High-Level Project Summary
FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality) Scoring System based on machine learning algorithms. This model takes data, analysises data and scores data about Fire Influence of specific area. Why is it important? Because every citizen of speific area should be warn about AQ in his(or her) area. This project can help to score AQ by analysing smoke age and windspeed in this area.Without FIREX-AQ soring this project includes weather forecast of every user's area.
Link to Final Project
Link to Project "Demo"
Detailed Project Description
This project has been written in the programming language Python in the Django framework
That's why after cloning the project from Github, several steps should be taken.
- Install Django(pip install django)
- Install Pandas for reading .csv file
- Running local server
After running the local server, there are four links, but two of them are the basis of our project:
Scoring - Scoring FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality), but here we got a dataset in .xlsx format and deleted several columns and rows. Only the data of Shany Hills has been taken and scored.
The Weather section shows the weather of the user's location.
Other sections are just for information.
The main benefit users and citizens can gain from this application is information about the influence of fires on the climate of their city or town from NASA's data.
Space Agency Data
We used NASA's Airborne Data: FIREX-AQ (Fire Influence on Regional to Global Environments and Air Quality)
https://asdc.larc.nasa.gov/data/FIREX-AQ/
https://asdc.larc.nasa.gov/data/FIREX-AQ/Analysis_Data_1/
Hackathon Journey
I and my group learned lots of things during NASA Space Apps Hackathon.
- First of ALL TEAM Work,
- How to use NASA's data esspacially NASA's Airborne data.
- Meet with new friends
Our approach for solving challenge is making machine learning model for scoring data,which is taken from NASA's Airborne Data. I want to thank to all of my teammates: Jahongir, Amir, Temur, Sardor and Sunnatillo. With them I lost my stress while facing several problems several problems
We had only one motivation for participating to NASA Space Apps Hackathon:
Space Exploration starts with the right data
References
TOOLS
For writing backend of project in Python ptogramming language. I and my team used Pandas and sklearn for data analysis and scoring climate
Microsoft Visual Studio Code (Code editor and Developer Environment) Environment for writing, running
HTML & CSS & JS(Front-End)
Google Chrome (Testing and debuging)
GitHub and Git (For hosting project to open source service)
Tags
#software #climatesoring #weather #climatechange