DriveSmart: An Autonomous Mobility Solution

Objective:

The project will deliver a Bluetooth-enabled application for secure, remote activation of an autonomous vehicle, powered by encrypted biometric authentication via PySyft—achieving over 98% accuracy in diverse real-world conditions. PyTorch-based anomaly detection provides 95% precision, validated across 10,000+ sensor inputs to identify early-stage malfunctions. Real-time diagnostics are visualized through dynamic Plotly dashboards. Agentic AI enables multilingual reporting in English, French, and Spanish, with translation accuracy exceeding of 97%.

Picture Of An Autonomous Vehicle:

Features:

Biometric Authentication with PySyft:

• Encrypted verification of user identity using biometric data.
• High accuracy and privacy-preserving computation.

Remote Vehicle Start via Bluetooth:

• Smartphone-controlled ignition using Bluetooth.
• Supports seamless pairing and real-time connectivity.

Vehicle Anomaly Detection with PyTorch:

• AI model trained on 100k+ telemetry record.
• Detects irregularities in engine, battery, brakes, and more.

Interactive Dashboard with Plotly:

• Real-time graphical display of vehicle diagnostics.
• Error trend visualization, performance history.

Multilingual Report Generation (Agentic AI):

• English, French, and Spanish translations of vehicle health reports.
• Text-to-speech and push notifications supported.

Installation:

Prerequisites:

• Python 3.8
• Pip package manager
• Bluetooth-enabled smartphone and vehicle hardware
• PySypt
• Cryptography
• Pandas
• Tenseal
• Numpy
• Linux
• Pytorch
• Plotly
• socket-io

Agentic AI Configuration:

API Credentials:

• Register and obtain your Gemini API key from Google AI Studio
• Store the key in .env file

LangGraph Flow Setup:

• Define a multi-step processing graph for translation and reporting

Configure nodes for:

• Input normalization
• Gemini translation output
• Language detection
• Report rendering