High-Level Project Summary
Using satellites, we measure the thermal radiation of living organisms in the specified area, from which we determine the type, density and condition of living organisms by making a classification using artificial intelligence. By using sensors, we can determine the wind speed and by the direction of the wind and the path of the fire and we can, using artificial intelligence, make a heat map, and thus predict the location of fires, types and the specifications, and thus the fires can be controlled and faced. We aren’t only target humans and rare plants found in some fire-prone areas, but also rare animal breeds found in forests such as in the Amazon as we've made an evacuation plan.
Link to Project "Demo"
Link to Final Project
Detailed Project Description
Background & literature review
We develop an application to chase the fire to make classification and predict the areas where the fire will spread using artificial intelligence. Controlled burns have become more important as fire suppression efforts have grown over the last century.
Historically, smaller fires occurred in forests at regular intervals.
When these fires are suppressed, flammable materials accumulate, insect infestations increase, forests become more crowded with trees and underbrush, and invasive plant species move in.
Methodology
Value Proposition
Its value lies in its usefulness for the whole world, its Reduces the damage of forest fires and helps to control them and put them out early and help to preserve plant life and human life in general.
Space Agency Data
WE do Practical example on a real Nasa Datasets Forest Fires (517x12) and Fire Archive M6 .
Hackathon Journey
We chose raise temperatures challenge because it caused a lot of risks in recent periods, most recently the forest fires in Algeria that killed thousands of people.
We're trying to reduce forest fires that kill large areas of trees and lead to human deaths every year.
References
1- fire_archive_M6_157333 data (From Nasa ).
2- P. Cortez and A. Morais. A Data Mining Approach to Predict Forest Fires using Meteorological Data. In J. Neves, M. F. Santos
and J. Machado Eds, New Trends in Artificial Intelligence, December, 2007.
3- D. Stojanova, P. Panov, A. Kobler, S. Dzeroski, and K. Taskova. Learning to Predict Forest.
4- Fires with Different DataMining Techniques. In D. Mladenic and M.
Grobelnik, editors.
Tags
Creativity Is Intelligence Having Fun
Global Judging
This project has been submitted for consideration during the Judging process.