Edge-Driven Biometrics and Facial Recognition for Virtual Assistant
H. M. Ramalingam, Mohamed Fazil, M. Pallikonda Rajasekaran, R. Kottaimalai, Vishnuvarthanan Govindaraj, T. Arunprasath · 2023
In modern society, time is essential. Recent advances in technology have accelerated the emergence of assistance systems for individuals in their everyday lives. Quick and correct information at the right time needs computerization. In the existing voice assistants, the proper authentication of the user for security purposes is not precise. Inculcating the face and voice biometrics will add up security for the system. To ensure each user’s data and personal information is properly maintained, we provide Multifactor authentication. Also, a lot of time is spent on tedious repetitive tasks which can be reduced by using a virtual assistant. This paper presents a combination of different technologies like Edge driven biometrics, Computer vision, and Machine Learning. The model was designed and developed for both personal mode and general mode. Usability testing was carried out for several use scenarios in order to assess performance.