Implementation of Low Cost IoT Based Intruder Detection System by Face Recognition using Machine Learning
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Abstract
The intruder may enter the premises without the owner’s knowledge. To identify the motion of a person who tries to enter the house will be detected by motion detection sensor. A PIR sensor placed on the door frame, it triggers the USB Camera to capture the person’s image. The captured image is processed to detect face and recognize the image using Machine Learning algorithms and OpenCV. During face recognition, Raspberry pi compares the detected face with the approved pictures kept in the database. Raspberry pi captured 28 images processed per second sends an email to the owner weather authorized or unauthorized. An authentication can be verified by the user via the Internet of Things.
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