Within the aim of supporting territories to create more sustainable systems, road infrastructure plays a paramount role, not only because road shoulders represent a non-negligible land area, including their own biodiversity, but also because this represents the interface with the territory's ecosystems. For this reason, future road management systems should include all the different dimensions of sustainability. However, sustainable management of roadsides can be considered a complex and dynamic process. It requires access to data, from communities, maintenance services, suppliers of mowing equipment, and the roadsides themselves (physiognomy of the terrain, the composition of the soil, biodiversity, the composition of the area to be mowed and pruned, etc.). Therefore, the current development of Industry 4.0 opens opportunities to capture, aggregate, and analyze the information needed to support decision-making by territory planners and to provide the network's various stakeholders with complete visibility. Although generic models for decision-making in big data environments have been proposed in the scientific literature, they fail to deal with the specific characteristics and data requirements of such a system. In this context, this paper proposes the integration of a process based on the dynamic systems theory and the Industry 4.0 paradigm to achieve sustainable management of roadside processing. It will enable us to identify and manage in a proper manner the varying and heterogeneous amount of data that this type of system entails. The proposed model will support territory policy-makers to take sustainable actions in order to ensure efficient decisions with a long-term view, to assess the current situation and future opportunities, and then to contribute to the evolution of territories towards a circular economy.