Alpha saviors

https://drive.google.com/file/d/1MAPWatKsD7g6MD-PpJDXrpRss1o5ky0W/view?usp=sharing

https://github.com/MoustafaMashaal

How We Addressed This Challenge

Problem:

Nowadays climate change has a serious impact on everything around us. Millions of acres have burned into ashes. Billions of animals have been killed mercilessly. USA, Australia, Turkey, Amazon forests and others have witnessed most severe fires in the last 10 years. USA for examples has a lot of areas exposed to fires like California, Texas, Colorado and Arizona.

Last year, there were 58,950 wildfires compared with 50,477 in 2019, according to the National Interagency Fire Center. About 10.1 million acres were burned in 2020, compared with 4.7 million acres in 2019. Six of the top 20 largest California wildfires fires occurred in 2020, according to CalFire’s list. Thousands of people had to leave there homes.

All of these heart-breaking things made us think about a solution. By using NASA FIRMS, Earth observations and some other data, we started acting and working on our project.

Our solution

Introduction

Our main idea lies in forming a past, present and future expectations information. Also helping people and animals before, during and after a blaze bursts. Our app also provides services, directions, guidance, maps, data and GPS directions.

Main Topic

   Humidity, temperature and wind; those are the main causes of wildfires. So we used a smart way to help predict the near risk by asking the user to enter the percentages of the three parameters and compare them to the percentages that may cause fire, hence we show the user three alerts; warning, near risk or safe; all with three colors; red, yellow and green.

 Providing Guidance to the public users has been taken into consideration. We have provided three main guidance info; the first one is a history about wildfires, the second one is info about today whether there is a fire or not, the third one is about future expectations using machine learning. (There’s some missing part in “Prediction” button. We needed more time to do Machine learning on previous data of wildfires to predict the future wildfires)

 Expecting the blaze helps controlling it as we included calling for help in our app. We included emergency numbers for users as they expect near risk. Following day-to-day updated information can save lives.

    During and after the blaze, we shave set services to call for help and self-help systems. In case a person is in danger and cannot wait for help, we provided self-help system by image processing and online GPS. By clicking on “Show safe directions” button on our app, the user can find safe directions to escape from fire (We needed more time to use satellite connections and GPS to complete “Safe direction” part).

In case a person has been exposed to a skin burn, we provided a button called “Degree of burn”. It works by image processing to check up on the degree of burn, hence call for help if necessary. 

There are two maps and one simulation mode; The first map appears when you click on “Active Fires”, it shows you the active wildfires and it’s auto-updated in Real-Time.

The second map is for monitoring drought and it’s also auto-updated in Real-Time.

There’s also a simulation model for surface temperature which you can use easily by changing the parameters provided.

 Our main goal is to provide an easy wide range data based app with help services, guidance and predictions which can be used by public. We hope to achieve more progress in this app using ML, DL, Sattelites, GPS and we really wish from deep inside that this app will become real and be used by people to help them and to save not only people's lives but also animals' lives.

Vision

·      Providing a smart and accessible tool (Mobile app) to the public users to guide, protect and save them before, during and after fires.

·      We hope to achieve more progress in this app using ML, DL, Sattelites, GPS and we really wish from deep inside that this app will become real and be used by people to help them and to save not only people's lives but also animals' lives.

NOTES:

We needed more time to complete some areas concern deploying what we have done with Machine Learning and Image processing into our Android app. So we let them separately. In other words, we coded ML and IP and we uploaded them on Github , however we did not have time to put them into our app. we used kaggle in our work.

Video for full project link

Note: If you click and still not working, copy the link below and paste it on a new tab.

https://drive.google.com/file/d/1g87F7ML1i7nHo8taQFyBbNvnfZEXFXRP/view?usp=sharing

Value Proposition

·      Providing an easy too to public users as a quick self-help

·      Providing multiple services in the application

·      Helping people before, during and after a blaze.

·      Predicting and monitoring the parameters which cause wildfires. 

Resources

Software

·    Android studio

·    Java

. Python

·    API

·    ML

·    Image processing

·    Data visualization

·    Inshot

·    Microsoft word

How We Used Data in This Project

We used NASA earth data (NASA Goddard Data/Info Services—DAAC ) to get Archive data for wildfires for the last year From, I have requested the data by my email. We found these data interesting as there's anything you need. NASA earth led us to FIRM NASA which we obtained the data from.

We used NASA/GISS surface temperature analysis to obtain a simulation model for surface temperature.

we used NOAA North American Drought Monitor to obtain a map for monitoring drought.

we used FIRMS: NASA | LANCE to obtain a map for the active wildfires in Real-Time.

Actually, these resources have tremendous amounts of data and they are really helpful.

Data

·        NASA Goddard Data/Info Services—DAAC

·        NASA urban climate change research network

·        USA Drought Monitor

·        NOAA North American Drought Monitor

·        https://firms.modaps.eosdis.nasa.gov/

·        https://www.kaggle.com/elikplim/forest-fires-data-set

It is worth saying that this experience not only a competition but also something leaves great impact in your entire life. That's why I shared for the second year.

We have learned so many valuable morals like helping each other and giving excuses to the ones who have them. We learned to be well-prepared much earlier because the time is very important and this is really our biggest challenge. We were fighting time to provide the best quality.

One of the reasons we participated in this competition is that our pure aim to help our planet from catastrophic disasters caused by climate change.

Finally, I would like to thank every member in my team for being cooperative and I would like to thank every person helped organize this amazing competition,

Thank you.

References

·     Wikipedia

·     https://www.iii.org/fact-statistic/facts-statistics-wildfires

·     https://commons.wikimedia.org/wiki/File:2020_California_wildfires.png

#Climate_Change #Wildfires #Software #App #Fire

This project has been submitted for consideration during the Judging process.