International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 09 Issue: 05 | May 2022
p-ISSN: 2395-0072
www.irjet.net
ENVIRONMENTAL QUALITY PREDICTION AND ITS DEPLOYMENT Dr.S.Sridevi1, Rakesh Jampala2, B.Yaswanth3 1Associate
Professor, Department of ECE, Vel Tech Rangarajan Dr.Sagunthala R&D Institute Of Science And Technology, Chennai, India 2,3Student, Department of ECE, Vel Tech Rangarajan Dr.Sagunthala R&D Institute Of Science And Technology, Chennai, India ---------------------------------------------------------------------***---------------------------------------------------------------------
Abstract - The environment is the source of survival for the
gathers data from sensors and learns to behave in an environment. The ability of machine learning (ML) algorithms to adapt was one of the reasons we chose machine learning to predict the air quality index. The machine learning algorithms in such as naive Bayes classifier, logistic regression and decision tree classifier are implemented in this approach.
human. In the modern days, the degradation of the environment has been increased significantly, when we compared to the last few centuries. Examining and protecting environmental quality has become one of the essential aspects for the government in recent days. The meteorological and traffic factors, burning of fossil fuels, deforestation, industrial parameters, and mass development of civilization played a significant role in environmental quality. With a significant rise in environmental pollution, we need models which will record information about the environment and its pollutants. The deposition of harmful gases in the air, mass deforestation, and industrial factors are affecting the quality of people’s lives around the world. Many researchers began to use the big data analytics approach as there environmental sensing networks and sensor data available. In this project, we implement ma chine learning models to detect and predict environmental quality. Models in time series will be employed for the better prediction of environmental quality
1.1 Aim of the project The primary objective of this project is to analyze and predict the optimum quality of air using the machine learning algorithm. In addition, develop a machine learning model for higher efficacy and lower error rate for better prediction. And top of that to help the society with the optimum model of machine learning for a better tomorrow.
1.2 Project Domain The project was designed to detect air quality, which is significant factor in contemporary society, as it impact individuals health. Therefore, We utilized Machine learning algorithms to predict the air quality. We designed the project using Supervised learning algorithms of Machine Learning algorithms such as Decision Tree, Support Vector Machine, and Naive Bayes.
Key Words: Environmental quality, Machine learning, Pollutants, Time series models.
1. INTRODUCTION With economic development and population rise in cities lead to environmental pollution problems involving air pollution, water pollution, noise and the shortage of land resources have attracted increasing attention. Among these, air pollution is significant problem, as it impact the human health. People exposure to pollutants has resulted in serious health problems. Both developing and developed countries are trying to figure out methods to ameliorate the present air pollution situations. Air pollution is usually caused by energy production from power plants, industries, residential heating, fuel burning vehicles, natural disasters etc. Human health concern is one among the important consequences of air pollution especially in urban areas. Artificial intelligence and machine learning in recent years has been one of the phenomenal advancement of technology Instead of just writing commands as standard works, the philosophy of artificial intelligence, in which the system makes its own choices gradually impacts all aspects of our society. Machine learning is an area where an artificial intelligence system
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1.3 Scope of the Project As the quality of the air is degrading around the world there is a need for efficient machines for the monitoring air around the world. Inhaling the air with toxics will leads to several disease. With the help of the air quality we can impose the restrictions for saving the environment and can save humanity from many disasters.
1.4 Methodology Classification is to determine the class to which each data sample of the methods belongs, which methods are used when the outputs of input data are qualitative. The purpose is to divide the whole problem space into a certain number of classes. A wide range of classification methods are present. There are diverse classification methods have been constructed for different data, since there is no particular
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