Smart room system with dual authentication

This project aims to create a Smart Room System with Dual Authentication, which includes face recognition as the first security layer and a password as the second. This system depends on cloudbased storage, which is Firebase to improve security in a variety of situations. At its center, a Raspberry Pi with a webcam performs face scanning and captures face. A numeric keypad for password entry after face verification, a solenoid sensor for door locking, an LED light that can be controlled remotely via a mobile application, a buzzer for detecting failed attempts, and a DHT11 sensor for humidity and temperature monitoring inside the smart room are all equipment of additional IoT hardware. The face recognition system relies on OpenCV for accurate face detection, capturing face only during system operation, whether a successful or unsuccessful attempt occurs. It uses the Histogram of Oriented Gradients (HOG) algorithm for face recognition, which results in lower power consumption and faster processing. Captured face are also stored in Firebase Storage for cloud access, while the Raspberry Pi sends a copy to the administrator via email with attempt details as a notification. In addition, a mobile application enables the administrator to monitor the door lock state either locked or unlocked, temperature, humidity, and LED light status either on or off, as well as change the LED light remotely. This project demonstrates the seamless combination of hardware and software in order to develop a Smart Room that improves security, savings on energy, and user simplicity