Measuring and Understanding Visualization Latency Performance for Smart City Applications

End-to-end latency is a critical metric in interactive and real-time systems, where even short delays can undermine usability, situational awareness, and trust. While most studies focus on network transmission delays, this overlooks other significant sources of latency, including sensor acquisition, processing, and especially visualization. Rendering pipelines are heavily influenced by hardware, visualization strategies, and data complexity, and in visualization-rich domains such as smart cities, these factors can add considerable overhead. Ignoring them leads to overly optimistic performance assessments and missed opportunities for optimization.In this work, we study the last mile of end-to-end latency, explicitly incorporating the visualization stage and bridging the gap between network-level metrics and user-perceived responsiveness. We introduce the Unreal Smart Cities Visualizer (USCV), a framework we have built to support precise latency assessment in realistic, data-intensive urban scenarios. Our contributions include highlighting the limits of network-centric evaluation, presenting a visualization-aware methodology, and demonstrating USCV as a tool for accurate end-to-end latency measurement.Our results show that visualization delays, particularly in latency-critical environments, are not negligible and cannot be underestimated.