Code'n'Klystron| Automated Detection of Hazards

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.

Fire Intelligent Detection

Summary

We have developed a fire detection system using satellites, neural networks as analyzers and telegram bots as an interface for notification. It detects fire and noticed user via telegram-bot

How We Addressed This Challenge
Our project solves a problem from the "problem list" of this call. The problem from the list sounds like "Automated Detection of Hazards".
How We Developed This Project

We have developed a fire detection system using satellites, neural networks as analyzers and telegram bots as an interface for notification.

We have used satellites that measure gases and small particles (PM10, PM2.5) that are generated in the atmosphere from fire. As we can see on the satellite gas map, point sources of gases are cities, factories and possible fires, as well as wind-blown gases.

From the data from satellites, we find the coordinates of new gas sources, these are possible fires.

We are looking for temperature, humidity and wind data at a given place and time.

How We Used Space Agency Data in This Project

We take these gases from the Copernicus satellite. With the help of api copernicus, we downloaded the data archive on the territory of Ukraine. Data consists of time slices of CO2 gas maps and combustion results - fine particles PM10, PM2.5. The time intervals with which the gas images were taken is 1 hour.

Project Demo

https://drive.google.com/file/d/1stAhkxnunObDtJ6z2HUa82xGWd0s7E0Q/view?usp=sharing

Data & Resources

We have used copernicus satellites.

Judging
This project was submitted for consideration during the Space Apps Judging process.