A Review: Internet of Things with Machine Learning to Develop Intelligent Systems

Abstract

A fresh era of internet-connected sensing gadgets that bridge the gap between the real and virtual worlds has begun, thanks to the rapid advancements in hardware, software, and communication technologies. About twenty-five and fifty billion internet-enabled gadgets are predicted to be in use worldwide. The term "Internet of Things" is a term used to signify a system of electrical devices that communicate with one another. There is a wide variety of infrastructure, retail, transit, and individual healthcare services and applications made possible by the Internet of Things. IoT is a driving force behind the evolution of the Internet and other forms of modern communication technology. Smart computation and evaluation of massive data are crucial to the growth of Internet of Things applications. IoT applications may benefit from data science tools by discovering new patterns and insights in data. Industry applications of data science with the Internet of Things focus on volume, velocity, and pattern identification. With the help of machine learning's predictive analysis, programs can now anticipate both welcome and unwanted occurrences. Thus, machine learning systems not only identify out-of-the-ordinary conduct but also aid in deducing and predicting broader societal tendencies. Continuing modification and monitoring is necessary for efficacy and effectiveness in data analysis. There are two sections to this article: the first discusses the many uses of the Internet of Things where machine learning plays a role in creating an intelligent system, while the second looks ahead to the potential of IoT and machine learning in the advancement of communication devices. Questions such as "What is the classification of artificial intelligence that can be implemented in IoT?" and "How could machine intelligence be implemented in IoT applications?" will be answered in this article.