Machine Learning Role in Internet of Things (IoT) Based Research: A Review

The rapidly growing field of hardware- and software-based connected items that employ communication technologies is known as Internet of Things (IoT). In the past years, IoT utilisation and popularity have increased dramatically across many different applications. IoT stands for new kinds of communication, including communication between two objects and between people and things. Currently, Internet of Things concepts is heavily influencing the online world by introducing a new dimension. Intelligent big data processing and analysis is essential for designing smart IoT applications. Transportation, Logistics, healthcare, agriculture and the environment are examples of such uses. An increase in internet usage and environmental factors outside of the system are causing a dynamic shift in the IoT. Interest in the field of study on employing smart environments to deliver ubiquitous care has grown recently. By tracking the behaviors of their occupants, these smart environments hope to provide comprehensive care through ubiquitous sensing. To make the environment smarter, IoT and machine learning must be used. Machine learning techniques have become more popular in recent years, which encompass tools for extraction, identification, regression, classification, and forecasting. Machine learning is utilised to investigate historical data from cameras and sensors, and techniques are employed to prolong the lifespan of networks. We provide an outline of the recent research in this study being done for various machine learning applications to the Internet of Things. This study's purpose is to survey several IoT technologies that can support smart environment living.