Drowsiness Detection using Raspberry Pi and GSM Module

#raspberrypi #vehiclesafety #engineeringproject

#engineeringproject #capstone Project #major Project
for EEE ECE, Engineering project, Science Exhibition project


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This Project employs image processing techniques and machine learning algorithms to analyze the captured images in real-time. When drowsiness is detected, the system can trigger alerts and SMS notifications through GSM, to alert the person and potentially prevent accidents, especially in scenarios like driving. This system provides an innovative and cost-effective solution for enhancing safety in various contexts.

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1. Synopsis/ Documents
2. Block diagram and circuit diagram with explanation.
3. Bill of material.
4. Components Specification list
5. Working principle of the project.
6. Datasheet of all components.
7. Program/code of Arduino with training.
8. Complete Working principle description.
9. Complete interfacing description.
10. you can get the project by courier.
11. viva preparation
ask us if other things needed.

Description

This project uses a 7805 voltage regulator to power a Raspberry Pi and connected components. The Raspberry Pi runs Python code to manage a USB camera that monitors the driver for signs of drowsiness. Two LEDs indicate system status: one for normal operation and another for detecting drowsiness. If drowsiness is detected, the system stops a DC motor, sends an emergency alert via a GSM module to the driver's relatives, and activates a buzzer for an audible alarm, ensuring immediate notification and response


Objectives

• To utilize a USB camera to continuously capture and analyse live video footage of the driver to detect signs of drowsiness.

• To implement real-time analysis of the driver's eye status to identify drowsiness. Activate visual (LEDs) and audible (buzzer) alerts to notify the driver and others when drowsiness is detected.

• To integrate a GSM module to send emergency alerts to the driver’s relatives if drowsiness is detected, ensuring timely intervention.

• To improve overall driver safety by combining real-time monitoring, automated responses, and emergency alerts to address drowsiness effectively.


Components required

Raspberry Pi (Microcontroller) (5V / 3A)
7805 regulator (6-36V / 1A)
Battery (12V / 1.5Ah)
Usb camera (5V / 200 mA)
Buzzer (5V / 10 mA)
LED 16X2 (5V / 1 mA)
GSM module (4V / 2A)

Methodology

Drowsiness detection using the Raspberry Pi system begins with supplying power to the entire circuit, where a 7805-voltage regulator steps down the battery voltage to a stable 5V, crucial for powering the electronic components. Once the system is powered, the Raspberry Pi boots up and starts executing its programmed Python code. A USB camera, connected to the Raspberry Pi, continuously captures live video footage of the driver. Two LEDs are incorporated into the system: one serves as an indicator for normal operation, glowing when all components are functioning correctly, while the second LED lights up to signal when drowsiness is detected based on the camera's observation of the driver's closed eyes. Simultaneously, a DC motor, controlled by an L293D motor driver, will stop its movement. A GSM module sends an emergency alert message to the driver's number. A buzzer emits a loud alarm sound, providing an audible alert of the detected drowsiness.


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