SmartCAN Analyzer: AI-Powered ADAS Validation Tool 🚗🤖

🎯 Project Overview

This tool automates the identification of anomalies in ADAS (Advanced Driver Assistance Systems) telemetry. It uses a custom QA Layer to validate physical constraints and AI (LLM/RAG) to generate technical diagnostic reports for engineering teams.

📊 Dashboard Preview

(The image below displays the interactive dashboard and AI analysis results)

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🛠️ Key Features

• Responsive Telemetry: Real-time signal visualization using Plotly.
• Deterministic QA: Python logic to catch sensor dropouts (e.g., -99m readings).
• AI-Driven Verdicts: Automated root-cause analysis based on technical manuals.

💻 Tech Stack

• Backend: Python 3.12 (Object-Oriented Programming)
• Frontend: Streamlit & Plotly
• AI: Gemini API Integration (Simulated)

⚙️ How to Run

1. pip install pandas streamlit plotly
2. streamlit run app.py