A new approach of modeling spatio-temporal relevancy in an urba n context-aware wayfinding system

Wayfinding is one of the important tasks of individuals in an urban traffic network. Guider geospatial information systems are the common services which helps people to navigate different unfamiliar routes with altered goals. The key challenge of these systems is the introduction of wayfinding information in a context aware manner. However، space، time and identity are the primary contexts and the other contexts are modeled based on these three elements. This article concentrated on modeling spatio-temporal relevancy of moving user based on his/her identity. The introduced model is able to cover all of the spatial relationships (topologic، metric and directional) on temporal dimension also to consider the characteristics of user and related contexts. In this way the proposed model utilizes Allen’s Multi- Interval Algebra (MIA) along with Dynamic Voronoi continuous Range Query (VCRQ) and introduces an innovative approach based on coarser calculus principals and customization methods. The model (MI 25) has been implemented as a software runnable on mobile systems and PDAs. The assessment of the implemented model is done regarding to three parameters including accuracy، time performance and users satisfaction. Tehran Districts 3، 6 and 11 are selected as case study area. In order to test the accuracy parameters، the designed software is run in three different routes with two different velocities and three time durations in 100 iterations. Then the accuracy of the detection of the related contexts is tested by means of a binomial distribution with one-sided 95% confidence level، precision and recall factors. The results of implementation and evolution based on accuracy، time performance and user satisfaction demonstrated the efficiency of the proposed model in an urban context-aware wayfinding systems.