MACHINE LEARNING AND THE INTERNET OF THINGS

Abstract

Machine learning is a part of computer science that developed from the study and construction of algorithms that can absorb from and make guesses on data. The Internet of Things (IoT) is the network of physical objects or "things" rooted with electronics, software, sensors, and network connectivity, which allows these objects to collect and exchange data. Collections of devices will act as systems that can be enhanced in new ways, and systems of systems will share data and perform as annetwork of data and devices. Machine learning - a term that describes numerous methods to evolving meaning from data - will have to be part of the calculation, but so will outdatedprofessional and data investigation techniques as organizations prepare for the Internet of Things (IoT). This paper will provide an overview of challenges and openings presented by this new model.