Working files & insights outlining the: Why, What & How, for TootAfrica (a subsidary of TootGlobal)

Machine Learning model to create an optimized ambulance deployment strategy in Nairobi.

this android application was a part of my mobile computing course at IIITD

A comprehensive analysis and classification of accident-prone zones in Australia using historical road crash data, leveraging machine learning models to predict and categorize high-risk areas.

🛣️ Identify roadway errors and improvement areas from images.

Source Code for Random Forest Accident Severity Prediction Modelling

This is my bachelor's thesis, which contains three main features: lane detection, road segmentation, and a Forward Collision Warning (FCW) system

Tathva Project

Road collision data for the United States

World Data League Stage 3 submission. Predicting Road Safety in Lisbon with YOLOv5 and visualizing results in deck-gl.

This repository hosts the official promotional website for the RoadVisor project, an innovative AR navigation application designed to enhance the driving experience. The website provides detailed information about the project, its features, the team behind it, and more.

A comprehensive software system leveraging convolutionary neural networks, drones, and IoT for real-time road quality monitoring and alerts. Built using Python, TensorFlow, Django, and Vue.js.

RoadVisor is an augmented reality navigation application aimed at enhancing the driving experience. It combines real-time traffic information and advanced computer vision techniques to improve safety and efficiency on the road. The project is brought to life by a passionate team of computer engineering students.

A site where you can upload videos to build road safety awareness in India.

Classification of traffic accident severity in Quebec

Self driving car project developed as a part of the course Software Engineering at NIIT University.

This project focuses on deriving insights from Irish road safety data from 2005 to 2012

prototype system that helps to recognize hand gesture to normal people in order to communicate more effectively with the specially disabled people

Driver Drowsiness Detection - A robust solution leveraging computer vision and machine learning. Unleash the power of facial and eye movement analysis for real-time fatigue alerts, contributing to an unparalleled level of road safety.