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This paper sheds light on the problems related database collection or selection in machine learning. It emphasizes on various aspects of database collection and issues one can get into while performing the collection procedure. It then discusses the second alternative method of using a premade database and how it could be an equally challenging issue, sometimes even worse. It concludes by a study of an air pollution database created in 2015 in.the state of Orissa, India which has over two thousand entries and applies different regression algorithms available analyzing the drawbacks of having data which is dense but limited to a particular location and time. This is followed by some methods through which the issues could be solved and emphasizes on the need for the issues to be solved and lack of databases in general. [ABSTRACT FROM AUTHOR]

Air pollution is the major level of environmental pollution which affects all the living beings health and atmospheric condition. In which it is a major challenging issue today's scenario. Air pollution leads to adverse effects on climate, ecosystem and living things including human, animals and plants etc,. The Atmospheric air is getting polluted by the industry, power plants, vehicle emission and many sources releasing the unwanted toxic, harmful gases and particulate matter into the atmosphere. This Particulate matter is one of the major sources for the contribution of increase in air pollution in the atmosphere. Such particulate matters create a serious requirement for monitoring, measuring and analysis of real-time air quality condition in order that appropriate resolutions are often taken during a period of time. This paper presents a real-time standalone solution for monitoring the air pollution level which includes various parameters: PM (Particulate Matters) 2.5, CO (Carbon Monoxide), CO2 (Carbon dioxide), air pressure, humidity and atmospheric temperature. The Internet of Things (IoT) is plays vital role in monitoring the pollution level in the atmosphere. IoT mingle with cloud computing gives a completely unique way for management of data from different sensors were collected and transmitted to the low power, a low-cost ARM Processor which act as a minicomputer based on Raspberry pi all the input from the various sensors are combined and compared to the standard level, when the variation is more than the standard it will inform the individual and also alert the user. Pollution in India has been increasing year by year and most of the states are suffering severely from it. So this system monitors pollution and updates pollution levels from all over the areas within the city in a real-time manner. [ABSTRACT FROM AUTHOR]

Emission-free economy is an achievable target with the formulation of policies by the Governments around the globe. A major contribution is made by the transport industry. Delhi is one of the examples among the cities in India which is polluting the air by transportation which is about 20 percent. Towards achieving the Sustainable Development Goals, the nation has to take a different trajectory from concentrating on the technical aspect of reducing the hazardous emissions to refining the regulatory awareness. The research study is based on the statistical inputs provided by the government agencies and the judicial verdicts seeking a pollution free atmosphere. The Judiciary has been proactively recommending and directing the respective government to take necessary action towards controlling the pollution caused due to road transport. Nevertheless, the use of Artificial Intelligence has been an area which has not been strongly recommended by the apex court. The regulatory and judicial control over the emissions is towards a penalizing perspective and the technological assistance has not been resorted to. Though a one hundred percent emission-free economy is not a possibility, the areas which are still not explored or have not been brought under the purview of consideration have been the scope of study in the research paper. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) are developing rapidly due to various factors, such as the climate and envi-ronment changes, reduction in prices comparing with conventional vehicles, due to the problems caused by gas-oline engines on the people as well as the environment. The automotive industry has changed to the EVs. EVs play a major role in reducing the emissions caused by the greenhouse gases which automatically leads to the reduction of air pollution. However, to enable the change from the traditional source of energy to fully EV powered motors, a new problem has emerged in society. The method of using electricity as a source of fuel is not a cheap task. It falls out of technology and infrastructure to support it as a primary source, infrastructure that is not available even in developed countries. EVs offer many benefits such as reducing pollution levels and oil imports bills etc. This paper offers reviews on electric vehicle mileage compiles and threats in promot-ing EVs. It also describes opportunities and challenges ahead in electric vehicles. [ABSTRACT FROM AUTHOR]

Air pollution in India is a serious health issue. A countrywide lockdown was imposed in India in response to the COVID-19 pandemic, firstly for three weeks starting from March 24 to April 14, 2020, and then extended until May 3, 2020. Because of the restrictions imposed, pollution levels in cities all over the country have dropped dramatically in just a few days, raised questions among scientists about lockdown as the most effective alternative approach for reducing air pollution. Hyderabad was chosen for this study because it is India's 5th largest city by area and 4th largest city by population, as well as major industrial centre in South-East Asia with strong air quality statistics. In light of the recent COVID-19 outbreak around the country, a detailed analysis based on air quality parameters from six distinct air quality monitoring sites in Hyderabad, Telangana, has been performed. For simple interpretation of air quality data, establishing a correlation between different pollutants, identifying sources of pollution, and determining the most significant parameters, different multivariate statistical approaches such as Cluster analysis (CA), Principle component analysis (PCA), correlation analysis, and multiple linear regression analysis (MLR) were used. The aim of this study is to evaluate the major air pollution sources in Hyderabad and to identify the most significant air pollutants based on their individual contributions to the Air Quality Index (AQI). Variation in air quality parameters collected for six air quality monitoring stations were represented using box or whisker plots. The data set has been grouped into four major clusters depending on the similarities in the air quality data. Major sources of air pollution in each cluster were identified using PCA. MLR analysis was used to create models for predicting AQI for each cluster based on concentrations of important air contaminants. The findings revealed that PM10 and PM2.5 play a significant role in determining AQI levels. [ABSTRACT FROM AUTHOR]