Face Count System & Buzzer Alert System

Project Overview

This project involves a distributed system using ESP32 modules to stream video, detect and count human faces, and trigger a buzzer when a set face count limit is reached. The system consists of three main components:

• ESP32-CAM Module: Streams live video.
• Face Detection Server: Processes the video stream to count faces.
• Pocket ESP32 Module: Receives face count updates, shows it on an LED, and triggers a buzzer in real-time.

How It Works

• Video Streaming: The ESP32-CAM captures and streams live video to the Face Detection Server.
• Face Detection: The Face Detection Server processes the stream using face detection algorithms and counts the number of faces.
• Real-Time Updates: The Pocket ESP32 Module receives face count data and triggers the buzzer based on predefined conditions.

Technologies Used

• ESP32-CAM Module: For video capture and streaming.
• OpenCV: For face detection and image processing.
• Python/Node.js: For the Face Detection Server implementation.
• MQTT/HTTP: For communication between the Face Detection Server and Pocket ESP32 Module.
• Raspberry Pi/Computer: To run the Face Detection Server.

Project Components

ESP32-CAM (Video Stream)

Function: Streams live video feed.

• Endpoints: / (provides video stream)
• Controls: Start Stream (starts video streaming)

Pocket ESP32 Module (Buzzer + LED Control)

Function: Controls buzzer and LED based on face count.

• Endpoints: /on, /off, /update_count
• Controls: Turn On/Off (toggles buzzer and LED)

Flask Face Count Server

Function: Processes video stream, performs face detection, and tracks faces.

• Endpoints: /video_feed (provides video feed with face detection), /counts (returns count of detected faces)
• Web Interface: Real-time video feed and face count updates

Setup Instructions

ESP32-CAM Configuration

• Update Wi-Fi credentials and upload the code via Arduino IDE.
• Ensure the camera stream is accessible via HTTP.

ESP32 Server Configuration

• Update Wi-Fi credentials and upload code via Arduino IDE.
• Controls the buzzer and LED based on face count updates.

Flask Server Setup

• Install required Python packages (Flask, OpenCV, MediaPipe, Requests, etc.).
• Run python server.py to start the Flask server.
• Access the web interface

Controls

• ESP32-CAM: Power on the camera module and connect via IP address to view the live feed.
• ESP32 Server: Send HTTP requests (/on, /off) to toggle the buzzer and LED. Check the serial monitor for the assigned IP.
• Flask Server: Monitor the live video feed and face count updates via the web interface or IP address.