Raspberry-Pi Based Surveillance Robot.ppt
This presentation showcases our undergraduate minor project titled “Raspberry Pi-Based Surveillance Robot”, developed as part of the 5th semester coursework in the Department of Electrical and Electronic Engineering, University of Chittagong. The robot is designed to perform real-time facial recognition, motion detection, and automated email alerts using Raspberry Pi 4, Pi Camera, and Python-based computer vision libraries. When an unknown face is detected, the system captures an image and sends it to the user via email. The robot is also mobile, allowing for remote surveillance using Bluetooth control. Core Features: - Face recognition using pre-trained CNN models - Email alerts with image attachments upon detecting intruders - GPIO-controlled hardware activation - Bluetooth-based mobility (Arduino + HC-05) This project integrates computer vision, embedded systems, and IoT for a cost-effective and scalable security solution. We gratefully acknowledge the support of our faculty mentors and hope this inspires other students working on smart surveillance or robotics projects.
Raspberry-Pi Based Surveillance Robot.ppt
- 2. A Project Presentation By Group: 07 1. Md. Rased Khan 2. Shakib Hossain Faysal 3. Jannatul Ferdous 4. Afia Farzana ID: 22702031 ID: 22702025 ID: 22702053 ID: 22702018 Under The Supervision of Dr. Md. Fazlul Kader Professor Dept. of EEE, University of Chittagong Sadia Sultana Assistant Professor Dept. Of EEE, University of Chittagong Project Name: Raspberry-Pi Based Surveillance Robot Course Code: CSE-518 Course Name: Laboratory on Computer Networks
- 3. INTRODUCTION • This project details a Raspberry Pi-based surveillance robot for enhanced security • Offers continuous monitoring using a PIR sensor for motion detection and a camera for capturing video • Facial recognition identifies known individuals and flags unknown ones, triggering email alerts with images • Integrates embedded systems, computer vision, and IoT for a practical security solution
- 4. MOTIVATION Modern security requires smart, affordable, and proactive solutions. This project fulfills that by offering intelligent Raspberry-Pi based system, real-time threat detection and instant user alerts, significantly boosting security. Features CCTV Camera System Raspberry-Pi Surveillance Robot Monitoring Passive, Continuous video storage Active, Real-time face detection and alert Intelligence Manual review required Face recognition, Email alerts Mobility Fixed Can patrol or be remotely moved Alerts No real-time notification Instant email alerts with intruder image Cost High due to NVRs and storage Low How does it differ from traditional CCTV Camera System?
- 5. OPERATION STEPS 1. Motion Detection: A PIR sensor detects human presence, triggering the system. 2. Image Capture: The Pi Camera module captures live video frames. 3. Face Recognition: A deep learning-based algorithm processes frames to recognize known individuals and identify unknown ones. 4. Hardware Control: GPIO pins can control external devices (e.g., LEDs/buzzers) for physical responses. 5. Email Alerts: Upon detecting an unknown person, the system captures an image and sends an email alert with the photo attached. 6. Mobility: Deployed on a soccer bot chassis, allowing for both manual and autonomous surveillance.
- 7. RESULT • System accurately recognized authorized and identified unknown faces. • Successfully sent email alerts with image attachments upon detecting unknown individuals. • Face detection accuracy was best in well- lit environments. • System effectively used face distance thresholds to prevent false positives. • Achieved sufficiently low response time for real-time monitoring. • Successfully deployed on a soccer bot chassis for both manual and autonomous surveillance capabilities.
- 8. COST-ANALYSIS Components Costs Raspberry-Pi Module 4500 Taka Pi Camera Module 750 Taka Carrying Bot 2500 Taka HDMI Cable 150 Taka PIR Sensor 100 Taka Low cost and affordable setup
- 9. This project offers significant scalability due to its modular and open-source architecture. - additional sensors (e.g., temperature, sound, or gas) - more advanced AI models for object detection - cloud-based remote monitoring can be easily integrated without major hardware changes. SCALABILITY - multiple units can be networked together for coordinated broad-range surveillance - improvements like solar-powered charging or 5G connectivity can extend its range and autonomy making it suitable for diverse future security applications in homes, campuses, or industrial sites.
- 10. REFERENCES • Face Recognition with Raspberry Pi and OpenCV, Core Electronics, 2024. • Real-Time Face Recognition: https://medium.com/data-science/real-time-face-recognition-an-end- to-end-project-b738bb0f7348 • Python GPIO Zero Documentation: https://gpiozero.readthedocs.io • Raspberry Pi Documentation: https://www.raspberrypi.com/documentation/ THANK YOU!