An IOT based System to Keep The Drowsy Driver Awake

Project Title

An IOT based System to Keep The Drowsy Driver Awake

Project Area of Specialization Software EngineeringProject Summary

Road accidents are usually caused by driver carelessness. The major carelessness exhibited by the driver are drunken behavior and negligence. The driver drowsiness detection system in automotive vehicle focuses on abnormal behavior exhibited by the driver using a microcontroller, the Raspberry pi single board computer. In the proposed system a non-intrusive driver drowsiness monitoring system has been developed using computer vision techniques. Irrespective of driver wearing spectacles and darkness level inside the vehicle, the system is able to detect the drowsiness. The system will detect drowsiness within the time duration of about two to three seconds. The driver is alerted through alarms in real time.

Project Objectives

The purpose of the drowsiness detection system 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. This device will not, however, guarantee that the driver will be fully awakened and that an accident will be avoided. It is simply a tool for improving driver safety; focusing primarily on long-haul truck drivers, nighttime drivers, people driving long distances alone or people suffering from sleep deprivation.

Project Implementation Method

To analyze different behavioral or visual-based attitudes of the driver, face movement and eye blink are measured to study the state of the driver. Here, eye blink is mainly focused to detect drowsiness of the driver. The threshold value of an EAR lies above 0.25 without any effect of exhaustion. When a driver automatically shuts down, then the threshold value of EAR falls below the given range. A threshold value of drowsy eye blink sample represents the number of video frames of the driver’s closed eyes. If the consecutive counting frames increase above the range of the threshold value, then the drowsiness of the driver is detected. Here, a Pi camera is used to regularly record the total movement of an eye through which the threshold value of an EAR is calculated. A counter is also included in it for counting occurrence of frames. Suppose that it exceeded above a range of 30. In that case, a voice is activated by a speaker and a mail is automatically sent to an authorized person of the vehicle which is generally processed at the time of drowsiness detection. The described modules work properly through Raspberry Pi3 which is programmed in Python programming language. 

Benefits of the Project

The drowsiness detection system is capable of detecting drowsiness in quickly. The system which can differentiate normal eye blink and drowsiness can prevent the driver from entering the state of sleepiness while driving. The system works well irrespective of driver wearing spectacles and under low light conditions also. During the monitoring, the system is able to decide if the eyes are closed or opened. When the eyes have been closed for too long a warning signal is issued. The ultimate goal of the system is to check the drowsiness condition of the driver. Based on the eye movements of the driver, the drowsiness is detected and according o eye blink, the alarm will be generated to alert the driver and to reduce the speed of the vehicle along with the indication of parking light. By doing this, many accidents will be reduced and provides safety to the driver and vehicle.

• The detected abnormal behavior is corrected through alarms in real time.

 • Component establishes interface with other drivers very easily.

• Life of the driver can be saved by alerting him using the alarm system.

• Speed of the vehicle can be controlled. • Traffic management can be maintained by reducing accidents

. • Practically applicable

.This system can be used in factories to alert the workers

. • If found drowsy, the alarm system gets activated and the driver is alerted.

Technical Details of Final Deliverable

In this project we are focusing on detecting the drowsiness of driver using Raspberry Pi 4.we are focusing on a driver drowsiness detection system in automotive vehicles. The driver behaviour is noticed in many conditions such as wearing spectacles and also in the dark condition inside the vehicle. The proposed system will be continuously monitoring the retina of the driver and all the monitored signals are sent to the microcontroller. The system is capable of detecting the drowsiness condition within the duration of more than two seconds. After the detection of abnormal behaviour it is alerted to the driver through alarms and the parking lights will be on that will stop the vehicle which reduces the accidents due to drowsiness of the driver.

Final Deliverable of the Project Hardware SystemCore Industry ITOther Industries Others Core Technology Internet of Things (IoT)Other Technologies Artificial Intelligence(AI)Sustainable Development Goals Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	72950
Raspberry Pi 4 Model B 8GB	Equipment	1	41000	41000
Pi Camera B+	Equipment	1	6000	6000
Crash Sensor	Equipment	1	3000	3000
32 GB SanDisk Ultra Class 10 Sd card with sd card reader	Equipment	1	3000	3000
GPS Module	Equipment	1	2000	2000
Speaker	Equipment	1	500	500
Force Resistive Sensor	Equipment	1	1500	1500
Simulator	Miscellaneous	1	6000	6000
Convince Charges	Miscellaneous	1	2500	2500
5V 3A Raberry Pi 4 Charger	Equipment	1	450	450
GSM Services	Equipment	1	7000	7000