Waste collection is a sensible topic in the context of smart cities. The tactical collection operation usually leaves room for improvement mainly in the form of schedule optimisation. The study in question explores the benefits of having access to additional contextual information, specifically data related to the dumpsters’ filling process. In this setting, there are two ways to predict the current waste volume held by each of the dumpsters: the first, which introduces high variance and can only be performed during the collection phase, relies on an estimation through weighting performed by the garbage truck; the second, which provides higher precision, utilises volumetric sensors positioned inside the dumpsters.