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Mrs. Agamani Chakraborty is associated with the Department of Electrical Engineering at Asansol Engineering College, West Bengal, India. Her academic interests include IoT systems, automation, embedded technologies, and smart monitoring systems. She is actively involved in teaching and research activities related to intelligent engineering applications.
AI-driven smart attendance systems utilising facial recognition and Internet of Things (IoT) devices are revolutionising conventional attendance management into automated, precise, and frictionless procedures. This chapter examines the amalgamation of computer vision, deep learning, and IoT technologies to develop intelligent attendance systems that provide real-time identification and data collecting. Facial recognition methods, including Convolutional Neural Networks (CNNs) and deep metric learning techniques, provide reliable detection and verification of persons, whilst IoT devices offer efficient data collecting, communication, and storage. The chapter delineates a comprehensive system architecture that amalgamates cameras, embedded devices, edge computing modules, and cloud platforms to guarantee scalability and efficiency.