Vehicle Telemetry with Raspberry Pi & Kafka

Capturing vehicle parameters using Raspberry Pi & ELM327 with real-time anomaly detection planned using Kafka and Spark

A Raspberry Pi-powered telemetry console that connects to your car’s OBD-II port using ELM327 (or CAN Bus), captures parameters like RPM, speed, coolant temperature, and displays them in real-time on a Python-based UI.

In the future, we plan to stream data over Kafka using a 4G modem and analyze anomalies using Spark ML.

🚗 System Architecture

The current and planned system architecture from ELM327 → Raspberry Pi → Kafka → Spark ML model.

🔧 Completed Features

  • Vehicle data captured via ELM327 (Bluetooth) or CAN bus.
  • Real-time dashboard on Raspberry Pi showing RPM & speed.
  • Python UI-based instrument console.

🔬 Planned Enhancements

  • Integrate Kafka to stream telemetry via 4G modem.
  • Use Apache Spark for real-time anomaly detection.
  • ML model to predict early signs of failure.

📷 Screenshots & Demo

From left to right: OBD-II dashboard, real-time speed/RPM values, Raspberry Pi console display.

📽️ Demo Video

💻 Source Code

🔗 GitHub Repository

🔍 Technologies Used

  • Raspberry Pi (Python)
  • ELM327 / CAN Bus
  • Bluetooth communication
  • Apache Kafka (Planned)
  • Apache Spark ML (Planned)

If you’re interested in IoT meets machine learning, or automotive diagnostics — feel free to explore the repo, suggest enhancements, or fork it!