Road Traffic Data Analytics Platform

The client needed a government-cloud traffic analytics system for city-wide management, processing historical and real-time transport data to assess congestion and respond quickly to incidents. The platform required high scalability, reliability, and continuous availability for public services.

Challenge

• Massive real-time and historical transport data from city-wide sensors needed processing at scale
• Slow identification and response to traffic incidents impacted city operations
• The platform needed to handle peak-hour data loads without degradation
• Government services demanded near-zero downtime and API reliability

Solution

• Public data access via secure internet-facing APIs
• Traffic data refreshed every 5 minutes for near-real-time visibility
• Auto-scaling cloud infrastructure with zero service interruption
• Continuous ML model retraining without API downtime
• GovCloud deployment on AWS for regulatory compliance

Architecture

Outcome

• 30-40% incident response time reduction through real-time alerting
• 99.95% data availability across all endpoints
• 90% congestion prediction accuracy using ML models
• Platform serves as the backbone of Hong Kong’s traffic management operations

Tech Stack

• Backend: Java, Spring Boot
• Frontend: React
• Infrastructure: AWS GovCloud