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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 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. (Optional: Add any additional features your project offers)

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:

Raspberry Pi (any model with sufficient processing power) Raspberry Pi Camera Module Non-contact temperature sensor (MLX90614 or similar) Python 3 with libraries: OpenCV, TensorFlow, NumPy (pre-installation recommended)

#Youtube Link for Demonstration of the Project

https://youtu.be/iLSv2P2ss_Y?si=ZzyKeemvTGG4aooZ

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