Having clear and fast information is decisive to ensure road safety. Nowadays, countless applications go in this direction: from innovative vehicle infotainment to intelligent traffic lights and control systems. Bad weather conditions are popularly acknowledged as a reason for diminished visibility and challenging brakings, thus resulting in higher risks for drivers safety. On-time information gathering and quick driver alerting are arguably among the lightest solutions to deploy for safer mobility. To this extent, many road stretches worldwide are already provided with roadside surveillance cameras, which are used in this scope as the source of real-time data. The work of this thesis falls in a wider collaboration with WaterView s.r.l., and it aims to develop a neural network-based model able to exploit these preexisting devices and detect the presence of water on the road pavement.