Deep Learning and the Internet of Things
John Byabazaire, Joana Tirana, Andreas Chouliaras, Vlasis Koutsos, Theodoros Aslanidis, Ioannis Panagiotidis, Dimitris Chatzopoulos · 2025
The Internet of Things (IoT) represents a paradigm shift from traditional computing by enabling physical things to communicate over the Internet. IoT devices, from sensors to wearables, produce unprecedented amounts of data that allow better and faster decision-making through analytics. As a result, this has led to innovations in many domains. Due to the enormous volume of data generated, several challenges require advanced techniques such as deep learning (DL). Additionally, as IoT devices collect personal data, concerns about data privacy are rising. Edge intelligence processes data nearer to its source, mitigating latency and bandwidth problems and ensuring data privacy. Moreover, TinyML overcomes the limitations of DL deployment to low-power IoT devices. This chapter explores the integration of DL and IoT to push intelligence closer to data sources, the deployment of DL capable of running on low-powered devices using TinyML, and how digital twins and the metaverse are being leveraged to create virtual environments within the IoT context.