless local area networks along with PDAs, mobile phones and similar devices, as opposed to custom sensors ensures that maintenance and administrative costs are kept to a minimum. Furthermore, a dynamic feedback system is proposed in order minimise deployment and initialisation effort by allowing refining of location information in fixed sensors."]},{"key":"dc:title","label":"Title","values":["Hybrid framework for dynamic position determination in multisensor environments"]}]}],"canonical_facts":{"dc:contributor.advisor":["Grey, David"],"dc:creator":["Liimatainen, Saana Pauliina"],"dc:date":["2009-05-01"],"dc:date.issued":["2009"],"dc:description.abstract":["Information about a user's context is crucial in obtaining the goal of ubiquitous computing. This thesis introduces a new approach in for looking at a special case of context; location information. Making devices location-aware is the first step of providing context-based services. Existing technologies for position determination are ill suited in terms of interoperability and heterogeneity. Furthermore, they rely either on vast and often expensive infrastructures to perform the position estimation or alternatively the mobile device is burdened with the responsibility of localising itself. Both of the current approaches have their trade-offs. The basis of this work is to maximise the availability of positioning services allowing mobility between different environments and surroundings while minimising the vulnerabilities of existing approaches.The work presents a managed positioning environment for indoor and outdoor surroundings, in which accuracy and precision can be improved by using a mix of fixed sensors and the sensing capabilities of mobile devices in a way that it allows the transformation of proximity data into absolute coordinates. It is believed that this also improves the availability of the positioning service as partial, imprecise or incomplete data is utilised rather than discarded. 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