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