Driver drowsiness is the most critical cause of road accidents so detection of drowsiness play a vital role in preventing road accidents. We are developing an android app that will alert drivers before an accident occurs. This will reduce the number of road accidents on a road. Drowsiness is a natural phenomenon that happens in human body due to different factors. Machine learning was applied to predict drowsiness and improve drowsiness prediction using facial recognition technology and eye-blink recognition technology. In this app, front camera will take a picture of drowsy driver then this picture will be taken as input. In processing the detected image, we are using OpenCV Library. OpenCV Library uses Haar Cascade Classifier for detection images such as eyes and face. Eyes and face will be the target in this system. This application will be implemented on Android Operating System. Drowsiness detection system will send alert to the driver when the driver feels asleep while driving a car, this can avoid accidents. Driver which is the user in this application, if they close their eyes within one second, the sensor which is the front camera in the smartphone will catch and process this event and then trigger the system to give voice alert to the user. Moreover, if the driver is willing to turn on back camera then it will detect the lane detection violation and will calculate the distance from the vehicle ahead of it. If the distance is too close, then it will generate an alarm. It will also generate an alarm if there is a violation of the lane on the road.

DriveSafe: A smartphone app to monitor reckless driving behaviors

DriveSafe is an ML app combating drowsiness and distraction in drivers using computer vision and AI. It merges PyTorch with Apple's Core ML, harnessing YOLOv8's object detection. Trained on a unique dataset, it's a vital tool for road safety.

No description available

DriveSafe : An android app integration that alerts a distracted driver using the machine learned model parameters.

Driver behaviour recognition using data collected in 2016 by using a smartphone app DriveSafe for the purpose of deep driving behaviour analysis.

🚗 Welcome to DriveWise - the NoCode app repository! Discover how we're revolutionizing road safety through innovative technology. Join us on our journey to make every drive safer and smarter! 🛣️ #DriveSafe

No description available

DriveSafe app

Landing Page for the DriveSafe App

React Native App of DriveSafe project

No description available

No description available

Application to help encourage safe drinking habits and warn users of potentially being close to or over the legal drinking limit.

This Repository holds all the files for this Android App

No description available

No description available

No description available

No description available

App that gives alert to driver when they reach a accident prone area and other alert via IOT device plugged to car

No description available

semester 6 main project

No description available

No description available

Aplicacion clónica de Social Drive

No description available

DriveSafe is a real-time anti-sleep alarm that uses AI eye tracking to detect drowsiness and trigger instant buzzer + motor alerts, keeping drivers safe on long journeys. Built with MediaPipe FaceMesh & Web Serial API.

DriveSafe is a research-based mobile application designed to combat phone-induced distracted driving. By integrating Behavioral Economics with Gamification, the app addresses the "Present Bias"—the cognitive tendency of drivers to prioritize the immediate gratification of a smartphone notification over the long-term, uncertain safety of the road.