We have developed a solution that crosses satellite data with open data and data sent by users to predict and combat forest fires, as well as providing variables that assist in predicting economic and ecosystem impacts;

Our solution is important because we got in touch with those involved in this fight and we understand their pain and the reason why current solutions have no impact.

We hope to achieve better effectiveness in fighting forest fires by promoting contact between the brigades and better fire detection and location.

Currently in Brazil and in the World, applications involving satellite data are centralized in the hands of institutions and government, thus delaying the decision-making of the brigadiers and the understanding of the data.

From the information provided to the software by crossing data from Landast 7 and 8 satellites, GEOS, FIRMS and MOPITT and data from the HG Weather api, we developed a mobile application model.

The app has a map that will inform you in as close to real time as possible:

- Showing the location of the fire based on images and satellite data provided by NASA and other “Open Sources” as CSA Resources from the coordinates.

- pointing the fire brigades and fire brigades near the fire.

- Suggesting the easiest route to the location (through topographic knowledge of the region's residents). And if it is a place of recurring fires this route will be saved in a database.

- Location of the brigadiers who are working in the combat.

- Location of communities that are within the area foreseen for the advance of the fire.

The app will also perform:

- Prediction of fire progress in a given time, using machine learning (through data such as temperature, rainfall, vegetation density, local relief winds and fire intensity);

- Classification of fire severity;

- Adequate distribution of players, for a more effective combat;

- The availability of a chat to facilitate communication between combatants and send relevant information about the fire, including an “emergency button” option where anyone can report the start of a fire outbreak by sending an image captured by application itself (avoiding fraud or “false alarm”);

- Sending SMS to all brigade members in the region and people in a risk area, as well as notification of high fire risk;

- Availability of data to assist in the calculation of damages for institutes that operate in the recovery of the site;

- Through our external server that will process A.P.I's data from Geostationary Satellites, Level of CO in the atmosphere and Heat from the surface, alerts will be issued in a simple way for the Application of easy access and understanding

1. Forest fire risk prediction is based on the prevailing forecast index in each country.

In the case of Brazil, the most effective is the Angstron index, calculated based on temperature and relative humidity.

B = 0.05H - 0.1 (t-27)

B - angstron index

h - relative humidity in%

T - temperature in ºC

high <= 2.5 <moderate <3.0 <= low

With the calculation of the index we can predict future fires, as well as having an important variable for studies of the cause of the fire.

2. The classification of the fire is based on the intensity of the fire;