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To increase safety of entry doors by an IoT-based facial recognition system linked to end user’s smartphones by an application and a real-time database, the project focuses on making a simple and secure IoT-based door entry system using facial recognition.

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team-Dauntless/Entry-Based-Security-System

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Entry-Based-Security-System

Requirements

Functional Requirements:

OpenCV module:
● cascadeClassifier: to detect faces in images using Haar Cascade Frontal Face.
● videoCapture: to read the output of the camera
● cvtColor: to convert images to gray
● imread: to read the images
● LBPHFaceRecognizer: using LBPH machine learning algorithm to train dataset

RandomLightFilter module
● adding filters to images such as addParallelLights, addSpotLights ...

Firebase SDK:
● Pyrebase: it helps to integrate firebase SDK
● initializeApp: to establish the connection to firebase
● Real-time database: to store data and get instant change in project
● Storage: to store all users videos

Crontab
● it’s an operating system function that helps in application scheduling

Non-Functional Requirements

● Videos have to be less than and equal to 10sec and recorded in mobile with vertical alignment
● Model update daily at 9 pm means new user recognize after 9 pm
● All capture images deleted after train the model
● mobile minSDk=29 to install the app
● Model takes 10min to train
● Notification used First-Come-First-Serve basis to grant access
● Raspberry Pi with Wifi, 1Gb ram, webcam

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To increase safety of entry doors by an IoT-based facial recognition system linked to end user’s smartphones by an application and a real-time database, the project focuses on making a simple and secure IoT-based door entry system using facial recognition.

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