International Journal of Engineering Sciences and Management- A Multidisciplinary Publication of VTU 2019; Vol: 1, No: 1, pp: 56-61 © 2019 VTU Page No. 56 Powering the Internet of Things and Big Data through Machine Learning Geetabai S. Hukkeri a* , R. H.Goudar b , Shivani Kulkarni c abc Department of Computer Network Engineering, Visvesvaraya Technological University, Belagavi, India; Abstract:: Eventually Internet of Things, Big Data, and Machine Learning will be an exposure to the wide-ranging scale of current applications. The Internet is getting linked to numerous appliances equipped in simple things, which allows them to deliver and accept the information or data. Big data is more of a progress than a thing. It has become the cover for the compilation, study and repository for huge amount of data. Machine learning is a function of Artificial Intelligence that implements the system’s intelligence to automatically learn and advance from experience without using any special programs. The focus of Machine learning is to advance the computer programs that can approach the data and utilize it to learn for them. An increasing measure of powerful data origins, drive in Internet of Things & Big Data improvement, also the convenience of a large variety of Machine learning computations attempts new possibilities to bring logical control to industries. Extensive amount of data have been generated, since the past decade as the downgrade of Internet of Things tools increments. Yet, such data is not beneficial without experimental abilities. Different Big Data and Internet of Things analysis arrangements have granted individuals to achieve effective knowledge into broad information generated by Internet of Things objects. Nonetheless, these arrangements are fixed in their original stages and the domain does not have a detailed report on this. This paper gives an acceptable deeper understanding about the Internet of Things and Big Data structure parallel to its various issues and challenges. It also gives possible solutions addressed by Machine Learning. A R T I C L E H I S T O R Y Received: 25-01-2019 Accepted: 27-03-2019 Keywords: Internet of Things, Big Data, Machine Learning, Routing, Sensor Technology, Computational Intelligence. 1. INTRODUCTION 1.1 Internet of Things In a simple term, IoT is referred to as “a link made between connected devices”. In regard to the input provided by human or user, IoT allows its devices to work as expected by users. Consider the following example to understand it more easily; there is a cup of milk inside your fridge, the IoT permit your fridge to collaborate with a cup of milk inside it. Without any interference of user, the fridge will come to know the expiration date of the milk, once that date is past, fridge will undoubtedly notify the user about the expiration of milk and to order new cup of milk. Like this IoT has several real timeApplications including, health monitoring, smart gardening, child and pet finder, fitness trackers, smart toothbrush, and so on. *Dept. of Computer Network Engineering, Visvesvaraya Technological University, Belagavi, Survey on the use of IoT:  In a technological ideal world, all of the gadgets and appliances would be connected together over the Internet, consistently communicating with each other and exchanging data.  IoT's prosperity is predicated on sharing and defining data between gadgets. With voice assistants coordinated into pretty much every cell phone. 39% of individuals trust access to critical data as the primary advantage of utilizing connected gadgets.  The top three connected devices that people own are smart home appliances, wearable, and digital assistants.  Sharing data implies more external parties approach client data. In the increasing security-cognizant atmosphere, individuals are becoming enthusiastic about how their data is gathered and distributed.  From a buyer point of view, the emerging IoT innovation can appear to be overwhelming and remote. "IoT is certainly still in the early-adopter stage with numerous buyers/ consumers.