real time drowsiness detection algorithm for drivers safety15066

Project Summary:  'Real Time Drowsiness Detection Algorithm for Driver?s Safety'  This project is reated to image processing field . Image processing is a method for transform a picture over to a digital perspective and fill specific roles on

Project Title

Project Area of Specialization

Artificial Intelligence

Project Summary

Project Summary: 

'Real Time Drowsiness Detection Algorithm for Driver’s Safety' 

This project is reated to image processing field . Image processing is a method for transform a picture over to a digital perspective and fill specific roles on it, to enhances image and get valuable data from it. Digital image processing is dependably a catching the more attention field and it freely transfer the upgraded multimedia data for human understanding and analyzing of image information for capacity, transmission, and representation for machine perception. . Continuous development in the field of real time image processing and its application to the industry motivated us to further investigate and contribute effectively in this direction. Drowsiness detection is a safety technology that can prevent accidents that are caused by drivers who fell asleep while driving. The detection of the driver fatigue and sleepiness during driving is main issue in every country and, it is expected that the amount of crashes will be reduced by 10%-20% using driver monitoring systems. It reduce an accidents factor and public safety. There are many algorithms and techniques which are used for drowsiness detection of driver like computer vision base system, EEG and EOG signals, CNN method, Multi-Task ConNN model, machine vision base system, Steering Wheel Movement (SWM) and also using filter etc. Our project is concept of  computer vision and based on real time that is to track the eye position by using  filter combined with normalized cross correlation based online dynamic template matching technique. Eye tracking is a technology that sense through the sensor or tracker to detect the eye position to find where the person is looking. The automotive industry is exploring solutions based on in vehicle sensors to monitor and prevent dangerous situations, making the vehicles smarter. The application of image processing design may also be utilized for driver's eye tracking by detecting correct information from sensor in moving cars. The proposed project is the requirement of imaging industry in order to enhance information content in the images. The filter design will allow us to track the eye positions and monitor the driver’s state. In order to make system effective, the images will be smoothened and further classified as open or close eye conditions. Preprocessing is performed in order to improve the quality. The filters are used in image processing to track human eyes, eliminates jitter interference, and greatly improves the accuracy of drowsiness detection. The study will be conducted on vehicles for guidance, navigation, and control of vehicles, particularly automobiles applications such as in highway traffic surveillance control, management, and urban traffic planning.

Project Objectives

Project Objective:

The idea of utilizing this automobile technology to recognize fatigue detection for driver safety based on tracking sensor. It has great potential to help a security purpose.

The aim of the project is to apply the engineering tools and knowledge for system design that is useful for the industry. The following objectives are to be achieved:

• To design a prototype for the driver drowsiness detection system.
• To collect data having different facial frames for eye detection.
• To improve and enhance quality of images for appropriate results.
• To interface with the camera for the real time tracking.

To plan a suitable algorithm for sleep detection and activate an alarm

Project Implementation Method

The flowchart of project implementation methodology is divided into three parts and these are data acquisition, image processing and segmentation. Our project is based on preloaded image template that are store on the system for identify the relevant image.

• First step is to data acquisition in which we collect images from different angle and in varying light condition and gathering those images when the eye are open and to close.
• The second step is to image processing, it deal with image enhancement that adjusting digital images so that the results are more suitable for display or further image analysis.
• De blurring the image to removing blurring artifacts from images and recovers a sharp image and noise removal, it can done by filter.
• The third step of flowchart is to segmentation, it correlation with real time image then condition of eye open/close occurs. So if eye is open then end the program and again start the feedback loop to the system
• And if eye is close then ringing the alarm for driver safety then end the program and again run the program.

Benefits of the Project

Benefits of the Project:

This project can be used in not only in automotive industry area but also in bank security, CC Tv footage security etc. This project is enabling to detect the drowsiness or fatigue detection of driver. This system is efficient to pre notify the alarm for driver safety therefore this system prevent the accidents more quickly and aware the sleepiness condition of driver. This project is great deal to  implementation of engineering knowledge to the practical world.

• Used for the safety of driver and vehicle.
• Beneficial for traffic security.
• Abnormal behavior of driving is corrected through alarms in real time.
• Components are adjustable to interface with different drivers.
• Practically applicable in any type of vehicles.

Technical Details of Final Deliverable

This image describe technical details of final deliverable project. Behind this real time frame deals with implementation of the overall methodology. The first is to adjustable camera will installed in car manufacturing  or placed at the front of driver like dashboard then system continuously detect the  eye location of driver and to correlate these current frame with reference frame for determine the fatigue detection of driver occur or not.  Enhance information content in the images.

The scope of the project is to track the eye positions and monitor the driver’s state also provide the effective system for vehicular network, the images will be smoothened and further classified as open or close eye conditions,  handle image processing or Preprocessing is performed in order to improve the quality. To identify the filters that are used in image processing and the study will be conducted on vehicles.

Final Deliverable of the Project is consist of both hardware and software integrated system.

Hardware components are raspberry pi model B, Buzzer and Arducam camera modules for raspberry pi.

Raspberry pi:

Raspberry Pi is a series of small single-board. Raspberry Pi to learn programming skills, build hardware projects, do home automation, and even use them in industrial applications.

Buzzer:

A buzzer or beeper is an audio signaling device, typical uses of buzzers and beepers include alarm devices, timers, and confirmation of user input such as a driver drowsiness, mouse click or keystroke.

Arducam:

Arducam is one of the first solution providers to offer high performance on Raspberry Pi and has released our MIPI camera product series on the Raspberry Pi.

Software components be made up anaconda platform using python language and libraries.

Libraries are:

 OpenCV: It provides a real-time optimized Computer Vision library, tools, and hardware. It also supports model execution for Machine Learning (ML).

 Dlib:

It is used for face detection and facial landmark detection..

 Numpy:

NumPy offers comprehensive mathematical functions, random number generators, linear algebra routines, Fourier transforms, and more. Interoperable

 Imutils:

A series of convenience functions to make basic image processing functions such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images

 Scipy:

SciPy in Python is an open-source library used for solving mathematical, scientific, engineering, and technical problems. It allows users to manipulate the data and visualize the data using a wide range of high-level Python commands

Final Deliverable of the Project

HW/SW integrated system

Core Industry

IT

Other Industries

Manufacturing , Transportation , Others , Security , Telecommunication

Core Technology

Artificial Intelligence(AI)

Other Technologies

NeuroTech, Others

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