Smart Car Safety system. Demonstrated during Pragyan '16.

1. Smart Car Safety
System.
Pragyaditya
Pragadeesh
Sananad
Krishna Sathwik

2. Concepts used :
IoT,
Artificial Intelligence,
Image Processing Concepts.

3. Accident Detection
Drowsiness Detection.
Alcohol Sensing.

4. Overview
 This project is to ensure the safety of the drivers
and prevent accidents due to drowsiness.
 There has been a lot of accidents due to drunken
driving.
 Statistics says that the probability of accidents
due to drowsiness increases with increase in age.
 Also as the number of hours of driving increase
the accidents increase exponentially.

5. Modules used:
 ArduinoUNO (MCU).
 GSM SIM900A (SMS Service).
 GPS TinyGPS (Location Sensing).
 CC3200 WiFi module (For accessing Google Maps).
 Ultrasonic Sensor HC-SR04 (Distance Sensor).
 MQ Air Quality Sensor (135 + 33).
 Pi Camera along with RaspPi for Drowsiness
Detection.

6. Two basic blocks…
 Hardware : Distance -> Sense -> Location -> Sense -> SMS.
: Breath -> Low -> Relay ON (Car starts).
Breath -> High -> Relay OFF (Car doesn’t start)
Relay used as an ON-OFF switch
 Software : OpenCV -> Python -> Classification Problem.

7. Prototype Details
It Consists of two sub-systems:-
The first is the Distance detection.
The second is Eye blink detection.

8. Distance and Drowsiness Detection.
 Using an Ultrasonic sensor we detect the vehicles or
object nearby and alert the driver using a buzzer.
 Using an impact sensor we can detect the impact of the
crash and send an SMS.
 The details are sent using GSM module (like blood group
and location of accident). Location is sent using Tiny GPS.
 Three states of your eyes : 0, 1 and 2. We are interested
in the frequency of consecutive Os.

11. Advantages:
 Cheap.
 Modular.
 User-Defined.

12. Disadvantages:
Dependence of Drowsiness Detection
on the ambient luminosity and other
factors.
Lag in initialisation of the GPS module.

13. Further Developments…
 MQ135 Air Quality Sensor and Relay interfacing.
 Better Image Processing for better drowsiness detection.
Use of PARALLEL COMPUTING to lower the cost upto 40%
of initial cost.
 Use of Gray Scale Images to nullify the adverse effects of
radiation.
 Using an accelerometer to detect the head movement.
 Better signal processing for more accurate location.

14. Any Questions?