Spot That Fire V3.0
ROF
Summary
we decided to build a website that makes a prediction about the coming wildfires and the economic losses. The prediction depended on machine learning and data analysis. - In addition, to make a prediction, our website offers the safety rules that everyone should follow if he will be camping in the forest or even before, during, and after the wildfires. also, our website is available in two languages English and Arabic. Also, the website provides the fire emergency number in all the countries in the world.
How We Addressed This Challenge
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.
[6:37 AM, 10/4/2020] Arwa Ahmed: Our project has succeeded in addressing this challenge from all directions where,
The ability to predict the economic effects of actual or potential forest fires by comprehensively collecting most of the economic effects of the most serious and significant previous forest fire incidents and also was able to predict possible places of forest fires, which reduce the negative effects of fires (this is the main problem in this challenge)
In our advice, we have developed the forecast of possible places of occurrence of forest fires and forecasting the economic effects associated with these fires and this project is very important to reduce the negative effects associated with these fires, the process of predicting fires before they occur is a very important process, through which these areas are precautionary and avoided, which leads to the reduction of human and economic losses as well,
Processes to build our website
We started collecting a database on forest fires and then we conducted data analysis for it using machine learning so that we can predict, and we have linked this prediction to a website that has been built with several programming groups including HTML, CSS, and JAVASCRIPT .then our site is designed and complete to work.
Our site consists of predictions of where forest fires will occur and also predictions of the economic effects associated with fires and there are also guidelines for how to deal with the fire before and after it occurs and anyone can use our site at any time and anywhere because it is open source because it is one of the most important features in our site
How We Developed This Project
We chose this challenge because we know how dangerous it is on the whole earth, the presence of any fire in any of the forests of the world harms an entire village, as well as countless living creatures. So we chose him to contribute to solving some of his problems. We relied on this project on forecasting the places in which fires could occur, and this is not very present and predicting the economic losses of any fire that could happen. Also, it is distinguished and what we do not find a lot is the firefighting numbers of each country and the safety rules, and this is distinctive in itself because we tried to cover the problem In all its aspects. We used the data set by NASA in addition to some data from the Kaggle website, and we analyzed and created the data through our learning of machine learning, created a website, and linked the data and the web site together to get the current result.
We faced many problems in choosing the people to participate with us, in the shortage of time and in our experiences and in everything, but we are trying hard, so we worked hard until we finished the project and we learned in this short time, and of course, we gained some good experiences.
How We Used Space Agency Data in This Project
The fact that NASA put the data to help us was one of the best things that happened because it is documented data first, so the accuracy of predation will be very high, and this will help the user, and it also saved us some effort in searching for the data due to lack of time as we relied on it in part. prediction and especially predicting the economic losses that the country will be exposed to when the fire breaks out, based on studying the economic losses of the most famous fires, their locations, the time period that they lasted, and based on all of the above, we make a prediction of the economic losses that the region will be exposed to
Project Demo
https://drive.google.com/file/d/1YnrycQZbMBPpXP6AWYs4FRk6VRSQLO2k/view?usp=sharing
Data & Resources
1. https://www.greenpeace.org/international/story/44159/fires-brazilbolsonaro-amazon-deforestation-2020/
2. https://phys.org/news/2019-08-amazon_1.html
3. https://wwf.panda.org/knowledge_hub/where_we_work/amazon/about_the_ amazon/why_amazon_important/
4. https://cnr.ncsu.edu/news/2019/09/amazon-rainforest-fires-everything-youneed-to-know/
5. https://globaledge.msu.edu/blog/post/56791/will-the-amazon-rainforest-fireburn-down-the-economy-- #:~:text=The%20Amazon%20holds%20massive%20amounts,would%20be %20pulled%20into%20question.
6. https://www.amazonfrontlines.org/chronicles/three-critical-consequences-ofthe-amazon-fires/
7. https://www.deccanchronicle.com/nation/current-affairs/160319/fire-on-themountain-why-bandipur-burned.html
8. https://bangalorean.com/blog/bandipur-forest-fire-tiger-reserve/