IoT Architecture for Smart Systems: A Data-Driven Approach to Machine Learning and Analytics
Mohammed Abdullatif Abdulhadi Alsayed · International Journal of AI BigData Computational and Management Studies · 2023
The Internet of Things (IoT) has revolutionized the way we interact with technology, enabling the seamless integration of physical and digital systems. This paper presents a comprehensive data-driven approach to IoT architecture for smart systems, focusing on the integration of machine learning and analytics. We explore the various layers of the IoT architecture, including the perception, network, and application layers, and discuss how data-driven techniques can enhance the efficiency, reliability, and intelligence of IoT systems. The paper also delves into the challenges and opportunities presented by data-driven IoT, and provides a detailed case study to illustrate the practical implementation of the proposed architecture. Finally, we present an algorithm for optimizing data processing in IoT environments and discuss future research directions