Awards & Nominations
IceTea has received the following awards and nominations. Way to go!
IceTea has received the following awards and nominations. Way to go!
Our project is based on foreseeing intense solar activity by using trained AI. After the Carrington Event, space weather has developed a lot, and has been showing more and more it's importance. For exemple, some really intense winds on the Sun could end up breaking down the world's acess to Internet. And that is exactly what we aim to avoid with the use of our app.
The app developed was based on remodeling the algorythm Darima and Sarima and applying it to a mathematic method of time analysis, something that turns it much more precise. Basically, the app uses a bunch of criteria such as solar winds, coronal mass ejections, the number of sunspots and the color of the polar lights, all from the day of the Carrington Event. The artificial intelligence was trained to recognize this data and compare it with the information provided. Therefore, it is able to check if any solar activity is not standart and is similar to the one from the most intense days, providing the risks of Earth being affected and hit by fierce magnetic pulses in advance.
The frameworks used were Pytoarch, React and Flask; the programming language was Python, Typescript and Rust; and the development engines Google Colab and vscode.
https://ngdc.noaa.gov/dscovr/portal/index.html#/ the data about the equipment taught us how the space weather is monitored. It helped us to come up with a innovation that follows the same principals.
https://www.swpc.noaa.gov/sites/default/files/images/u33/12-Kasper%202016-SWW-DSCOVRFC.pdf to learn about the current method of observing solar phenomena, is to be able to improve it!
https://www.nesdis.noaa.gov/current-satellite-missions/currently-flying/dscovr-deep-space-climate-observatory this taught us more about space weather and how it
The experience was amazing, almost unreal. We met so many amazing, smart, engaged people, and created some amazing bonds. We were able to learn a lot about about space: The Solar System, electromagnetism, magnetic fields, space weather and the Sun. Not only that, we were in contact with entrepreneurship, marketing, strategy and problem resolution. There were many moments when we had to take one step back and then two forward, when we had to just sit down and stare at the ceiling, when we had to stop everything and brainstorm to try and solve the multiple problems on our way. But still, all the smiles and vibrations with all of our accomplishments made us kind of apreciate any kind of stress we've been through; it was all worth it.
However, we did expect some difficulties. We chose the challenge based on the fact that it didn't have a established solution, we were intrigued and inspired by the problem and determined to find an answer. And it was awesome working on something as a team. The team wasn't just us from IceTea, though. All of the mentors were so helpful and kind, hence, a special thank you to them.
https://spaceweather.com/glossary/sunspotnumber.html
https://sidc.be/activities/data-processing
https://www.aanda.org/articles/aa/pdf/2011/09/aa16655-11.pdf
https://www.swpc.noaa.gov/products/solar-cycle-progression
https://ccmc.gsfc.nasa.gov/RoR_WWW/SWREDI/training-for-engineers/Zheng_CH_HSS_2014winter.pdf
https://swe.ssa.esa.int/what-is-space-weather
https://science.nasa.gov/science-news/science-at-nasa/2008/06may_carringtonflare
https://www.space.com/the-carrington-event
https://www.nesdis.noaa.gov/current-satellite-missions/currently-flying/dscovr-deep-space-climate-observatory
https://ngdc.noaa.gov/dscovr/portal/index.html#/vis/summary
https://www.swpc.noaa.gov/communities/space-weather-enthusiasts-dashboard
https://ngdc.noaa.gov/dscovr/portal/index.html#/%23swi
#Sun #MagneticField #Earth #Software #SpaceWeather
If a major space weather event like the Carrington Event of 1859 were to occur today, the impacts to society could be devastating. Your challenge is to develop a machine learning algorithm or neural network pipeline to correctly track changes in the peak solar wind speed and provide an early warning of the next potential Carrington-like event.

