Awards & Nominations
Supernova has received the following awards and nominations. Way to go!


Supernova has received the following awards and nominations. Way to go!

The application of artificial intelligence that predicts areas of heat stress and areas of potential fires by using the data of climate sensors and NASA data to give the necessary instructions to both civilians and fire officials.Flowchart :( https://drive.google.com/file/d/1QJXSRf1xusxAsCYp_mbBsddhxgPu1jW2/view?usp=sharing )Application interface:( https://drive.google.com/file/d/1Wd_3-c9K-IPHWLk-xO-LbMQAJPRicNAF/view?usp=sharing )
The application of artificial intelligence that predicts areas of heat stress and areas of potential fires by using the data of climate sensors and NASA data to give the necessary instructions to both civilians and fire officials.
Application goals:
danger zones
Using artificial intelligence to predict and monitor the probability of forest fires using a special map displaying heat stress areas, categorized using a classification model such as: Red > Severe Hazard.
Weather
Present temperature, humidity, pressure and wind speed and many factors that effect on the nature.
Warnings
Based on the classification of heat stress areas, a warning about potential risks is sent to the competent authorities, and to the general public to be careful.
Instructions
Sending special instructions to both civilians, such as: not to throw inflammable waste, and fire officials, such as: the amount of water needed in the event of a fire
Reports
Weekly and monthly reports help to know and predict risk levels.
https://archive.ics.uci.edu/ml/datasets/forest+fires
The Portugal region data was temporarily used to test part of the app idea. The image shows a description of the data set that was used in machine learning.
(The actual application will use data provided by NASA
( crowdsourcing data)
(EO observation)).
For more information about the data, please see the link
We used the RandomForestRegressor model in order to predict the size of the areas where wildfires can spread and classify the level of fire risk based on the previous data (pre-processed data). And as an example, we predict the wildfires boundaries, level of fire risk and amount of water required to put out the fire which is one of the instructions of our application.
enrolling in this experience was very entertainment and full of advantage because this journey help us to discover some problem in the world we were not having a lot information about it or we were not knowing that it exist, and it makes us think about many solution and know we have a lot of information in many sides of science
https://archive.ics.uci.edu/ml/datasets/forest+fires
https://www.giss.nasa.gov/projects/impacts/uccrn/
#science #nasa #world #save_planet #environment #fire
This project has been submitted for consideration during the Judging process.
Climate change is expected to exacerbate heat-related extremes that impact human health and environmental and ecological systems. Your challenge is to build a tool that uses Earth Observations (EO), crowdsourced data, and models to provide warnings about potential impacts of these events, along with guidance on mitigation measures.
