Researchers are using Bluetooth traffic data to predict travel times in urban areas through a data-driven approach. The methodology involves filtering, cleaning, and fusing the data to develop advanced models and tools for forecasting congestion effects. One promising model is an ARIMA-based model that showed good results in predicting path travel times.