Wildfires contributed to large amounts of damage to countries, both in economical and environmental aspects. Extreme weathers and climate change affect vegetation water content and have further exacerbated the effects. In 2020, the combination of a long drought, extremely high temperatures, strong winds, and population growth have produced over 8,500 wildfires spreading over 1.7 million hectares, contributing to over $2 billion in losses.
There are many efforts on monitoring wildfire perimeters and locations. However, wildfires are very hard to contain - when forest fires start, they are often not noticed for a few hours to a few days.
With EasyML powerful platform, I would like to investigate if there are any parameters that can detect forest fires early on. This would ideally contribute to the early detection and timely containment of wildfires.
What it does
Machine learning models on wildfires
How I built it
I built the machine learning models with EasyML platform
Challenges I ran into
I don't have a background in statistics and machine learning, and I have never used EasyML platform before. I spent a lot of time learning basic statistics principles and how to use the platform to generate machine learning models.
Accomplishments that I'm proud of
I generated some machine learning models
What I learned
I learnt a lot about machine learning, data cleaning, and how to use EasyML platform to make ML models
What's next for PreventLab
Extend to other states and countries