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Enhancing Urban Planning Outcomes with Geographic Information Systems and Digital Twin Technologies
Introduction Business challenges Solution overview Partner Overview Solution Architecture Validation
Validation
GIS urban and Smart City
Results Findings
Integration of GIS and Digital Twin platforms
Results Findings
Enhance GIS workflow with Digital Twin simulation capabilities
Results Findings
Conclusions References

GIS urban and Smart City

Home > Workload Solutions > Computer Vision > White Papers > Enhancing Urban Planning Outcomes with Geographic Information Systems and Digital Twin Technologies > GIS urban and Smart City

GIS urban and Smart City

  • Findings

    • Overall, the flow and functionality of the CityEngine platform is easy to use.
    • The graphics resource (1 xL40 vGPU - 48Q profile) utilization never exceeded >5% for any of the above use cases.
    • End-user graphic latency was noticeable (slow GUI movement, fewer than 5 Frame Per Second (fps) for long-distance remote sessions.
      • On-site user (distance to lab ~ 100 m , max network latency 5 ms):

        Good user experience CityEngine ~ 10 to 15 fps

      • Remote user (distance to lab ~ 25 km, max network latency 10 ms)

        Good user experience CityEngine ~ 10 to 15 fps

      • Remote user (distance to lab ~ 8500 km, max network latency 253 ms)

        Poor user experience CityEngine ~ 2 to 3 fps

      • Modification of CityEngine default camera rendering settings screen-space ambient occlusion (SSAO) significantly improved user experience for high latency connections
    Note: For high latency connections, see the Dell Technologies technical white paper Remote User Experience with Graphics intensive software, which describes performance considerations and best practices for optimizing remote user experience.