Decision Making using Internet of Things and Machine Learning: A bibliometric approach to tracking main research themes

The internet has become an integral part of our life, we connect daily for informational, social, entertainment and even work and economic purposes. Therefore, it is completely normal to connect to the internet; But it is not only people, also these everyday objects or things in our environment who connect to the network to take advantage of its benefits. This next stage in the evolution of the internet, in which connectivity extends to the objects which surround us, is known as the Internet of Things. Sensors, Machines, Devices, Wearables are part of the Internet of Things and these can be identified to be recognized and interact without the need for a human being. With the Internet of Things, the connection extends to any type of object. All these interconnected devices and people produce an immense amount of data, when analyzed, they become a tool that allows organizations to make wise decisions in real time by having information on various market situations and ensuring a better understanding of behavior and consumer preferences. One of the disciplines of Artificial Intelligence responsible for analyzing this large amount of data is Machine Learning, whose sole purpose is to improve the Decision-Making process. To understand the relationship between Internet of Things, application of Machine Learning and the Decision Making process, a bibliometric analysis is carried out from 2013 to 2020 to know its evolution, trends, research areas, authors and other aspects using Scopus.