Internet of Things (IoT) with deep learning (DL) is drastically growing and plays a significant role in many applications, including medical and healthcare systems. In this paper, we employ Haar Cascade Classifier in an image processing of user face to render the face detection with high accuracy.
The software used is OpenCV Library which is useful to display and process the image produced by webcam. The main control circuit on this system is Raspberry pi. However, if the user is not recognized, then the buzzer will alert. If the user is recognized by the master user, then the solenoid door lock will be opened through the signal sent from the smartphone. Otherwise, the data will be sent to the master user via Android-based smartphone that installed certain applications. If the user has access rights then the solenoid door lock will open and the user can enter the room. Every user detected by the webcam will be checked for compatibility with the database in the system. The system comprises a webcam to detect faces and a solenoid door lock for accessing the room. This paper describes the prototype of a secured room access control system based on face recognition. A vital link in security chain is the identification of users who will enter the room. Security issues are an important part of everyday life.
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