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In recent years, the Internet-of-Things (IoT) technology is being used in many application areas such as healthcare, video surveillance, transportation etc. The massive adoption and growth of IoT in these areas are generating a massive amount of data. For example, IoT devices such as cameras are generating a huge amount of images when used in hospital surveillance scenarios. Here, face recognition is an important element that can be used for securing hospital facilities, emotion detection and sentiment analysis of patients, detecting patient fraud, and hospital traffic pattern analysis. Automatic and intelligent face recognition systems have high accuracy in a controlled environment; however, they have low accuracy in an uncontrolled environment. Also, the systems need to operate in real-time in many applications such as smart healthcare. This paper suggests a tree-based deep model for automatic face …