A real time, webcam based, driver attention state detection/monitoring system in Python3 using OpenCV and Mediapipe
Real-time drowsiness detection using Python, MediaPipe, and EAR to monitor driver fatigue and prevent accidents.
Python-based Fleet Management System with real-time automotive telematics: OBD-II diagnostics, GPS tracking, CAN bus decoding, DTC analysis, driver behavior monitoring, fuel analytics & live dashboard. Built with FastAPI + SQLAlchemy.
MVP for detecting drowsiness of driver using the eye lids of the driver, if the driver seems to be drowsy it gives an alarm
Convolutional Neural Network for predicting driver attention based on a front-facing image of the driver 🚘
While drunk or drowsy people can’t react to stimuli efficiently in the environment, thus we intend to check for a verbal response from the driver upon detecting anomalous driving patterns. IMU tracker upon detecting frequent changes in acceleration and sharp turns triggers the voice assistant, checking up on the driver’s state and takes further …
Driver Behaviour Analysis System (DBAS) is a ROS-based driver monitoring system utilizing OpenCV, Dlib, and YOLOv5 to detect and alert on drowsiness, device usage, and other behaviors during driving.
Jetson Nano Drowsiness Detection - SUSTech Project of CS324: Deep Learning in Fall 2025 - Score: 95/100
IoT-based system for real-time driver drowsiness detection using ESP32 and cloud services for monitoring and alerts.
A real-time driver fatigue detection system using computer vision. This project monitors eye movements to detect drowsiness and alerts the driver with a visual and audible warning when fatigue is detected. Built with OpenCV, dlib, and Python, it's designed for enhancing driver safety.
Analyzing large-scale vehicle camera datasets using Convolutional Neural Networks to classify distracted driving behaviors and evaluate trends in driver position change for road safety applications.
Proyecto 1 - Programacion Concurrente Y Paralela
Driver drowsiness detection using YOLOv8n face ROI, a CNN classifier, Grad-CAM explainability, and fuzzy risk mapping.
A real-time drowsiness and yawn detection system built with Python, OpenCV, and dlib to help prevent accidents caused by driver fatigue.
Real-time driver drowsiness detection using OpenCV and MediaPipe with EAR and MAR based voice alerts
While drunk or drowsy people can’t react to stimuli efficiently in the environment, thus we intend to check for a verbal response from the driver upon detecting anomalous driving patterns. IMU tracker upon detecting frequent changes in acceleration and sharp turns triggers the voice assistant, checking up on the driver’s state and takes further …
AI system that detects driver drowsiness in real time using computer vision
This repository contains source code in Arduino for the project-"Driver Safety Enhancement System", that was carried out in Hackathon: "Byte-Camp'19"
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