International Journal of Intelligent Defence Support Systems
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International Journal of Intelligent Defence Support Systems (1 paper in press)
IoT Services and Deep Learning Techniques for an On-site Facial Recognition Security System by Amlan Mohanty, Rakesh Kumar Lenka Abstract: Security is a primary concern today for any organization. With the advancement in technology, newer and more effective security systems and solutions are being put to use, making it tougher to breach and easier to manage. The Internet of Things (IoT) is a bridge between machines and the hub of all data the Internet. A potent security model is a real-time Face Recognition system. This research tries to put forth a model of an effective and smart security structure using IoT services and face recognition technology. IoT devices have been used along with the Intel Neural Compute Stick2. Deep Learning and DNN concepts are implemented for the face recognition algorithm for their effectiveness over other algorithms. The Caffe detector is used for localizing faces, followed by creating face embedding by implementing Deep Metric Learning and Triplet Loss concepts. Finally, we have used the Support Vector Machine Classifier for recognizing the faces. Keywords: Internet of Things; Face Recognition; Deep Learning; Deep Neural Network; Face Identification and Security. DOI: 10.1504/IJIDSS.2022.10050575