Automated Detection of Hazards

Countless phenomena such as floods, fires, and algae blooms routinely impact ecosystems, economies, and human safety. Your challenge is to use satellite data to create a machine learning model that detects a specific phenomenon and build an interface that not only displays the detected phenomenon, but also layers it alongside ancillary data to help researchers and decision-makers better understand its impacts and scope.

YPHD (Your Phenomena Detector )

Summary

First, the sensor of the satellite will based to determine the distance of the storm from the planet that will program by using A, I recommend Arduino. According to this info, the machine learning model will be a website that will divide into three sections in the first section: It will receive a warning about the occurrence of the storm, for example, and then write what will result from it and when it will happen. In the second section: it will write about incidents that happened before that, how did you work with them, and what their position on it.The third section: will write in it how to deal with the storm and the precautions to be taken and benefit from previous experiences.Finally,

How We Addressed This Challenge

The solution for this challenge is a machine learning model as required in the challenge. So, we decided to make a website and developed it by some programming languages like HTML and others. The websites is mainly depended on the satellite sensor date and blog it in the website to make the people know about the expected disasters in the nearby time, the details, causes and location to avoid the bad sites as possible as we can. so, the website will divide into three parts. First, what are the expected disaster. Second, previous ones. Third is how to deal with. All of that will help our world to avoid that and protect our community from being damaged.

How We Developed This Project

The main reason that inspired us to work in his challenge is the floods in Sudan that caused a high number of dead people and many losses. Also, damage some places. According to that we realize the main value for this machine learning model to help the communities avoid all this bad effect. So, we approached our website to make the people know about the disaster expectations, previous stories with same disaster to know about the causes and the results, and finally how to deal with by taking the full safety precautions. Using programming languages such as HTML and CSS and adobe dream weaver app tO complete our software project. There are some problems that faced us in achieving the project like the programming section but, we did not give up and use an app to help in achieving the software of the website to get our idea out to the light for real help for people.

How We Used Space Agency Data in This Project

We have used NASA data to understand the challenge more and help us to know examples of problems that may occur with scientists in space, and there was a prior solution to this problem, and this solution is that they use dramatic images of tropical cyclones to understand the size and intensity of the storm.

Data & Resources

NASA data 

Hindawi 

Arduino 

Adobe Dreamweaver

Tags
#software #detectore #website # sensor #ardiuno #programming
Judging
This project was submitted for consideration during the Space Apps Judging process.