Towards indoor localization and navigation independent of sensor based technologies

Many sensor based technologies exist to assist localization and navigation tasks in indoor space. Their success is hindered by limitations in their technology, accuracy and cost. This research provides an approach for localization and navigation based on the topological property of connectivity between spatial entities combined with qualitative information gathered from the user. In the research, a model and an algorithm is developed for localization and navigation in indoor space. It provides the user with the information necessary to express their unique location qualitatively using properties of spatial entities. The spatial entities and the accessibility property between them are stored in a graph-based data structure. The user's location and navigation path are derived using spatial queries that combine qualitative user input with the stored properties. Localization is provided only when the user provides input and is, therefore, an alternative solution to when sensor based technologies are limited or costly. A proof of concept application is implemented using the algorithm for a selected floor plan of a shopping mall.