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AI & Machine Learning
Active / Ongoing
ADAR v3.0
ADAR v3.0 is a comprehensive, real-time driver assistance and safety monitoring system. It leverages computer vision and hardware integration to proactively monitor driver states and vehicle telemetry, aiming to reduce accidents through high-end automotive safety technology.
Python
OpenCV
YOLO
MediaPipe
C++
ESP3
A
LEAD
Aditya Raj
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The GitHub repository, documentation, and demo links for this project are protected. Only club members and authorized users can access these resources.
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Technical Specification
The architecture integrates a localized machine learning pipeline with embedded hardware for low-latency response. The software stack utilizes Python, OpenCV, and YOLO/MediaPipe models for real-time facial feature extraction and object detection to monitor driver alertness. This vision system is interfaced with microcontroller units (such as the ESP32) for physical safety triggers, utilizing a 1.3-inch OLED display for the telemetry dashboard and local system alerts. The system is designed for high reliability in edge-computing environments.
Achievements & Awards
3 TOTALNational Finalist — Presented ADAR v3.0 at the national-level hackathon at VIT Pune (April 2026).
VIT PUNE
Apr 24, 2026
Competition / Hackathon
Top 10 National Finalist — OpenAI Academy x NxtWave Buildathon National Finale, New Delhi (February 2026).
India AI Impact Summit 2026
Feb 18, 2026
Award / Recognition
State-Level Champion (1st Place) — OpenAI Academy x NxtWave Buildathon at Noida International University (December 2025).
State-Level Champion
Dec 15, 2025
Project Milestone
Team
2 MEMBERS
Aditya Raj
Project Lead
Deepak Kumar Gupta
Core Member