Vehicle Driver Safety System

Project Title

Vehicle Driver Safety System

Project Area of Specialization Electrical/Electronic EngineeringProject Summary

Vehicle driver safety system protects

driver and passengers from accidents

by sensing signs of drowsiness or carelessness. The main aim of this project is

to propose such technique that can

detect the signs of drowsiness or carelessness and make corresponding decisions to make him alert. This project

presents a technique in which the driver will be continuously monitored by a

camera, speedometers, and potentiometer. Moreover, it also assists the driver

with the smart Center Rear View Mirror

that eliminates the need of mirror to be

manually adjusted. Sign detection on

the highways will also be a great feature to our project. 

Project Objectives

Vehicle Driver Safety System mainly

focuses on the safety of the driver. This

project contains five major modules.

The first one is the Driver Drowsiness

detection system which is based on a

technique that not only detects the

drowsiness but also Sprinkles the water

to alert the driver. The second module is

the Traffic sign detection system which

detects the signs and guides the driver

accordingly the concept behind this

module is the transfer learning Technique which is a very efficient method in

Machine learning. The third module is

Rear mirror adjustment which replaces

the conventional way of adjusting the

rear mirror with a new accurate and

reliable automatic adjustment with

memory options so that driver can easily adjust the mirror with one click. The

fourth module is a high beam detection

system that detects the high beam of an

oncoming car and helps the drivers of

both cars to drive comfortably and safely by turning off the beam automatically.

The last module is the steering wheel

detection system which is responsible

for the grip detection of the driver. At

high speed, the car steering is a very

sensitive place and small negligence will

lead to a big accident. 

Project Implementation Method

Nvidia Jetson Nano is used for analyzing the data. The reason for using this

controller is to use two cameras simultaneously. Technique of machine

learning models that are used to train

and test the data include sequential

and inception V3 model.

Sequential Model: For the generation

of single tensor input and output (For

Traffic Sign Detection).

Inception V3 Model: For optimizing the

network for better model adaptation

(For Drowsy Driver System).

Benefits of the Project

The driver safety system will no doubt

facilitate a lot of people on highways.

This whole system will help the driver to

keep its focus on the road to prevent

accidents with the help of its modules

like drowsy driver module, in which PICam will focus on the blinking of an eye.

The steering wheel grip module that will

alert the driver if he/she drives at a

higher speed without having hands on

the steering wheel. The rear-view mirror module which will automatically

adjust itself according to the physical

features such as height of the driver.

The traffic sign detection module that

will facilitate the driver by recognizing

traffic sign boards with the help of PiCam. If all these modules work side by

side, the percentage of accidents in

Pakistan can be minimized. 

Technical Details of Final Deliverable

Nvidia Jetson Nano is used for analyzing the data. The reason for using this

controller is to use two cameras simultaneously. Technique of machine

learning models that are used to train

and test the data include sequential

and inception V3 model.

Sequential Model: For the generation

of single tensor input and output (For

Traffic Sign Detection).

Inception V3 Model: For optimizing the

network for better model adaptation

(For Drowsy Driver System).

Final Deliverable of the Project Hardware SystemCore Industry TransportationOther IndustriesCore Technology OthersOther TechnologiesSustainable Development Goals Good Health and Well-Being for PeopleRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	80000
Nvedia jetson nano	Equipment	1	70000	70000
Hardware body	Miscellaneous	1	10000	10000