car safety system

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Smart Car Safety System. Pragyaditya Pragadeesh Sananad Krishna Sathwik

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Post on 13-Apr-2017

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Page 1: Car safety system

Smart Car Safety System.

PragyadityaPragadeesh

SananadKrishna Sathwik

Page 2: Car safety system

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

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Accident Detection

Drowsiness Detection.

Alcohol Sensing.

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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.

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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.

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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.

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Prototype Details

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

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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.

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Advantages:

Cheap. Modular. User-Defined.

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Disadvantages:

Dependence of Drowsiness Detection on the ambient luminosity and other factors.

Lag in initialisation of the GPS module.

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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.

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Any Questions?