GT ECE4180 Fall2019 Final Project

By: Shruti Ramanathan and Jeffrey Jacob

Motivation

Being safe and aware when driving is a critical problem for drivers on the road. With busy schedules and the easy of multi-tasking with technology, it is increasingly important that drivers who are feeling tired, sleepy, or disrupted on the road have the appropriate measures taken to make sure they are alert regardless. As our final project, we wanted to use eye-tracking technologies to warn and caution a driver when they need the extra help to stay awake at the wheel and make it home safely.

Block Diagram

Demo

Key Features

• Eye-tracking and detection using Computer Vision (CV) via Webcam monitoring for us to identify if the driver's eyes are in the appropriate range of activity for steady driving
• Risk score calculation to identify how at risk the driver is of getting into an accident
• Text alert sent to family/friend from Emergency Contact to provide an update of risk
• Audio alerts to awaken the driver
• Visual cues provided with LCD screen changes to indicate security of driver
• LED blinking as a function of risk

Technologies in Action

Computer Vision

Twilio

We used Twilio to send SMS text message notifications to family members or loved ones that wanted a status on a driver who may be at risk of falling asleep at the wheel.

Parts Used

uLCD

Speaker and Audio Amp

Raspberry Pi 4

Webcam

LED

Demo Implementation/Code

Wheel Awake Pi Code: https://github.com/jjacob35/ece4180_FinalProject