Smart IoT Using Data Mining Techniques

Abstract

Data mining process refers to the process of semi-automatic analysis of large databases for pattern mining, which is innovative, legal, useful, easy to understand, and is also known as database knowledge retrieval (KDD). The data mining or KDD process includes problem formulation, data collection, data cleansing (e.g. pre-processing, transformation, selection of mining operations/methods, and evaluation/visualization of results). Knowledge discovery is an iterative process. In this article, a systematic review of various data mining models and applications in the field of Internet of Things (IoT), as well as its advantages and disadvantages, was investigated. Finally, we discussed the challenges of the Internet of Things. Internet of Things (IoT) is evolving rapidly due to the latest developments in communication and sensor technology. It is very difficult to connect each thing through the Internet, but after a certain amount of time, the Internet of Things will completely change our lives. The vast amount of data captured by the Internet of Things (IoT) is considered to have high business value and social value, and various data mining algorithms can be applied to IoT data by extracting hidden information from the original data.