Autonomous Vehicle ADAS Lane & Obstacle Collision Warning System
Advanced Driver Assistance System with dynamic polynomial lane curve estimation, YOLOv8 vehicle/pedestrian distance bounding, and Time-to-Collision (TTC) acoustic warning.
Detailed Project Overview
An embedded computer vision ADAS implementation. Processes forward-facing dashcam video streams in real-time, executing perspective bird’s-eye transformations, sliding-window polynomial lane fitting, and monocular depth estimation to alert drivers of imminent front collisions.
Academic Problem Statement
Driver distraction and inadvertent lane departures account for over 35% of fatal highway crashes. Affordable camera-based ADAS software is needed for mass automotive retrofitting.
Proposed Methodology & Flow
More Projects in Artificial Intelligence & Machine Learning
Explore alternative architectures and applications in this discipline.
AI-Powered Smart Attendance & Anti-Spoofing Facial Recognition
Real-time multi-face attendance logging with liveness anti-spoofing detection using YOLOv8, FaceNet embeddings, and automated faculty analytics dashboard.
Medical Image Classification for Pneumonia & Brain Tumor Detection
Clinical-grade deep transfer learning model with Grad-CAM visual heatmaps, classifying Chest X-Rays and Brain MRI scans with 97.8% diagnostic validation.
Real-Time Misinformation & Fake News Detector with Explainable BERT
Deep bidirectional transformer NLP model evaluating news credibility, emotional sensationalism bias, and source provenance with Chrome Extension integration.