Unleashing IoT Data Insights: Data Mining and Machine Learning Techniques for Scalable Modeling and Efficient Management of IoT

Abstract

This chapter explores the era of unprecedented data creation propelled by the widespread adoption of internet of things (IoT) devices. The massive and diverse IoT data, while holding advantages, necessitates data mining and machine learning techniques to unveil concealed insights. Focusing on the integration of these techniques, the research explores scalable modeling and effective administration of IoT applications. It navigates through the challenges of scalability, data complexity, real-time processing, and security concerns within IoT data. The chapter emphasizes the necessity of feature engineering, data preparation, and model selection tailored to IoT data's particularities. By incorporating IoT capabilities for data gathering, real-time streaming, and comprehensive data analysis, the research promotes efficient handling of IoT data, fostering a new era of productivity and creativity. The findings contribute to the evolving landscape of IoT applications, presenting a roadmap for data-driven decision-making and enhanced operational efficiency.