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AQI-Prediction-Neural-Network

Using LSTM to Predict and test if the predictions performed are accurate.

It includes the Program And a data set of AQI data collected in a room in 9th block MIT , India

AQI Category, Pollutants and Health Breakpoints AQI Category (Range) PM10 (24hr) PM2.5 (24hr) NO2 (24hr) O3 (8hr) CO (8hr) SO2 (24hr) NH3 (24hr) Pb (24hr) Good (0–50) 0–50 0–30 0–40 0–50 0–1.0 0–40 0–200 0–0.5 Satisfactory (51–100) 51–100 31–60 41–80 51–100 1.1–2.0 41–80 201–400 0.5–1.0 Moderately polluted (101–200) 101–250 61–90 81–180 101–168 2.1–10 81–380 401–800 1.1–2.0 Poor (201–300) 251–350 91–120 181–280 169–208 10–17 381–800 801–1200 2.1–3.0 Very poor (301–400) 351–430 121–250 281–400 209–748 17–34 801–1600 1200–1800 3.1–3.5 Severe (401–500) 430+ 250+ 400+ 748+ 34+ 1600+ 1800+ 3.5+

Air quality has been a major concern to our species for hundreds of years, with our incremental use of natural resources for creation of energy to power our ever growing need, we have pushed the natural reservoir of our planet to its limits and in the process helped to increase the release of harmful and detrimental gases into our atmosphere.

Gases such as Carbon Monoxide, Sulphur dioxide, Carbon dioxide, Nitrogen dioxide, and Ozone, which not only increase the overall temperature on the earth surface but also act as harmful chemicals to the biosphere and the life within it. It is important we develop ways to measure it. To make this possible, the main approach should measure the most polluting components of the vast array of pollutants and harm and affect us. Our project focuses on the Particulate matter that is present in our environments because PM is something that is much more stubborn and creates greater health risk compared to every other component that is capable of harming us, thus sensing and monitoring the PM accumulation in a system gives a much better and clearer idea of the demerits and harm of our approach to using resources and our lifestyle.

Through our photometric method of scaling and measuring the size and the concentration of the PM in an environment we can find out the level of pollution prevailing in that zone. The output of our set up gives accurate reading of the size of the particulate matter (Between PM 2.5 and PM 10) and the concentration, and the entire device is controlled by an Arduino Uno. The output can be analyzed and studied to get inference about trends about the level and condition of the air quality in that region and thus helps us to figure out how to change our methods to better incorporate our processes which lead to greater generation of Particulate Matter .

India lacks serious infrastructure that can accommodate our growing industrialization and keep up with the ever increasing sources of pollution. We are not developing steps and methods to combat the amount of damage we are doing to our Flora and Fauna and it is important we take matters in our own hands and create solutions that not only save our livelihoods but also out lives and of those of the generations that are going to come after us . We have pushed our planet to its limits and we need technology that better our understanding and perception so that we can make intelligent and informed decisions to fix this growing threat.

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Using LSTM to Predict and test if the predictions performed are accurate.

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