Overview
OneData’s Traffic & Parking Intelligence Platform integrates IoT edge devices, smart video analytics and cloud-based AI to transform how traffic flow and parking assets are monitored, managed and optimised. Built on AWS, the platform is designed for dynamic urban mobility environments — from smart city intersections and airport garages to large retail or commercial parking facilities.
Architecture & AWS Integration
• AWS IoT Greengrass runs on edge devices with smart cameras and sensors, enabling local preprocessing of video and telemetry, reducing latency and bandwidth consumption.
• Amazon Rekognition performs video analytics for vehicle detection, parking occupancy classification, license-plate or anomaly recognition, and triggers events such as “parking slot freed” or “illegal parking”.
• Captured and processed events are streamed to AWS cloud services (e.g., Kinesis Video Streams, Lambda) for aggregation and orchestration.
• AI/ML models (built with Amazon SageMaker) consume processed event-data to predict traffic congestion, parking demand peaks, and dynamic allocation of parking resources.
• Dashboard and reporting layers visualize key metrics: slot usage, traffic bottlenecks, dwell times, and predictive trendlines for planners and operators.
• The full solution supports smart-city, retail or airport scenarios: cameras detect cars arriving/departing, smart routing guides drivers to available slots, and predictive models forecast upcoming congestion or parking load.
Capabilities
• Real-time vehicle and parking slot detection via computer vision & IoT edge.
• Congestion prediction and routing optimisation based on live and historical data.
• Automated parking guidance: availability notifications, dynamic slot assignment, violation detection.
• Insight dashboards & analytics for traffic management teams and operators.
• Scalable deployment: from single parking lots to city-wide multi-node systems.
• Seamless integration with existing infrastructure (CCTV, sensors, signage) and cloud-native AWS services for manageability and reliability.
Use Cases
• Smart cities managing intersections, urban parking, and traffic signal systems.
• Shopping malls or airports optimising parking slot allocation, reducing search time for drivers and improving throughput.