An Iris+Voice Recognition System for a Smart Doorbell

In this paper, we describe our methodology for designing a smart doorbell system for the homes. While the recent trend of big companies is to offer a home voice assistant, which can integrate all possible services, including the recognition of the owner (or authorized people) at the house door, privacy concerns and independence from a single service provider are requiring more freedom in the choice of the 'smart objects' that surround us. The doorbell system is using both iris and voice recognition to verify the identity of the user who rings at the door. Since there is the involvement of biometric data, this information has to be properly handled. In particular, we designed our system in such a way that it can avoid to send or store any biometric data to the cloud. Machine-learning algorithms are used to perform local computations, thus implementing Edge-Computing analytics to determine the identity of the user, by combining both voice and iris biometrics. The system is implemented on reconfigurable hardware in order to accelerate some of the most intensive tasks and achieve enough performance at a reasonable power consumption. Our tests confirm that, by using our architecture, the performance is about 5x the sequential case and, at the same time, we reach about 7x less energy consumption.