Urban Mobility Control Center

Eastgate built a centralized traffic data analytics platform for a German smart mobility client, enabling real-time monitoring and AI-assisted incident management across the urban road network. The platform processes historical and live traffic data through a microservices architecture on Kubernetes, delivering sub-200ms latency for operator dashboards and public information systems. Delivered as a dedicated engagement from 2019 to 2023.

Challenge

• No centralized platform to monitor real-time and historical traffic data across the urban road network
• Traffic incident management relied on manual assessment without real-time data feeds or automated alerting
• Required integration with existing city infrastructure and scalable deployment for city-wide coverage
• Limited ability to deliver timely, data-driven recommendations to traffic operators and the public

Solution

• Built a real-time and historical traffic data analytics platform for urban mobility monitoring
• Developed AI-assisted UI tooling for traffic incident monitoring and control center operations
• Implemented microservices architecture using Spring Boot and Spring Cloud for scalable service isolation
• Integrated real-time event streaming via Kafka for continuous traffic data ingestion and processing
• Deployed on Kubernetes using Docker for auto-scaling and 24/7 high availability
• Established monitoring and observability pipeline using the ELK Stack

Architecture

Outcome

• Improved traffic incident response efficiency by 30-40% through real-time monitoring and automated alerting
• Reduced real-time data processing latency to under 200ms across all traffic event streams
• Achieved 99.9% system availability across continuous 24/7 operational requirements

Tech Stack

• Backend: Spring Boot, Spring Cloud
• Data: PostgreSQL, Kafka, Redis
• Infrastructure: Docker, Kubernetes
• Tools: ELK Stack