Smart or digital city infrastructures facilitate both decision support and strategic planning with applications such as government services, healthcare, transport and traffic management. Generally, each service generates multiple data streams using different data models and structures. Thus, any form of analysis requires some form of extract-transform-load process normally associated with data warehousing to ensure proper cleaning and integration of heterogeneous datasets. In addition, data produced by these systems may be generated at a rate which cannot be captured completely using standard computing resources. In this paper, we present an ETL system for transport data coupled with a smart data acquisition methodology to extract a subset of data suitable for analysis.