Why this course?

Description

Raspberry Pi platform in embedded systems, IoT, and automation applications. Learners will acquire hands-on experience in sensor interfacing, GPIO control, Python scripting, and real-time project development.

Learning Outcomes

• Understand Raspberry Pi hardware and setup
• Use Python to interface and control sensors and actuators
• Build mini-projects involving real-time data, PWM, and sensor feedback
• Set up web servers, send automated alerts, and integrate with cloud or LAN systems

Daily Breakdown

• Day 1: Introduction to Raspberry Pi and Installation Process (Presentation)
• Day 2: Complete Guide to Raspberry Pi 4 GPIO Pins (Presentation)
• Day 3–4: Python Programming with Raspberry Pi (Presentation)
• Day 5: Controlling GPIOs via Python (Presentation)
• Day 6: Sensor Interfacing with Raspberry Pi 4 (Presentation)
• Day 7: MPU6050 Gyro Sensor Interfacing (Presentation)
• Day 8: PWM Signal Generation via Python (Presentation)
• Day 9: DC Motor Control via Python on Raspberry Pi (Presentation)
• Day 10: BME280 Sensor – Temperature, Humidity, Pressure (Presentation)
• Day 11: RFID Authentication System (Presentation)
• Day 12: Weather Reporting System (Presentation)
• Day 13–14: LCD Interfacing and Programming with Python (Presentation)
• Day 15: Sending Email with SMTP from Raspberry Pi (Presentation)
• Day 16: Motion Detection with Email Alerts (Presentation)
• Day 17: LAMP Server Setup (Apache, MySQL, PHP) (Presentation)
• Day 18: ESP32/ESP8266 Data Publishing to Raspberry Pi (Presentation)
• Day 19: Mosquitto MQTT Broker Installation (Presentation)
• Day 20: Pi Camera Module Interfacing with Python (Presentation)
• Day 21: Basic Linux Commands (Presentation)

Project Sessions

• Drowsiness Detection System
• Eyeblink-Controlled Wheelchair
• Face Mask Detection
• Fire Detection System
• Automatic Number Plate Recognition
• Smart Surveillance System
• Smart Voting System

Section 6: Internship Report Guidelines

Report Structure

Title Page

• Student details, mentor, project title

Abstract

• One-paragraph summary

Introduction

• Scope and purpose of the internship

Modules Covered

• Summary of tools and techniques

Case Studies and Projects

• Problem, implementation, outcomes

Insights and Learnings

• Tools mastered, challenges overcome

Conclusion

• Future applications of skills

References

• Cited datasets, libraries, documentation

Appendices

• Screenshots, code samples, charts