Vision Based Drowsiness Detection System

style="background-color: #222222 !important;color: #eeeeee !important;">A drowsiness detection system based upon finding the eye aspect ratio can be installed in every vehicle in order to avoid horrible accidents. The system includes small webcam installed in every vehicle in order to track the eyes

Project Title

Vision Based Drowsiness Detection System

Project Area of Specialization

Artificial Intelligence

Project Summary

This project describes a system used to detect the drowsiness of the driver. This project mainly has two modules. First module is used to detect the drowsiness of the driver and second used to alert the driver if drowsiness is detected. In this system a camera placed in front of the driver is used for the continuous monitoring. This camera feeds data to the processor and processor simulate using algorithm to detect the drowsiness of the driver. The process is based upon the eyes state of the driver. This technique can find drowsiness of a driver and can avoid some serious happenings.

Project Objectives

A drowsiness detection system based upon finding the eye aspect ratio can be installed in every vehicle in order to avoid horrible accidents. The system includes small webcam installed in every vehicle in order to track the eyes of the driver. Usually the camera will get the real-time input in the form of video. The video will then be split into frames and each frame will be processed by the processor. The processing speed depends upon the processor speed. The best to processor is the Raspberry Pi which has the highest processing speed of the real-time data. The processing is done in python language which checks the eye aspect ratio. Based on eye aspect ratio the processor will send the signal to alarm system. If the ratio is below the normal then alarm is turned ON. Usually the ratio is compared between the eyes closed and eye open.

Project Implementation Method

This project can simply be implemented in vehicles with a small camera on steering wheel or at a certain angle where the camera can easily detect the drivers eyes so that it could detect the drowsiness. Microprocessor would do the background processing, whether the drowsiness is detected or not and therefore it would trigger the alarm system accordingly.  

Benefits of the Project

This present innovation is about the system provides low cost drowsiness detection using continuously eye monitoring of the driver. In this system camera is placed in vehicle for the eyes monitoring of the driver. This system also include a processor use for the processing of the video using program feed in the processor. Processor process the data continuously to find the state of the eyes whether they are open are in closed according to the defined ratio. If eyes are not close it keeps on processing the data until processor finds something odd for the eyes aspect ratio. This system monitor driver face and eyes using camera place in the front of the driver. If the aspect ratio of eyes is below the defined aspect ratio for completely opened eyes, processor processes to find the time duration for which there is a difference in EAR(eye aspect ratio) and turns on the alarm system if needed so that  driver can initiate the safety measure to avoid any misshape.

Technical Details of Final Deliverable

Image processing done in background using Raspberry Pi with a python code embedded on it. Continous checking of real time frames of every second in order to check the drowsiness. If drowsiness is detected alarm system goes on,

Final Deliverable of the Project

HW/SW integrated system

Type of Industry

Transportation

Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Life on Land

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com