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Smart Traffic Management with Edge + Cloud AI

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Smart Traffic Management with Edge + Cloud AI

  • Use Case: Urban cities face challenges of traffic congestion, accidents, and pollution. A smart traffic management system can leverage Edge devices + Cloud AI to analyze real-time video streams from traffic cameras, IoT sensors, and connected vehicles to dynamically control traffic lights, reroute vehicles, and improve road safety.

Objective

  • Optimize traffic flow and reduce congestion.

    Enable real-time decision-making using edge AI for low latency.

    Use cloud AI/ML for predictive analytics (accident hotspots, rush hours).

    Improve Quality of Experience (QoE) for commuters (shorter travel times, reduced emissions).

Project Description

  • The project integrates IoT-enabled traffic cameras and road sensors at intersections (edge layer). Edge devices (e.g., GCP Edge TPU, IoT gateways) run real-time AI models to detect vehicles, pedestrians, and congestion patterns.

    Data is sent to Google Cloud AI services for advanced analytics like traffic prediction, anomaly detection (accidents, violations), and long-term optimization.

    BigQuery stores historical traffic data for trend analysis.

    The system sends commands to traffic light controllers or mobile navigation apps to reroute traffic in real time.

Key Technologies & Google Cloud Platform Services

  • Google Cloud Service Purpose in Smart Traffic Management
    Google Cloud IoT Core / Edge TPU Connect IoT sensors, traffic cameras, and perform edge AI inference for real-time local decision-making.
    Pub/Sub Ingest high-throughput, real-time traffic data streams.
    Dataflow Handle both stream and batch data processing for detecting traffic events (e.g., congestion, accidents).
    BigQuery Store and query large-scale historical traffic data for predictive analytics and pattern detection.
    Vertex AI Train, deploy, and manage ML models for traffic forecasting, congestion detection, and accident prediction.
    Looker / Data Studio Provide interactive dashboards for city traffic authorities to monitor and analyze traffic flows.
    Cloud Functions Enable event-driven automation, such as sending reroute alerts to navigation apps.
    Cloud Run / GKE (Kubernetes Engine) Deploy scalable microservices for real-time traffic management APIs.
    Google Maps Platform APIs Deliver real-time rerouting suggestions, road conditions, and traffic status updates directly to drivers.