Artificial Intelligence-Powered Contactless Face Recognition Technique for Internet of Things Access for Smart Mobility

被引:0
作者
Hiremani, Nirmala [1 ]
Hasan, Mohammad Kamrul [2 ]
Basavaraju, T. G. [3 ]
Islam, Shayla [4 ]
Alboaneen, Dabiah [5 ]
Alkayal, Entisar [6 ]
Alharbi, Nesreen M. [7 ]
Mansor, Zulkefli [2 ]
Amanlou, Sanaz [2 ]
机构
[1] Visvesveraya Technol Univ, Dept Comp Sci & Engn, Belagavi, Karnataka, India
[2] Univ Kebangsaan Malaysia, Fac Informat Sci & Technol, Bangi, Malaysia
[3] Govt Engn Coll, Dept Comp Sci & Engn, Hassan, Karnataka, India
[4] UCSI Univ, Inst Comp Sci & Digital Innovat, Kuala Lumpur 56000, Malaysia
[5] Imam Abdulrahman Bin Faisal Univ, Dept Comp Sci, Coll Sci & Humanities, POB 31961, Dammam, Saudi Arabia
[6] King Abdulaziz Univ, Fac Comp & Informat Technol Rabigh, Dept Informat Technol, Rabigh 21911, Saudi Arabia
[7] King Abdulaziz Univ, Fac Comp & Informat Technol Rabigh, Dept Informat Syst, Rabigh 21911, Saudi Arabia
关键词
IOT;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A contactless system became necessary for smart mobility during the COVID-19 pandemic. There are many touchpoints in private and public areas where contact is essential, such as intelligent transportation systems for vaccine carriers, patient ambulances, elevators, metros, buses, hospitals, and banks. A secured contactless device reduces the chances of COVID-19 infection spread. Several devices use smart cards, fingerprint identification, or code-based access. Most of these devices require some form of touch. The cost of such devices varies, depending on their capability and intended use. Sensors developed by using artificial intelligence (AI) to provide secured access are an emerging area. This paper presents an AI-powered contactless face recognition system. The solution has the Internet of Things (IoT) enabled access system. To identify a person, it uses AI assistance for face recognition with the help of Python Dlib's facial recognition network. Dlib offers a wide range of functionality across several machine learning sectors and is open-source. The Arduino Uno (ATmega328P) and STK500 protocol has been used for communication to testify and validate the performance of the proposed technique. The objective is to detect and recognize faces by the proposed contactless approach. The obtained result shows 92% accuracy, 94% sensitivity, 96% precision and FRR 6% for face detection. There is a significant improvement in FRR in our work compared to the published 27.27%. The implemented solution in this paper provides accurate and secure contactless access to conventional, readily available techniques in public health safety.
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页数:11
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