Alt-Solve - Space Apps Challenge

Alt-Solve| Spot That Fire V3.0

Awards & Nominations

Alt-Solve has received the following awards and nominations. Way to go!

Global Nominee

Spot That Fire V3.0

Recent wildfires worldwide have demonstrated the importance of rapid wildfire detection, mitigation, and community impact assessment analysis. Your challenge is to develop and/or augment an existing application to detect, predict, and assess the economic impacts from actual or potential wildfires by leveraging high-frequency data from a new generation of geostationary satellites, data from polar-orbiting environmental satellites, and other open-source datasets.

FUEGO

Summary

Our system is intended to take data from NASA’s API’s, JAXA API’S some of its formats (like.geotiff and json) and registered users' info to confront wildfires by sending notifications to both users and authorities in proximity, while also deploying equipped emergency drones to help in the authorities in confronting wildfire incidents.Our project takes a number of steps to reach three general goals:1- Identifying wildfires.2- Reporting of wildfires efficiently. 3- Facilitate effective retaliation given a 3 hours time window.

How We Addressed This Challenge

The project/application identifies the fires near its users and this is done by using NASA data near-real time data; however since we are limited with a 3 hour delay in on incident reporting by all major space stations satellites, we decided to make an app to be used by campers for reporting wildfires and addressing the incidents with sending drones and notifications. With this application we hope to confront the wildfire global incidents.

Our system value lies addresses the challenge of confronting wildfires in a series of steps:

1-It takes inputs(Image) from users of a website and a mobile application available on all major platforms.

2-It processes the data in a number of ways through AI and servers.that implement the logic

3-As output system sends push notifications to registered users & authorities in the area.

4- Another output is sending deployment signals to smart drones that lie in close proximity to the incident relative to their stationary placement.

How We Developed This Project

The challenge started in gathering the team and then seeing the capabilities, talents and advantages of each member. After that we chose a challenge that suits our capabilities and preferences as a single team. Where the talents and abilities of the team members were like artificial intelligence & machine learning programming, mobile Application development, web design, embedded systems design and implementation, data communication, data structures and algorithms, Native mobile applications and general programming. Then we divided the work equally with everyone, based on the talents of each member. Where we used flutter and the dart language along with mapbox to make the mobile application. For the website, javascript html and css to make the website and login pages. Moreover we also integrated mapbox, then we deployed it through netlify.

the artificial intelligence & machine learning programming by python and keras among other modules for the data stuff to implement a CNN (convoluted neural network).

Lastly, we used tinkercad and arduino in c code for the drones and parachutes. At the end we combined these qualities, shared the work, and made " FUEGO ".

How We Used Space Agency Data in This Project

We decided to use eonet.sci.gsfc.nasa.gov or EONET one of NASA API’s for ‘Natural Event Tracking’ where it provided us in json format links of reported incidents of wildfires in the USA through ‘inciweb.nwcg.gov’.

We then trained a CNN Artificial Intelligence system to analyze images and reveal the authenticity of the reports.

After using the data available from NASA and its collaborating space companies like JAXA in the competition, the accuracy rate of the program has become close to certain, with a rate of 100% giving our 540 images input.

Project Demo

30 second demo:

https://www.youtube.com/watch?v=6egnjn0FtpE

Full explanation(length 5:49):

https://www.youtube.com/watch?v=2zDPyoKDiuY

**there is also short powerpoint in our github repository and links in the readme.md file on github

This application or project will help the environment and the whole world.

•As the percentage of fires will be greatly reduced and the number of trees burned will decrease, which will help increase the percentage of oxygen in nature and reduce global warming significantly, and also the amount of animals that die or are displaced due to the fires will decrease and on the contrary they will have a shelter, and also this project may provide some job opportunities such as supervising and verifying drone stations.