The EO Dashboard has multiple global maps for air quality and greenhouse gases in GeoTIFF file format. Your challenge is to create a spatial analysis and time series plotting tool for EO Dashboard air quality and greenhouse gas GeoTIFF datasets.
Our project “Air Quality Index” focuses mainly on making an air quality monitoring system. This is done by distributing sensors for different pollutants in the air. These sensors will be connected to NodeMCUs that will return a value that reflects the quality of air and the percentages of its pollutants. By posting these values on a server and displaying them for the user the air quality can be monitored live from any place. Also, this application has a huge library for air quality records years ago allowing governments to compare between these records to see how the air on their lands is changing opening doors for early analysis.
With this electronic progress we are living in, scientists are looking for new ways that can keep humans safer from what is threatening his life in the previous years. As it is mentioned in this challenge it is required to make a global map for air quality and greenhouse gasses and plotting them in an appropriate dataset for analysis. What is provided in our system agrees with what is desired as it provides a platform where new air quality records will be gathered and meet the old ones forming a time series for the records of air records that can be easily understandable by people. This can be done by the connection between Arduino sensors and the NodeMCU which will return the value of the parameter and being posted into a server that will display these records in front of the user. This can allow the users to easily compare the quality of air where they live along long time series, opening their eyes whether their place is going better or worse. We hope that if normal people can access this information and it is easy for them to take notes about where the world is heading if they noticed an increase in pollution, they can take some serious steps to help in beating the air pollution.
Although no one can live without air, the air is still being polluted by people which contributed to making some regions poisonous for their inhabitants. That inspired us to make an accessible platform where anyone can monitor the air quality he is breathing and to know whether it is safe or not hoping to increase the people’s awareness about how sometimes the air they can’t see that is inhaling into their lungs can be very dangerous only because of their actions polluting it. To develop this idea into an actual working prototype we used a NodeMcu development board linked to an online web server. To program the board, we're using Arduino IDE. The code works with the WifiClient.h Libra along with the HTTP.Post function to send the data to the webserver. In further details, rendering the output in front of the user can be done by running our scripts on a server; so first we started making a web app project with Django (python framework), after that we wrote some code to handle POST and GET requests from and to the user in the client-side, and from to NnodeMCU on the server-side, so we created the main project under name galaxyexplorers and the main app name was airquality, then we configured the settings of the project and added the app to the main project, after that, we organized the views functions and linked them to the app urls.py, then we included the app urls.py to the project structure url.py file, finally we made the project migrations and saved them, then we ran the server and that worked, and all of that is the part of the client-side.
No good work originates from scratch, there should be a method of help that boosted this work at the beginning. In this project space agencies’ data was important in the progress of this project. First of all, after searching about prior attempts in monitoring the air quality, it was found that different space agencies like ESA and NASA have launched constellations of satellites orbiting around the Earth to monitor the air quality, but what lacks their attempts as said from one of NASA’s team members then is how to connect these data coming from satellites in right datasets. Their attempts helped us in seeing how this project can start and how this network of sensors can be established and from where they stopped was the point where we started to progress and represent these data in an interactive app where it is easy for users to read and understand these data and gain information about the air they breathe. Also, space agencies’ data was important in making this application bigger as it contains a library of previous air data records which was once gathered from these orbiting satellites.
As we provide a simple, interactive, options provided GUI for users to interact with; first, the user chooses the options to select the method which will be performed, then the bunch of these data is sent to the back-end (server) to organize them in JavaScript object notation format (JSON), to make that able for the NodeMCU component to read them, after that it performs its tasks using the algorithms we put for it, then the statistics are sent back to the server which in turns converts them to human-readable data and sends it to the front-end to be rendered in front of the user in an organized and simple way. Some examples for codes that are inserted into this project can be viewed by opening the following links:
https://drive.google.com/drive/folders/1Xd_w1DLxIplbBn65dkMd8DxFXdL1b9HL?usp=sharing
https://drive.google.com/drive/folders/1Cp_rrcF0kOfpPj2ie6MqnDI7Wnl60q-p?usp=sharing
https://drive.google.com/drive/folders/1eE9GF5ZKF2siDv1rJzbFU09gJoNrBty_?usp=sharing
#Internet of things #automation #Artificial intelligence #Web development #space agency data based
This project has been submitted for consideration during the Judging process.