PhD Proposal: Immersive Visual Analytics of Radio Frequency Signal Propagation and Network Health

Talk
Alexander Rowden
Time: 
03.13.2023 12:30 to 14:30
Location: 

IRB 3137

The world we live in is filled with important information that is constantly being communicated around us. This data is transmitted through radio waves and contains information such as health data, communications, and financial records. It is of little consequence whether the waves represent WiFi, Bluetooth, or chip readers for credit cards; the integrity of these communications is vital to our lives. Still, we cannot see how they interact with each other and their environment as they are invisible to the human eye. Thus, there is a need for comprehensive visualization techniques to allow experts to analyze sensor data and evaluate these signals. Traditional visualization techniques are not enough because of the scale of these datasets. By leveraging novel techniques in volume rendering and virtual reality (VR) in this work, we present two systems a) an outdoor volume rendering visualization that allows large-scale visualization over a college campus that minimizes the memory requirement of the rendering while allowing real-time customization of the result for analysis purposes and b) an indoor, building-scale visualization that allows data to be collected and analyzed without blocking the environment for the user.In our outdoor system, we present the Programmable Transfer Function. Programmable Transfer Functions offer the user a way to replace the traditional transfer function paradigm with a more flexible and less memory-demanding alternative. Our work on indoor WiFi visualization is called WaveRider. WaveRider is our contribution to indoor-modeled WiFi visualization using a virtual environment. WaveRider was designed with the help of expert signal engineers we interviewed to determine the needs of the visualization and who we used to evaluate the application. Both of these works provide a solid starting point for signal visualization as our networks transition to more complex models.Indoor and outdoor visualizations are not the only dichotomy in the realm of signal visualization. We are also interested in visualizations of modeled data compared to visualization of data samples. Our future work will include the design of multiple sample-based visualizations and a formal evaluation where we compare these to our previous model-based approach. We hope to show that visualizing the data directly without modeling improves user confidence in their analyses.

Examining Committee

Chair:

Dr. Amitabh Varshney

Dept. Representative:

Dr. Nirupam Roy

Members:

Dr. Kirsten Whitley (US Government)

Dr. Eric Krokos (US Government)