https://github.com/lehuuan1006/security-system
A face recognition-based security camera system for secure access, area monitoring, and camera control using ESP32-CAM
https://github.com/lehuuan1006/security-system
arduino-nano esp32 esp32-cam face-recognition pyqt5 python security-cam-esp32 security-camera-app yolo yolov5
Last synced: about 1 month ago
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A face recognition-based security camera system for secure access, area monitoring, and camera control using ESP32-CAM
- Host: GitHub
- URL: https://github.com/lehuuan1006/security-system
- Owner: Lehuuan1006
- Created: 2024-10-31T02:53:44.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-10-31T04:41:24.000Z (7 months ago)
- Last Synced: 2025-04-06T21:47:40.844Z (about 1 month ago)
- Topics: arduino-nano, esp32, esp32-cam, face-recognition, pyqt5, python, security-cam-esp32, security-camera-app, yolo, yolov5
- Language: Python
- Homepage:
- Size: 81.8 MB
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# **Human Motion Detection and Security Alert System**
This project implements a human motion detection, face data verification, and security alert system using machine vision and IoT technologies. It leverages the ESP32-CAM for real-time monitoring and integrates YOLOv5 for object detection and OpenCV for face recognition, creating a secure and efficient surveillance solution.
## **Project Overview**
With the rise in security concerns, the need for smart surveillance solutions has grown. This system was designed to detect human motion, identify faces from a pre-registered database, and issue alerts to designated users. Key features include real-time streaming, face authentication, motion tracking, and a user-friendly interface for system control. Link [System demo](https://drive.google.com/drive/folders/1Xu5WDIanh8UqaNph10PIVM5tNPEqGjRM?usp=sharing)
## **Features**
- Real-time Human Motion Detection: Utilizes YOLOv5 to detect human presence and capture motion in various environments.
- Face Recognition: OpenCV and face_recognition libraries are used to verify registered faces during system access.
- Remote Camera Control: ESP32-CAM is mounted with a servo system to adjust the viewing angle, enabling flexible monitoring.
- User Management: Allows administrators to add, update, or delete users, ensuring the system remains secure and up-to-date.
## **Technologies**
- Hardware: ESP32-CAM, Arduino Nano, Servo SG90
- Software: PyQt5 for interface, OpenCV, face_recognition, and YOLOv5 for object detection
- Programming Languages: Python (mainly), Arduino IDE for microcontroller programming
## **Usage**
1. Setup: Connect ESP32-CAM to the network and launch the Python application.
2. User Registration: Register users by capturing and encoding their facial data for future authentication.
3. Monitoring: Start live streaming for motion detection; the system triggers alerts and records images upon detecting human presence.
4. Manage Users: Access the control panel to view, update, or remove registered users.
## **Future Development**
Planned improvements include:
- Mobile app integration for remote monitoring
- Enhanced real-time notifications through email or app alerts
- Additional camera support for larger coverage areas