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TableNOC: Monitoring and Controlling Telephony Networks Using Multitouch Tables/Displays

This is a completed project.


TableNOC is a surface-based application for visualizing and monitoring network data. Through the use of open-source geographic information systems (GISs), including OpenLayers and MapServer , we are able to visualize information about calls, texts, and other geo-locateable data. Network operators can use these visualization to understand information about networks like the load on devices, the locations of regions of high call volume, etc. This can be done on either sets of data that have been previously collected or on data fed into the system in near-real time (1-minute increments).


The first use case for TableNOC is as a system for putting historical data about network events into a geospatial context. To accomplish this, we make use of point maps and heatmaps to display the relative density of calls ito the system within a given time period. This is useful for understanding where services are most heavily used:


For near-real-time data, we can take this one step further and actually map not only the location from which a call originates but also the destination at which it is handled. Locations of interest can be tapped to bring up a bubble with additional information. This allows us to understand the geospatial, distributed nature of the network as it is changing:

TableNOC is being developed with an emphasis on usability. In light of this, we included functionality for allowing users to easily upload and visualize their own data. This system works with historical data (from .csv files) and web services.

Currently, TableNOC runs on a variety of devices and browsers – including its touch functionality. This was done using a JavaScript implementation of TUIO, Caress.

Even as a research prototype, TableNOC has already turned a very significant profit for our industry partner.


Future Work

Further work on the visualizations used in TableNOC will be done. Specifically, we are investigating visualization techniques that display information about how the network is behaving without overwhelming TableNOC’s users with information. We are finding ways to aggregate data so that makes sense at different zoom levels.

We are also working on visualizations and interactions that allow us to determine if factors like quality of service or cost are impacted by the way in which a call is routed by our industry partner. This will also allow us to understand if quality of service is adequate at call centers and draw operators’ attention to trouble points. Further, we are looking into doing more work with real-time data and with previously-collected data to predict how the current state of the system could influence its state in the near future. This would allow us to predict with critical situations occur so that they can be dealt with proactively.

Finally, we are working on incorporating a greater range of touch interactions into the system in order to encourage users to explore and engage with their data.


Demos and Software Components

The data visualized by TableNOC is currently of a sensitive nature. We regret that we are not able to link to the live website at this time, since the application itself is behind an authentication system.


Research Partners

Funding is provided by ivrnet, TRTech and NSERC through a Collaborative Research and Development grant.



  • Dr. Frank Maurer (Supervisor)
  • Theodore D. Hellmann (PhD Candidate)
  • Shahbano Farooq (MSc Student)
  • Julia Paredes (Research Assistant)
  • Sydney Pratte (Research Assistant)
  • Gabriela Jurca (Research Assistant)
  • Gellert Kispal (Research Assistant)
  • Mandy Wong (Research Assistant)


Past Researchers

  • Ali Hosseini Khayat (PhD Student)
  • Patrick King (Student Intern)
  • Abhishek Sharma (MSc Student)