Ensuring Real-Time Safety with Raspberry Pi and Machine Learning

This project implements a system for real-time safety monitoring in public areas using a Raspberry Pi and machine learning techniques. It combines face mask detection and non-contact temperature measurement to help prevent the spread of illness.

Features

• Face mask detection with a machine learning model for mask compliance monitoring.
• Non-contact temperature measurement using an infrared sensor.
• Real-time feedback system to indicate mask compliance and temperature readings.

Getting Started

This project requires a Raspberry Pi, a camera module, a non-contact temperature sensor, and software libraries for machine learning and sensor interaction.

Prerequisites:

• Hardware:

  • Raspberry Pi (any model with sufficient processing power)
  • Raspberry Pi Camera Module
  • Non-contact temperature sensor (MLX90614 or similar)

• Software:

  • Python 3
  • Libraries: OpenCV, TensorFlow, NumPy (pre-installation recommended)

📽️ YouTube Demonstration