Real-time Implementation of a Smart IOT-Based Driver Drowsiness Detection System for Accident Prevention

The proposed system detects driver drowsiness and acts as a collision avoidance system in real time. To avoid accidents, this device typically combines two distinct systems into a single integrated system. The existing techniques are psychologically based in monitor the behaviour of the driver, but

Project Title

Real-time Implementation of a Smart IOT-Based Driver Drowsiness Detection System for Accident Prevention

Project Area of Specialization

Internet of Things

Project Summary

The proposed system detects driver drowsiness and acts as a collision avoidance system in real time. To avoid accidents, this device typically combines two distinct systems into a single integrated system. The existing techniques are psychologically based in monitor the behaviour of the driver, but collision avoidance sensors have not been installed. The existing system is an Arduino-based system that is ineffective in a real-time scenario due to time delay. As a consequence, the proposed system is used to build a non-intrusive technique for connecting driver drowsiness with the severity of a collision caused by braking or a mishap. This system’s main components are the Raspberry Pi3 model B+ module and Pi camera module that are used for persistent recording of face landmarks that are localized through facial landmark points then to calculate EAR. However, if the calculated EAR value exceeds the threshold range, the eyes remain open and no change in system state occurs. Similarly, if the EAR value falls beyond the threshold range, the system immediately alerts the authority (owner) via speech speaker and warning e-mail for extra supportive alertness to the driver. Furthermore, the severity of the collision (impact) is measured through the integration of sensors with the GPS module in order to properly track the location of the accident.

Project Objectives

The purpose of the drowsiness detection device is to aid in the prevention of accidents passenger and commercial vehicles. The system will detect the early symptoms of drowsiness before the driver has fully lost all attentiveness and warn the driver that they are no longer capable of operating the vehicle safely. If there is a car accident, this device will be capable of sending the exact location of the vehicle to the owner via E-mail.

Project Implementation Method

Step 1 – Take image as input from a camera.

Step 2 – Detect the face in the image and create a Region of Interest (ROI).

Step 3 – Detect the eyes from ROI and feed it to the classifier.

Step 4 – Classifier will categorize whether eyes are open or closed.

Step 5 – Calculate score to check whether the person is drowsy.

Benefits of the Project

Benefits of this project are:

1. Driver will be alert while driving.
2. Less chances of accident due to drowsiness of driver.
3. Owner will have the exact location in case of any mishap.

Technical Details of Final Deliverable

The project's final deliverable will be a device that will aid in reducing vehicle accidents (cars, buses, trucks, etc.) caused by driver drowsiness. The device will detect the driver's eyes using an AI system, and if the driver's eyes close due to drowsiness, the system will sound an alarm. If there is a car accident, this device will be capable of sending the exact location of the vehicle to the owner via E-mail. And the owner will be able to monitor time intervals when the driver's eye is closed for longer than the fixed time limit.

Final Deliverable of the Project

Hardware System

Core Industry

IT

Other Industries

Core Technology

Internet of Things (IoT)

Other Technologies

Sustainable Development Goals

Good Health and Well-Being for People

Required Resources

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