iot based drivers fatigue monitoring system using machine learning6051

A dataset of various drivers while driving will be adopted and considered to be classified according to condition of a driver. Usual classes of a driver while driving a vehicle include normal, happy, tired or sleepy. To detect the severity, we use machine learning based video classificat

Project Title

Project Area of Specialization

Internet of Things

Project Summary

A dataset of various drivers while driving will be adopted and considered to be classified
according to condition of a driver. Usual classes of a driver while driving a vehicle include
normal, happy, tired or sleepy. To detect the severity, we use machine learning based video
classification model. The machine learning method detects, in which condition currently a
driver is. This information can be used to alert the authorities and nearby vehicles to handle the
situation when the driver is feeling sleepy. It can help to avoid the accidents and big damage.
We will be using neural network model to extract the features in a video and recurrent neural
network method to classify the videos accordingly.

Project Objectives

TO MONITOR THE DRIVER’S FATIGUE USING IOT

AN AUTOMATED SYSTEM

Project Implementation Method

The emergence of artificial intelligence and the rapid development of electronic and
information technology provide more opportunity to detect driver fatigue using machine
learning approaches. Deep learning is proving to be a very helpful in every field of life of
humans to provide easy and accuracy simultaneously. There is a need to promote road safety
as well using machine learning.
Problem Statement:
Road safety is becoming a big concern as we move toward a technological world. Drivers health
is necessary to be checked during driving not only to protect others with but outside a vehicle.
So, it is crucial to promote the technologies for detecting driver fatigue.
Proposed Methodology:
A dataset of various drivers while driving will be adopted and considered to be classified
according to condition of a driver. Usual classes of a driver while driving a vehicle include
normal, happy, tired or sleepy. To detect the severity, we use machine learning based video
classification model. The machine learning method detects, in which condition currently a
driver is. This information can be used to alert the authorities and nearby vehicles to handle the
situation when the driver is feeling sleepy. It can help to avoid the accidents and big damage.
We will be using neural network model to extract the features in a video and recurrent neural
network method to classify the videos accordingly.

Benefits of the Project

Drivers' fatigue monitoring.

less mishaps.

Save deaths

Automatic handling of vehicle

save passengers

Technical Details of Final Deliverable

Automated system

managed vehicle

AI based implementations

Auto controlling

auto messaging

Alarm generation

Final Deliverable of the Project

HW/SW integrated system

Core Industry

IT

Other Industries

Core Technology

Internet of Things (IoT)

Other Technologies

Sustainable Development Goals

Industry, Innovation and Infrastructure, Life on Land

Required Resources

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