A pervasive computing approach to mixed granularity indoor wayfinding

Mystification and discovery are key components in the enjoyment and human experience of wayfinding and fundamental to its success. This thesis extrapolates this theory by applying it to indoor wayfinding, using a mixed granularity wayfinding solution within a pervasive computing context. To exemplify this a smartphone application was deployed with a mixed granularity mapping interface which allows users to view a floor map of a building containing navigation nodes and pathways as well as the coarsely granular location of points of interest with which users can explore the environment. Users may also access finely granular wayfinding information by scanning QR codes placed within the environment to pinpoint their location. The smartphone application was deployed among first year undergraduate students in the University of Limerick over a two year time period. Presented by this thesis is a mixed method quantitative deductive and inductive approach which employs a grounded theory strategy in answer to the research question. This mixed method approach consists of three experiments (one of which is the smartphone application), two deductive and one inductive combined with an inductive data analysis phase. Four research objectives overlap these experiments as a part of the research approach. The results are presented and show that a pervasive computing approach to mixed granularity indoor wayfinding can be successfully exemplified.