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This study proposes a novel approach to optimize traffic sensor placement in urban areas for better congestion management. By utilizing centrality measures such as Degree, Betweenness, and Closeness, critical links in the network are identified, reducing the number of required measurements while maintaining the representativeness of the Network Fundamental Diagram (NFD). Evaluation with real data from Chania's urban network demonstrates consistently low error values, indicating the effectiveness of this method. Integration of topology elements offers a promising solution to the problem of suboptimal sensor placement, enhancing congestion management strategies in urban environments.