Smart door for handicapped people via face recognition and voice command technique

Joint Authors

Salman, Hana M.
Rashid, Rana T.

Source

Engineering and Technology Journal

Issue

Vol. 39, Issue 1B (31 Jan. 2021), pp.222-230, 9 p.

Publisher

University of Technology

Publication Date

2021-01-31

Country of Publication

Iraq

No. of Pages

9

Main Subjects

Electronic engineering

Topics

Abstract EN

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 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.

American Psychological Association (APA)

Salman, Hana M.& Rashid, Rana T.. 2021. Smart door for handicapped people via face recognition and voice command technique. Engineering and Technology Journal،Vol. 39, no. 1B, pp.222-230.
https://search.emarefa.net/detail/BIM-1282632

Modern Language Association (MLA)

Salman, Hana M.& Rashid, Rana T.. Smart door for handicapped people via face recognition and voice command technique. Engineering and Technology Journal Vol. 39, no. 1B (2021), pp.222-230.
https://search.emarefa.net/detail/BIM-1282632

American Medical Association (AMA)

Salman, Hana M.& Rashid, Rana T.. Smart door for handicapped people via face recognition and voice command technique. Engineering and Technology Journal. 2021. Vol. 39, no. 1B, pp.222-230.
https://search.emarefa.net/detail/BIM-1282632

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references : p. 230

Record ID

BIM-1282632