Application based air pollution prediction system using machine learning

Over the past years due to the pollution caused by industries human activities and by some incidents the air quality index is becoming worse day by day so we are making an app and a device that measures the air quality index by measuring the number of harmful gases and pollutants like Sulphur, carbon dioxide and carbon monoxide particulate matter measures if AQI is in a danger level. The app not only tells the AQI but also tells if a person suffering from a disease like asthma, then he/she has to go outside or not in that situation. Motor cars, industry, and power plants all contribute to outdoor air pollution by burning petroleum products or coal. Another major source in some nations is the combustion of wood or agricultural waste. Industrial processes that produce dust (for example, cement factories and metal smelters) or gas discharges can also cause pollution (for instance, from chemicals production). Indoor sources contribute to outdoor air pollution as well, and their contribution in densely populated places can result in exceptionally high levels of outdoor air pollution.PM, nitric oxide and NO2 (together referred to as NOx), carbon monoxide, organic compounds, and lead are all released by automobiles. particulate matter (PM) (dusts, fumes, mists, and smokes), gaseous pollutants (gases and vapours), and odors are the three types of air pollutants.Total suspended particles are divided into two categories: PM10, Sulfur compounds such as SO2 and CO2 are examples of gaseous pollutants.. At ground level, nitrogen oxides and hydrocarbon emissions combine with sunlight to produce ozone, a secondary pollutant. Unlike ozone in the upper atmosphere, which occurs naturally and protects life by screening out UV radiation from the sun, ozone at this level.