CosmoSpirit| Spot That Fire V3.0
Spot That Fire V3.0
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.
CosmoSpirit - we make a product, that solve a huge world problem is fire problem
Summary
On our website you can find out the likelihood of fires in a particular areaThe calculation of probability will take into account such factors as wind, temperature, humidity, the presence of thunderstorm clouds, as well as human factors such as the season and time in the cityLater, this system can be implemented in the fire services systemIf the fire risk increases, a warning will come to the fire station
How We Addressed This Challenge
We chose the direction of "Confront" and "Detect Fire"
How We Developed This Project
On the backend, we used Django + Django Rest Framework and numpy to calculate the probability of fire (mini neural network), at the front we used Vue-cli together with libraries: vue-router, vuex, axios, as well as html, css. The problems were the lack of time, and the right scales for the neural network.
How We Used Space Agency Data in This Project
Not yet, but in the future we will closely use data from satellite maps
Project Demo
Our project is useful because we warn about the fire in advance
The photo shows how a user types a given city and gets the result
Judging
This project was submitted for consideration during the Space Apps Judging process.