USF researchers have created analytic systems with the ability to analyze data in real-time. These analytics take the random nature of changes into account via a control process to speed up the prediction process and provide more accurate decision making procedures. The analytic method combines process control, signal processing, and machine learning analytics together to form a decision making system. This novel method is applicable to multiple processes over a variety of fields such as health sciences (real-time epileptic seizure prediction, heart problem diagnosis), environmental sciences (predicting and detecting honey bee dance moves used for communication), finance (decision making upon potential market changes). The adaptability of the analytic method has great potential to transform machine learning across multiple disciplines.
Scalp Map of Brain Activity for Average Amplitude Showing Use of Analytics for Prediction