The use of mobile navigation aids, such as in-car devices and smart phone applications are fast becoming truly ubiquitous, and come with considerable benefits to the user. However, with this increase in ubiquity, consideration also needs to be given to the effects of their use, both during navigation itself, and longer-term. While the support of a mobile device allows the user to navigate to and within unfamiliar environments, research has also shown that their use can affect engagement with the task and environment during navigation. Users can become device-focussed and passive during the task, causing them to develop a reduced understanding of their environment and poorer subsequent memory for it. Maintaining engagement with task and environment during navigation is central in the development of appropriate user-device relationships. While previous work has investigated ways to encourage engagement during navigation, generally they have failed to account for differences in the way individuals approach the navigation task, despite the extent to which they may mediate differences in the relationship between device use and task and environment engagement. This research therefore investigates how users differ when navigating with mobile devices, and the impact these differences have on environmental and task engagement. To answer this question, the research perspective places navigation as an embodied, situated activity; to understand the user, consideration must also be given to their interaction with both device and environment. This thesis adopted a mixed methodological approach, combining interviews, real-world studies and a questionnaire to gain a rich, multifaceted understanding of how individuals navigate with their mobile devices. An initial set of exploratory interviews, conducted with 18 participants, identified a number of key user and device factors which were central in shaping task and environmental engagement outcomes. These factors were taken forward for investigation in a real -world pedestrian navigation experiment with 24 users of mobile navigation technology, which aimed to determine the influences of navigation support, and user self-efficacy and trust on levels of environmental engagement and learning.

Advances in positioning, imaging, location-based services capabilities and broadband connectivity enable public participation in environmental monitoring and decision making in a manner previously mostly possible for professional scientists. Data collected by volunteers, Volunteered Geographic Information (VGI), has long been an important factor in environmental programmes, but the difficulties in applying quality control measures has limited their scientific value. This thesis addresses this challenge. It defines and develops a surveying architecture, allowing efficient in-field data collection from a Global Positioning System (c ps) enabled ubiquitous devices. The originality of this architecture comes from a real-time analysis of surveyed responses in order to drive the survey for optimised precision and validity. Spatial awareness of the surveying engine allows the system to monitor and accommodate the sets of questions for each surveyor as the survey progresses. As a result this architecture is able to support the implementation of a dynamic and directed approach to in-field data collection with real-time quality control driven by an adaptive survey modelling technique ensuring improved data collection and personalised feedback to users. Various post-processing methods are proposed for further statistical analysis of collected data. The research defines this conceptual architecture and a technical solution for its implementation based on HTMLS, independent of the mobile hardware producer, tablets, smart phones, netbooks, laptops, in order to allow the widest public participation opportunity possible. The thesis proposes future research topics related to automatic recruitment of volunteers in the surveying areas, automatic supportive knowledge base identification, for example Twitter or RSS feeds, plus more precise and faster post-survey analysis tools. The open-source architecture gives the possibility to extend current knowledge base, allowing the adaptive surveying engine to use multilevel multi-sourced sets of information. The implementation was tested thoroughly on Google Android and Apple iPhone devices with a use case coming from the Tranquillity Report of the Campaign to Protect Rural England (CPRE) 2006.

Multipath is the main error source in short- to medium-baseline GNSS (Global Navigation Satellite System) relative positioning. So, in order to achieve the highest possible accuracy, multipath errors must be modelled and/or mitigated. A new era in GNSS positioning is on the horizon. GPS modernisation is being undertaken, which will provide an unencrypted civil signal (L2C) on the L2 frequency and the signal power of the L2 signal will be increased. Also an additional signal, the so-called L5, will be available on GPS Block IIF satellites scheduled for launch beginning in mid- 2006. Furthermore, the European GNSS, named Galileo, is being developed to provide four carrier frequencies and its Full Operational Capability (FOC) is scheduled to be in 2008, but more likely in 2010. This study identifies and models the factors causing phase multipath errors and investigates some possible phase multipath mitigation techniques using the multiple frequency data that modernised GPS and Galileo will offer. A GNSS data simulator has been developed to generate multipath contaminated data using a phase multipath model based on ray tracing. All known geometrical and physical factors have been taken into account and are described in detail. The model has been validated with real data collected in two experiments with reflectors of different materials. A GNSS data processor has been developed for this validation and for subsequent analyses. The results show good agreement (i.e. similar amplitude and frequency) with real multipath from a steel panel (planar reflector) and fairly good agreement (i.e. similar amplitude with slight different frequency) with real multipath from a lake (dynamic irregular reflector). They show that the multipath model has the potential to correct phase multipath errors in cases where the exact geometry of the reflection process and the nature of the reflector are known. Some of the characteristics of phase multipath and the sensitivities of simulated GNSS measurements to the factors causing multipath are investigated and described. Multipath mitigation through averaging based on the least squares process and standard outlier detection technique using multiple frequency GPS, Galileo, and integrated GPS and Galileo data have been investigated. Since multiple frequency GPS and Galileo data are not yet available, all data has been generated by the GNSS data simulator described in the foregoing. It was found that standard outlier detection techniques were not sufficiently robust to tackle the frequency-dependent multipath errors because they could not handle the worst case scenario when multiple frequency multipath errors from a particular satellite were all in-phase. Therefore a cocktail multiple outlier detection algorithm has been proposed and tested. Results show that a combination of more satellites, more frequencies and the cocktail multiple outlier algorithm can substantially mitigate multipath errors and so improve positioning accuracy.

Tourism destinations face various challenges in the implementation of mtechnologies and although mobile applications are used by some destinations, many are in their early stages of development. Few destinations have yet managed to develop credible mobile services. In particular, small and mediumsized enterprises (SMEs), which are the backbone of the tourism industry, have struggled to embrace new technologies, e.g. e-commerce applications, which has prevented them from benefiting from new technologies. It is unclear which business model will emerge to make mobile services viable. This study aims to explore the way that tourism destinations deal with these issues and will develop a mobile information model integrated with a mobile destination coding system to help tourism stakeholders optimise their exploitation of mtechnologies. This research comprised two phases. Phase one aimed to explore organizations that had implemented m-technologies. It employed a case study methodology utilising a variety of methods (semi-structured interviews, observation and document analysis). Phase two aimed to design a destination mobile information coding system. To achieve this paper prototyping interviews with m-technology and tourism experts were used. Phase one involved two case studies: Innsbruck as a case study for a tourism destination that had already implemented many m-technology applications for visitors; Cardiff Bus and Traveline as organizations that had implemented mtechnologies. Cross-case analysis informed the development of a model for tourism destination stakeholders, particularly SMEs, to encourage better mtechnology practices in tourism destination marketing. It concludes with a model for mobile information provision for tourism destination. The major contribution of this research is Tourism Mobile Information Coding System (TMICS) - a mobile coding information system which aims to provide tourists with destination information through their mobile phones. It is anticipated that the new system will enhance tourism destination stakeholders marketing efforts.

No description available.

No description available.

No description available.

No description available.

No description available.

No description available.