Modelling spatio-temporal relevancy in urban context-aware pervasive systems using voronoi continuous range query and multi-interval algebra

  • Authors:

  • Najmeh Neysani Samany;Mahmoud Reza Delavar;Nicholas Chrisman;Mohammad Reza Malek

  • Affiliations:

  • Department of Surveying and Geomatics Engineering, College of Engineering, University of Tehran, Tehran, Iran;Center of Exellence in Geomatic Engineering in Disaster Management, Department of Serveying and Geomatic Engineering, College of Engineering, University of Tehran, Tehran, Iran;Department of Geomatic Science, Laval University, Québec, QC, Canada;Department of GIS, Faculty of Geodesy and Geomatic Engineering, K.N. Toosi University of Technology, Tehran, Iran

  • Venue:
  • Mobile Information Systems
  • Year:
  • 2013

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Abstract

Space and time are two dominant factors in context-aware pervasive systems which determine whether an entity is related to the moving user or not. This paper specifically addresses the use of spatio-temporal relations for detecting spatio-temporally relevant contexts to the user. The main contribution of this work is that the proposed model is sensitive to the velocity and direction of the user and applies customized Multi Interval Algebra MIA with Voronoi Continuous Range Query VCRQ to introduce spatio-temporally relevant contexts according to their arrangement in space. In this implementation the Spatio-Temporal Relevancy Model for Context-Aware Systems STRMCAS helps the tourist to find his/her preferred areas that are spatio-temporally relevant. The experimental results in a scenario of tourist navigation are evaluated with respect to the accuracy of the model, performance time and satisfaction of users in 30 iterations of the algorithm. The evaluation process demonstrated the efficiency of the model in real-world applications.