The Signals and Systems Research Group focuses on integrating mathematical modeling with artificial intelligence (AI) algorithms. The resulting methods require significantly fewer training resources, while their mathematically grounded, model-driven architecture ensures transparent and interpretable decision-making. These results are broadly applicable across various fields of signal processing, including medical and engineering applications. This video presents a proprietary model-driven, AI-based signal processing system that utilizes data from a sensor embedded in a tire to identify road type and road surface quality in real time, and to estimate the tire–road friction coefficient.