Driver Safety Assistance

Humans are now much modernized as compared to the previous ages. Now modern inventions are being used by humans almost in every aspect of life. As the humans are progressing in technology day-by- day, the more humans are putting their lives in risks. We have cars for the purpose of transportation wh

Project Title

Driver Safety Assistance

Project Area of Specialization

Internet of Things

Project Summary

Humans are now much modernized as compared to the previous ages. Now modern inventions are being used by humans almost in every aspect of life. As the humans are progressing in technology day-by- day, the more humans are putting their lives in risks. We have cars for the purpose of transportation which help us to travel in a quick and easy way within the city in very short period.

On December 2018, World Health Organization (WHO) launched a report on global status based on roadside safety, which highlights that the number of yearly road traffic deaths has reached 1.35 million. Roadside traffic injuries are now the leading cause of death of the people belonging to age group of 5-29 years. According to the survey of motorway police and National Highway Authority, approximately 15000-16000 people lose their lives in Pakistan because of the roadside accidents. The real causes behind the roadside accidents are fatigue, drowsiness, and distraction of the driver.

As per United Nation’s 17 Sustainable Development Goals, multiple domains should be explored to make life more effective and secure. Following the goal of “Industry, Innovation and Infrastructure”, a modern technology-based Driver Safety Assistance System is proposed which is a real time system for cars that will monitor and detect the activities of the driver while driving the car and will alert the driver if there are any signs of drowsiness, distraction, and fatigue are found. This project is based on IOT concepts and Machine Learning. OpenCV will be used for detection of drowsiness and fatigue through image processing. The main idea is to deploy OpenCV and Machine Learning modules on Raspberry Pi hardware to achieve the required functionality like real time detection. Furthermore, some relevant features like facial recognition, live tracking and parental control will also be added, and smart phone application will be developed to monitor and control the other features.

Project Objectives

• To utilize industrial innovation in order to minimize the number of roadside accidents and secure human lives by developing a system “Driver Safety Assistance”.
• To design a real time system for monitoring the activities of driver and take specific actions under certain circumstances to avoid roadside accidents, and to help driver/car owner to easily monitor the activities which are related to the car.
• To solve above mentioned problems, a system can be developed which will monitor the activities of the driver while driving and alert the driver, if there are any sign of drowsiness, fatigue, and distraction

Project Implementation Method

To develop this project, the incremental model will be adopted. With the help of this model, different modules of the project will be developed one by one, and will be integrated into pervious developed module, this is how the project will be completed in iterations, and time to time progress can be shown.

Benefits of the Project

The system provide safety to drivers by detecting and monitoring the activities of the driver and sending alert to user. System also provide security from unauthorize persons and location tracking to the car owner. 

• Detect and monitor the activities of the driver and warn if there are any sign of fatigue, drowsiness, and distraction.
• System provides safety of car with the help of facial recognition module. Camera will capture the live streams to detect if any unknow person sits in the car or the car gets stolen, it will alert to the owner of the car. The owner can track the live location of the car through GPS module which will help to get his car back.
• Parents can also set the parental controls for their child, like over speed detection and going far away from home.

Technical Details of Final Deliverable

Embedded system consists of Raspberry Pi 4, Night Vison Camera and GPS modules, with OpenCV and Machine Learning models deployed on raspberry pi for real time detection of drowsiness, fatigue and focus of driver. Also, with real time car location tracking, over speeding and going out the restricted area alert on smart phone application.

Final Deliverable of the Project

HW/SW integrated system

Core Industry

Transportation

Other Industries

IT , Health , Security

Core Technology

Internet of Things (IoT)

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Good Health and Well-Being for People, Industry, Innovation and Infrastructure

Required Resources

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