Inspiration
We witnessed the recent fires that have devastated communities of Los Angeles. Upon realizing that one of the driving factors was the dry and hot weather, we thought to ourselves, "How can we warn people of their location’s risk of wildfires?"
What it does
Our program takes in sensory input to determine the area's humidity and temperature. Then, it compares that information with the historical rainfall and wind speeds of the location to determine the risk of a wildfire.
How we built it
We used the microchip ESP32 in conjunction with the DH11 sensor to sense the humidity and temperature. We used Arduino to collect the information. That program was then put into the Python backend of our website, which has a React.js and Tailend front end.
Challenges we ran into
All of us were Arduino beginners, so there was a big learning curve in using the application and wiring the hardware.
Accomplishments that we're proud of
We managed to combine hardware with our React.js website, even though we were told they had bad compatibility.
What we learned
We learn that anything is possible if you put your mind in it. What matters most is your effort to improve and use the resources around you.
What's next for FireFight
Improving the user-interface and explaining the risk factor calculation.
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