UAV Sensor Operator Training Enhancement Through Heat Map Analysis

Ashish Amresh, Arizona State University
John Femiani, Arizona State University
Jason Fairfield, Arizona State University
Adam Fairfield, Arizona State University

Dr. Amresh was not affiliated with Embry-Riddle Aeronautical University at the time this paper was published.


Heat map based data visualization and mining is an emerging area in game engine design and architecture. Employed by many state of the art game engines and popular commercial games, this technology helps populate and collate player activity and behavior to better inform the system for further action. Simulation and serious games can tremendously benefit by applying heat map based visualization for the purposes of analyzing and tracking player behavior. Heat maps are time varying texture maps that represent a chosen activity over a certain grid at any particular interval of elapsed time. In this paper results of applying a real-time heat map data capture and generation tool on two military simulations: 1) Ground-based combat scenario and 2) Unmanned Aerial Vehicle sensor operator scenario is presented. The research showcases several real-time visualization techniques developed into the simulation with the main goal of understanding participant behavior. Novice and expert data is populated as part of the experiment to validate the effectiveness of our methods.