Eco-routing has been proposed as a means of distributing traffic in cities to improve mobility sustainability [1-3]. The implementation of eco-routing in real-life requires a diverse set of information, including heterogeneous and legacy sensors often already present in the city infrastructure. In this work, we present a modular architecture leveraging Internet of Things (IoT) technologies that enables collecting the necessary data, fusing it, and inferring the information required for the eco-routing application. Further, we formulate the eco-routing problem as a multi-objective optimisation to distribute traffic targeting better pollutant emissions vs travel time trade-offs. A city manager chooses the desired solution, which is used to serve routes, e.g. to a fleet committed or incentivized to contribute to an environmentally friendlier city. Preliminary results show the potential impact of eco-routing using real data for a mid-sized European city, and the impact of using static emission weights in the optimization formulation.