A Survey of IoT Considerations, Requirements, Architectures and Their Potentials for Machine Learning Applications
Rama Krishna Yellapragada, K. Krishna Murthy · 2024
This survey paper presents a comprehensive analysis of IoT considerations, requirements, architectures, and their potentials for machine learning applications. The objective of this study is to explore the relationship between the Internet of Things (IoT) and machine learning, highlighting the crucial role of IoT in enabling advanced data-driven applications. The paper covers various key topics, including connectivity and communication in IoT systems, data collection and processing challenges, and the significance of edge computing and cloud computing architectures. Additionally, it delves into the potentials of machine learning applications in predictive maintenance, anomaly detection, and the development of smart cities. Through this survey, it is evident that the fusion of IoT and machine learning holds immense potential for transforming industries and enhancing quality of life, with implications for optimizing maintenance operations, detecting anomalies, and enabling smarter urban environments.