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Computer Vision for Public Transportation - Phase 2
Overview
Overview
Introduction
Document purpose
Architecture concepts Solution architecture Validation Sizing the solution Conclusions References

Document purpose

Home > Workload Solutions > Computer Vision > Guides > Computer Vision for Public Transportation - Phase 2 > Document purpose

Document purpose

  • This Design Guide shows how to design an end to end solution that can be used in the transportation sector. The testing focuses on use cases from a public transit system using buses as an example but it can be applied to multiple other transportation scenarios.

    The components of the solution that will be discussed in detail are:

    • AI computer vision execution on a public bus vehicle
    • Event and telemetry dashboarding using the EPIC iO public cloud-hosted services.
    • Data management and integration of ruggedized servers hosted in a public bus depot.
    • Integration from the depot to a centrally located data center.

    We designed our solution for public transportation following the best practices of EPIC iO for deployment of DeepInsights, an open AI + IoT software suite that combines and enriches video, external feeds, and sensor data into a seamless operational experience, as well as EPIC iO's DeepVision Application, a Federated VMS Platform with Integrated DeepInsights AI, IOT Sensor Fusion, and telemetry transmission to DeepInsights for aggregated and hierarchical visualization.