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S. Bhuvaneshwari is an Assistant Professor in the Department of Mathematics at K.S.R College of Engineering, Namakkal, Tamil Nadu, India. Her research interests include applied mathematics, optimization techniques, and computational methods. She has contributed to interdisciplinary studies involving AI and intelligent systems.
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.