The symbolic models of the world are inspired in human mental models of space as studied in psychology. In the scope of this research project, the focus was on a graph-based symbolic world model built upon four basic components: objects, object attributes, relations and relation attributes. Figure 1 shows an example of such a model.

Figure 1: An example of a symbolic world model

This model is meant to be distributed over a federation of servers. Each user may build their own personal local model and insert relations to other available models. As the number of interrelated objects grows, a wider-ranging global model starts to emerge.

Figure 2 shows our system architecture.

Figure 2: The system architecture

The main topics of this research were:

• Modelling of the space dynamics
  • What is the relation between the dynamics that may be observed in situ and the dynamics that can be captured by the deployed sensor networks (e.g., WiFi network)
  • WiFi data analysis based on:
    • The number of users per access point
    • Lists of MAC addresses per access point
    • Anomaly detection techniques
      • Utilization level difference
      • Pearson correlation
      • Spearman rank correlation
      • Entropy
      • Development of a set of processing modules for automatic model feeding:
        • Classification of access points based on the utilization rate and the  average number of users;
        • Correlation between pairs of access points
        • Hotspots detection based on the data generated by the two previous modules and on the distance between correlated access points
        • Tenant level calculation which indicates if a place is visited mostly by its tenants, by frequent visitors or by strangers
        • Detection of groups of users
        • Development of an editing application for manual model feeding (SC Space Editor)
        • Development of a pedestrian navigation application (Route Finder)

The prototypes of our applications may be found on the following links:

• SC Space Editor: http://local.dsi.uminho.pt/scse
• SC Browser: http://local.dsi.uminho.pt/scb
• Route Finder: http://local.dsi.uminho.pt/route

This research project resulted in the following publications:

1. K. Baras, A. Moreira, “Anomaly Detection in University Campus WiFi Zones”, in Proceedings of the 7th Workshop on Managing Ubiquitous Communications and Services, Mannheim, 2010.
2. K. Baras, A. Moreira, “Symbolic Space Modeling Based on WiFi Network Data Analysis”, in 7th International Conference on Networked Sensing Systems (INSS’10), Kassel, 2010.
3. K. Baras, A. Moreira and F. Meneses, “RouteFinder – Symbolic World Model Assisted Navigation”, International Conference on Indoor Positioning and Indoor Navigation (IPIN), Zurich, 2010.
4. A. Moreira, F. Meneses and K.Baras, “Self-location and navigation without maps”, demonstration, International Conference on Indoor Positioning and Indoor Navigation (IPIN), Zurich, 2010.
5. K. Baras, A. Moreira, “Groups and frequent visitors shaping the space dynamics”, The 4th Conference on Smart Spaces ruSMART 2011, S. Petersburg, 2011.
6. K.Baras, “Dynamic world models for context-aware environments”, Thesis (PhD),  University of Minho, 2011.