Futurıstıc Access Control Method To Avoıd Covıd-19 Transmıssıon

Abstract

The current demand of market is to have machine, which can understand human needs as well as support fast lifestyle. It also means that machine should also be supportive to human hygiene which is directly proportional to human health. The paper presents intelligent access control method, which reduces probability of COVID-19 and Swine flu type of disease transmission. These diseases generally transmit from human to human either through direct contact or indirectly via any commonly used touch-based system. Proposed method gives touch free access control which is combination of voice and eye retina-based person identification intelligence. Voice identification logic works on Siamese network and CIFAR network-based architecture and gives 88% test accuracy. Eye retina-based person identification is based on retinal vasculature uniqueness. It is a principle that all humans have different retinal vasculature which can use in person identification. Voice based person identification gives 88% test accuracy but if combined with eye based person identification, it gives complete freedom from touch based access control system and prevents different types of diseases like nCOV(Novel corona virus 19) during office or home access

Keywords: Access Control, Person Identification, Voice Recognition, Speaker Identification, COVID-19, Artificial Intelligence, Swine Flu