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| Title | Empowering Teaching Institutes: Integrating Federated Learning In The Internet Of Things (Iot) Debashree Chakravarty |
|---|---|
| ID_Doc | 22950 |
| Authors | Chakravarty D.; Satpathy I.; Jain V.; Patnaik B.C.M.; Poddar S. |
| Year | 2024 |
| Published | Federated Learning for Smart Communication using IoT Application |
| DOI | http://dx.doi.org/10.1201/9781003489368-11 |
| Abstract | The Internet of Things (IoT) has enabled educators to reinvent instructional methods and create dynamic, efficient, and privacy-preserving learning environments. One of the most transformative and adaptive technologies is the IoT. This paradigm shift allows robots to do complex tasks independently, changing many industries by creating a seamless network of device-cloud communication. Creative applications in healthcare, agriculture, manufacturing, smart cities, and other sectors are enabled by the IoT, a collective network that connects devices and technology. Educational institutions have changed as the world moves from archaic to the IoT. The IoT in education enhances teaching and learning by connecting objects and systems. Smart classrooms with interactive boards, networked devices, and data-driven analytics are becoming increasingly widespread, making education more immersive and engaging. The IoT has several educational uses. In smart classrooms, the IoT allows real-time student–instructor contact, interactive learning, and personalized content based on achievement. Smart learning software and wearable devices make education more dynamic and personalized. Federated learning enhances education. IoT privacy is enhanced using Federated learning, a decentralized machine learning method. It solves centralized model problems by training models on decentralized devices without exchanging raw data. Federated learning in education lets students create customized learning paths, and educators get real-time feedback while securing sensitive data. © 2025 selection and editorial matter, Kaushal Kishor, Parma Nand, Vishal Jain, Neetesh Saxena, Gaurav Agarwal, Rani Astya; individual chapters, the contributors. |
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