Big data‑driven decision support systems for smart cities: challenges and solutions

Abstract

Smart cities are densely populated urban areas that leverage digital technologies to improve governance, sustainability and quality of life. Massive volumes of real‑time data generated by sensor networks and connected devices create opportunities for more informed decision‑making across transportation, energy, public health and other domains. This paper proposes a conceptual framework for a big data‑driven decision support system (DSS) that integrates heterogeneous data sources, advanced analytics and domain‑specific models to support urban planning and service delivery. We discuss the components of the framework, identify key challenges faced by practitioners, and suggest solutions and future research directions. Case examples of smart city initiatives illustrate the potential of big data‑driven decision support to reduce congestion, optimize resource consumption and enhance citizen services.