Asphalt : Real-Time Vehicle Data Processing Pipeline

Asphalt is a scalable, real-time data processing pipeline designed to extract actionable insights from vehicle position data.

Built for flexibility and resilience, it adapts to evolving data schemas and diverse use cases.

📖 Full Documentation available at: https://markov-ngz.github.io/Asphalt

Project Overview

- Apache Flink: Real-time data processing engine

- Apache Kafka: Distributed event streaming platform

- Kubernetes (K8s): Orchestration for scalable deployment (Docker setup also available)

Asphalt ingests, processes, and analyzes vehicle position data in real time, enabling:

- Dynamic integration of new data sources

- Seamless schema evolution ( medallion architecture )

- Support for emerging use cases

- Robust handling of real-time challenges (watermarks, state management, window computations)

All processed data is visualized in an intuitive dashboard, providing real-time traffic analytics for each route or line. Key metrics include:

- Maximum speed: Identify peak performance and potential bottlenecks.

- Average speed: Monitor overall traffic flow efficiency.

- Active vehicles: Track fleet utilization and operational density.