Paper Title
Indoor Location Tracking Using Iot and Deep Learning

Abstract
In the rapidly evolving landscape of educational institutions, the efficient management of campus resources and the safety of students and faculty have become paramount concerns. This review paper examines the "EduLocation," a ground-breaking initiative that employs deep learning, the Internet of Things (IoT), and real-time data analytics to build an intelligent and dynamic campus environment. This paper aims to provide a comprehensive overview of the latest advances in indoor positioning, occupancy monitoring, and campus management systems, with a focus on the creative contributions of the "EduLocation" project. This survey article classifies and examines numerous technologies, approaches, and trends in the field through a careful examination of recent research and advances. The main points discussed are IoT-based user interfaces, cloud infrastructure, facial recognition systems, occupancy monitoring methods, and indoor positioning technology. This project is positioned in this paper's context of upcoming trends and difficulties in the industry in addition to evaluating the benefits and drawbacks of current solutions. Keywords - Indoor positioning, IoT based tracking, GPS, IndoorAtlas, Facial recognition, Deep learning, CNN, Facial recognition, Real-time location information.