Open AccessSmart Door controller for handicapped people based on face recognition and voice command technique
Author(s) -
Rana Talib Rasheed
Publication year - 2020
Publication title -
iraqi journal for computer science and mathematics
Language(s) - English
Resource type - Journals
eISSN - 2958-0544
pISSN - 2788-7421
DOI - 10.52866/ijcsm.2019.01.01.03
Subject(s) - facial recognition system , password , biometrics , computer science , android (operating system) , raspberry pi , implementation , phone , keypad , hacker , identification (biology) , face (sociological concept) , lock (firearm) , computer security , face detection , human–computer interaction , embedded system , computer hardware , artificial intelligence , operating system , engineering , pattern recognition (psychology) , internet of things , mechanical engineering , social science , linguistics , philosophy , botany , sociology , biology , programming language
There are a few houses that indicate an application for various implementations, they can indicateall types of systems that direct any door lock as well as many other apparatuses. Facial identification that can beconsidered as a significant section for safety and monitoring, specifically for the handicapped, has the ability to bea way which treats with biometrics and employed for identifying any facial image by employing basic facecharacteristics. A system of face recognition based on Raspberry Pi utilizing recognition mechanisms as well asconventional face detection will be provided. Thus, the approach that image-built biometrics utilizes a RaspberryPi has been depicted. The goal here could be to transfer face recognition towards a level where the system has theability to change RF I-Cards’ use and a password for getting access into all security systems, and reviving thesystem as well as keeping the door safe hacking people, specifically via utilizing an authorized person’s photo, weturn raspberry pi off and do not turn it on just by an order from cell phone of the authorized person. The presentedproposal’s outcome can be a system which utilizes face recognition via employing Raspberry Pi and OpenCV, andit works on Android, and its percentage can be 99.63%. It ought to be secured cost-effective, easy to use and ofhigh performance, that is employed in all applications of smart homes