Energy-efficient Face Recognition Authentication System Using Human Detection IoT Modules

The application of effective techniques like facial recognition and object detection in the domain of IoT has revolutionized the levels of control and accuracy sensors have had for a variety of purposes. Face recognition modules have established their immense usefulness, and their impact has overweighed most other traditional forms of access control. It remains one of the most secure methods to authenticate human beings to grant them access to restricted areas or systems in an organization. However, this incomparable rise in accuracy comes with a relatively huge price. The algorithms used in facial recognition are complex mathematical functions that are iteratively performed on vast volumes of data continuously. In IoT applications, the embedded systems that run these algorithms are at all times clocked to their maximum processing power, they need not run in cases when there are no humans are present in the vicinity. This is inefficient, especially in systems that need to perform face recognition round-the-clock for authentication. This paper proposes a simple, intuitive and efficient solution to conserve the processor from being clocked to its maximum throughput without compromising on the high level of security that the face recognition algorithm offers.