Labelling Data for Correlation Pollution Dataset by Using Machine Learning

Abstract

The significant problem in the environment is the pollution of air which affects all the areas in our world. The solution of this problem is excluding by using Internet of Things (IoT) technology which designed system that monitors the parameters that affect the pollution in the environment. The handling and operation of large quantities of information from a wide range of sources is challenges in IoT technology. The purpose of this study is to decrease the dimensions in IoT systems so we suggest two models for IoT system and also aims to build rules for Air quality classification by defining pollution levels. In this study, we suggested machine learning techniques to predict an air pollution levels based on a dataset consisting of daily weather, also we simplified our classification models to solve this problem by using binary classification which is to classify the air pollution level into “High pollution” and “Simple pollution” class labels. The decision tree J48 Algorithm gives the best outcomes in the first model than the second models.