FireScout| Spot That Fire V3.0
Awards & Nominations
FireScout has received the following awards and nominations. Way to go!
Spot That Fire V3.0
SafetyForest
Summary
In this project, it seeks to provide a solution to the scarce information and tools for the control and spread of forest fires in real-time, seeking to reduce the number of people affected and economic losses, among others.Based on this, SafetyForest was born, a system that, using environmental satellite data and fire records, IoT sensors, and drones with infrared cameras, allows to considerably optimize decision-making in real-time, informing the authorities and emergency teams, and in the second instance the affected population may be notified through the use of social networks, to optimize mobilization to safe areas and protect their possessions.
How We Addressed This Challenge
In general in Chile, more than 500,000 hectares are affected by different fires, where this not only affects the trees or plants but also the animals and people who live in nearby areas, consuming their homes and even claiming many lives of inhabitants. and firefighters. That is why our FireScout group is focused on developing a real-time early warning and prediction system that can help detect and anticipate a fire source and make the best decisions both in advance and in real-time while the fire develops. To develop our solution we applied technologies such as Python - C / C ++ and Golang but due to a problem with the pages that were not operational, we decided to work only with EarthData and WorldView, which if the ideal positions to install the sensors were achieved and estimated and obtain the distribution data to later enter the AI.
How We Developed This Project
Year after year we see problems related to fires that in recent times have been increasing considerably as a result of drought, temperature, and climatic changes. Fires spread rapidly in critical places where there is a high probability of fire risk, exposing people who are nearby, causing significant damage exposing health due to pollutants, exposing an entire environment within a community.
How We Used Space Agency Data in This Project
In this project, it seeks to provide a solution to the scarce information and tools for the control and spread of forest fires in real-time, seeking to reduce the number of people affected and economic losses, among others.
Based on this, SafetyForest was born, a system that, using environmental satellite data and fire records, IoT sensors, and drones with infrared cameras, allows to considerably optimize decision-making in real-time, informing the authorities and emergency teams, and in the second instance the affected population may be notified through the use of social networks, to optimize mobilization to safe areas and protect their possessions.
Project Demo
https://docs.google.com/presentation/d/1hfoLTzM7MqwcoQ0PLUHP2ZcK_54geHXCEImpYkcBCPM/edit?usp=sharing
Data & Resources
We have proposed a Three-Dimensional Sensory Triangulation (TST) algorithm based on a different point in space, where these points have a variety of sensors.
With the TST algorithm plus an interior mapping of the data networks together with the reading of different variables such as wind speed and direction, ambient temperature and humidity, and detection of a change in environmental pollution, the initial focus of the fire and predict direction, speed, temperature, and power that will spread
The position of the system that uses the TST algorithm is of a tetrahedron pyramid where the edges are formed by slave antennas in low height and the vertices in the culmination of a pivot antenna in height, this geometric formation allows us total monitoring of the area of Three-dimensional way and using triangles as connection bases between point and point results in a total encompassing of the monitored area.
According to the characteristics of the terrain, the slaves and pivots are conveniently positioned, but always maintaining the rule of the tetrahedron triangle.
Taking an average of the values delivered by the sensors plus the TST algorithm we can obtain a fairly complete reading of the analyzed sector
Also taking into account the variables of temperature, humidity, and time of year, a detailed diagnosis of the status and level of vulnerability of a possible fire source in a specific area can be delivered.
We use the NASA satellite data displayed in WorldView and delivered by EarthData, where we work with the Surface Wind Speed data delivered by Merra-2 and Thermal Anomalies delivered by: