Machine Learning Approaches for IoT-Data Classification

Abstract

The emergence of concepts like Data Science, Big Data, Machine Learning, IoT in recent years have added the potential of research in today's world which is flooded with data. The use of IoT devices, sensors, etc. which are collecting data continuously is putting a lot of pressure on the existing IoT network which is resource-constrained. And hence pointing towards the potential of research for such kind of resource-constrained environment. In this paper, the focus is on the classification of data at the device level, edge/fog level and cloud level using machine learning techniques. The data analysis for the same will be done by using Python language. As the data which is coming from different devices is vast and is of variety, therefore it becomes very important to choose the right technique for the particular type of data for classification. This will help in optimizing the data at the device, edge/fog level for better performance of the network in the future.