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Journal ArticleDOI

Smart Door for Handicapped People via Face Recognition and Voice Command Technique

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TLDR
The aim of the paper here can be considered as transferring face recognition to a level in which the system can replace the utilizing of RF ICards and a password to access any system of security and making the system alive and protect the door from being open by hackers.
Abstract
Smart home indicates an application for different technological implementations, it could indicate any system which controls the door lock and several other devices. Facial identification which is an important section to achieve surveillance and safety, especially for handicapped people, can be considered as one of the ways that deal with biometrics and performed to identify facial images via utilizing fundamental features of the face. A Raspberry Pi-based face recognition system using conventional face detection and recognition techniques is going to be supplied, so the method in which image-built biometrics uses a Raspberry Pi is described. The aim of the paper here can be considered as transferring face recognition to a level in which the system can replace the utilizing of RF I-Cards and a password to access any system of security and making the system alive and protect the door from being open by hackers, especially by using the picture of an authorized person, we make the raspberry pi turn off and cannot turn on only by a command from the authorized person's mobile. The result of the presented proposal is a system that uses face recognition by utilizing OpenCV, Raspberry Pi, and it functions on an application of Android, and this system percentage becomes 99.63%. It should be cost-effective, of high performance, secured, and easy to use, which can be used in any smart home application.

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Citations
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Journal ArticleDOI

Survey of intelligent surveillance system for monitoring international border security

TL;DR: In this paper, an automated vehicle with a monitoring system on the basis of face recognition and detection algorithms, the human presence is checked via the system which after that runs the algorithm for face recognition.
Proceedings ArticleDOI

Alert Intruder Detection System Using Passive Infrared Motion Detector based on Internet of Things

TL;DR: This study offers a prototype for an Internet of Things-based home intruder detection system that can do daily motion detection work automatically and examines several choices for each attribute, including aspects of passive infrared motion detector works that suggest unique methods for home invader motion detectors on the Internet of things.
References
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Proceedings ArticleDOI

Rapid object detection using a boosted cascade of simple features

TL;DR: A machine learning approach for visual object detection which is capable of processing images extremely rapidly and achieving high detection rates and the introduction of a new image representation called the "integral image" which allows the features used by the detector to be computed very quickly.
Journal ArticleDOI

Robust Real-Time Face Detection

TL;DR: In this paper, a face detection framework that is capable of processing images extremely rapidly while achieving high detection rates is described. But the detection performance is limited to 15 frames per second.
Proceedings ArticleDOI

Robust real-time face detection

TL;DR: A new image representation called the “Integral Image” is introduced which allows the features used by the detector to be computed very quickly and a method for combining classifiers in a “cascade” which allows background regions of the image to be quickly discarded while spending more computation on promising face-like regions.
Proceedings ArticleDOI

Real-time emotion recognition from facial images using Raspberry Pi II

TL;DR: A method for real time emotion recognition from facial image using Haar cascade, features extraction, Active shape Model, and Adaboost classifier for classification of five emotions anger, disgust, happiness, neutral and surprise is proposed.
Proceedings ArticleDOI

A Smart Home Appliance Control System for Physically Disabled People

TL;DR: This paper presents a system that uses smart plugs, smart cameras, smart power strips and a digital assistant such as Amazon Alexa, Google Home, Google Assistant, Apple Siri, or Microsoft Cortana to capture voice commands, from a person with physical disabilities, spoken in a much more natural way to control ordinary home electrical appliances in order to turn them on or off, with minimal exertion.
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