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https://github.com/jjateen/esp32-cam-security
The ESP32-CAM Security System (CamVisioTech MK0) is an IoT project that combines facial recognition with smart security features, such as solenoid lock control and real-time alerts via Telegram. Developed during IoT Workshop-1 (ECL 108) Task 4, it includes a custom desktop application for easy management.
https://github.com/jjateen/esp32-cam-security
Last synced: about 11 hours ago
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The ESP32-CAM Security System (CamVisioTech MK0) is an IoT project that combines facial recognition with smart security features, such as solenoid lock control and real-time alerts via Telegram. Developed during IoT Workshop-1 (ECL 108) Task 4, it includes a custom desktop application for easy management.
- Host: GitHub
- URL: https://github.com/jjateen/esp32-cam-security
- Owner: Jjateen
- License: mit
- Created: 2023-07-15T16:38:10.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-01T07:15:29.000Z (16 days ago)
- Last Synced: 2024-11-01T07:26:19.282Z (16 days ago)
- Language: Python
- Homepage:
- Size: 719 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
---
# ESP32-CAM Security System (CamVisioTech MK0)
## Project Overview
This project implements a Face Recognition & Alerting System using the ESP32-CAM module, designed for Task 4 of the IoT Workshop-1 (ECL 108). The system utilizes facial recognition to control a solenoid lock, unlocking the door for 3 seconds when a known person is recognized. If an intruder is detected, the system sends an alert via Telegram and activates a buzzer. Additionally, the system offers a web-based interface for monitoring and control, and a custom desktop application built with Python, Tkinter, and CustomTkinter to manage both the facial recognition and alert system.
---
## Features
- **Face Recognition:** Captures and processes images via the ESP32-CAM and compares them against pre-stored face encodings.
- **Door Control:** Utilizes a solenoid lock controlled via a relay to lock/unlock the door based on successful face recognition.
- **Intruder Alert System:** Sends the intruder’s image to the user’s Telegram account and sounds an alarm if an unauthorized face is detected.
- **Web Interface:** Allows real-time streaming of video feed and control of the door lock and buzzer through a web-based interface.
- **Python-based GUI:** Includes both a high-latency (old-school) and low-latency modern Python GUI for user-friendly system control.
- **Hardware Enhancements:** Includes heat sinks to reduce heat generated by the ESP32-CAM module.
---
## Hardware Components
- **ESP32-CAM Board**: Wi-Fi-enabled microcontroller with an integrated camera.
- **Solenoid Lock (12V)**: Electronic lock controlled by a relay.
- **Relay (5V, 10A)**: Controls the solenoid lock.
- **IC-7805**: Voltage regulator that ensures a constant 5V power supply.
- **Buzzer**: Provides an audible alert in case of an intruder detection.
- **Additional Components**:
- Diode (1N4007)
- NPN Transistor (BC547)
- Resistors (330Ω)
- Capacitor (100μF)
---
## Software Requirements
- **Arduino IDE**: For uploading code to the ESP32-CAM module.
- **Python**: For running the GUI and integrating face recognition.
- Libraries: `opencv-python`, `face_recognition`, `requests`, `tkinter`, `customtkinter`, `numpy`, `Pillow`
- **Telegram Bot**: For sending notifications in case of an intruder alert.
---
## Project Structure
```bash
ESP32-CAM-Security/
│
├── ArduinoSketch/ # Folder for Arduino code
│ ├── debug.cfg
│ ├── debug_custom.json
│ ├── esp32.svd
│ └── finalCamProj.ino # Main Arduino sketch controlling ESP32-CAM
│
├── guiTest.py # Old-school GUI with high latency
├── guiNew.py # Modern GUI with lower latency
├── LICENSE # Project license
├── README.md # Project documentation
├── final_setup.jpeg # Final project setup image
├── ckt.png # Circuit diagram
├── flowchart.png # Flowchart illustrating system process
└── task4.pdf # Project report
```
---
## Setup Instructions
### 1. ESP32-CAM Setup
1. **Install ESP32 Board Manager** in Arduino IDE:
- Go to **File > Preferences** and add the URL:
`https://dl.espressif.com/dl/package_esp32_index.json`
- Go to **Tools > Board > Board Manager** and install the ESP32 package.
2. **Connections**:
- Connect the ESP32-CAM with a TTL programmer.
- Interface the **solenoid lock** with the relay module and connect the ESP32 GPIO to control it.
- Connect the **buzzer** to an ESP32 GPIO pin for intruder alerts.
3. **Upload Code**:
- Use the provided `finalCamProj.ino` file located in the `ArduinoSketch/` directory.
- Set your Wi-Fi credentials in the code:
```cpp
const char* WIFI_SSID = "your_ssid";
const char* WIFI_PASS = "your_password";
```
4. **Access the Web Interface**:
- Once the ESP32-CAM is connected, visit `http:///` to access the video feed and control panel.
### 2. Python GUI Setup
1. **Install Python dependencies**:
```bash
pip install opencv-python face_recognition requests pillow customtkinter numpy
```
2. **Configure the GUI**:
- Modify the `path` in the Python script to point to the folder containing known face images.
- Ensure your ESP32 IP address is correctly set in the GUI for interaction with the hardware.
3. **Run the GUI**:
- Run `guiNew.py` or `guiTest.py` depending on your latency preference.
- The GUI will allow you to monitor the video feed and receive real-time notifications in case of intruder detection.
---
## Circuit Diagram
Here is the circuit diagram showing the connections for the ESP32-CAM, solenoid lock, buzzer, and other components:
---
## Flowchart
Below is the flowchart that illustrates the system's working process:
1. **Start**: The system begins by powering up the ESP32-CAM and initializing the network connection.
2. **Image Capture**: The ESP32-CAM captures the user's face image.
3. **Face Recognition**: The system compares the captured image with stored face encodings.
4. **Match Found**:
- If a match is found, the solenoid lock is triggered to unlock the door for 3 seconds.
5. **No Match**:
- If no match is found, the system identifies the person as an intruder and:
- Sends the intruder’s image via Telegram.
- Activates the buzzer for 1.5 seconds as an alert.
6. **End**: The system returns to the start, ready for the next user.
---
## Final Setup
Below is the image of the final setup of the ESP32-CAM security system:
---
## How It Works
1. **Face Recognition**:
- The ESP32-CAM captures images at regular intervals and sends them to the server.
- The server compares the captured images with pre-stored face encodings to authenticate users.
2. **Intruder Detection**:
- If a face does not match the stored faces, the system triggers an intruder alert.
- An image of the intruder is sent to the user’s Telegram account.
- The buzzer is activated for 1.5 seconds as a local alert.
3. **Web Interface**:
- The web interface allows users to:
- View the real-time camera feed at different resolutions.
- Control the solenoid lock (unlock for 3 seconds).
- Trigger the buzzer manually if needed.
---
## Demo
- [ESP32-CAM Security System (CamVisioTech MK0) Demo](https://www.instagram.com/p/CvfpnTPIu1L/)
---
## References
1. ESP32-CAM Documentation: https://github.com/espressif/esp32-camera
2. Solenoid Lock Guide: https://www.s4a-access.com/dc12v-magnetic-solenoid-lock-for-smart-storage-cabinet_p307.html
3. Face Recognition: https://github.com/ageitgey/face_recognition
---
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
---
By following the setup and usage instructions, you'll be able to deploy a fully functional security system using the ESP32-CAM with both face recognition and intruder alert capabilities.