Revolutionizing Smart Devices: Integrating Federated Learning with IoT for Advanced Digital Innovation
Sudeshna Dey, Siddhartha Chatterjee, Rituparna Mondal, Ritwika Ghosh · International Journal on Smart & Sustainable Intelligent Computing · 2024
The explosive growth of the Internet of Things (IoT) has transformed the capabilities of smart devices, allowing them to gather and process enormous quantities of data. But as the amount of data grows, serious issues with privacy, security, and bandwidth use surface. Federated Learning (FL), which reduces data transfer, improves privacy, and allows smart devices to work together to create shared models while storing all training data locally, provides a novel solution to these problems. This study looks at the IoT and Federated Learning synergy and shows how it might lead to more advanced digital innovation in smart devices. Through real-time data analysis and localized modifications made by smart devices, FL enhances service efficiency and customisation while protecting customer security and privacy. The suggested solution is assessed in multiple situations, demonstrating its applicability in sectors such as smart homes, healthcare, and industrial IoT. This creative approach will usher in a new era of intelligent transformation that will improve the security, autonomy, and user experience of smart devices