Early Wildfire Detection

The Project

What is a Wildfire? Wildfires are basically uncontrolled fires that happen in a forest and can be able to get out of control immediately. Why do we need to prevent it from happening? We need to help stop wildfires because there are different greenhouse gasses that are being released into the atmosphere and it helps cause climate change. Another reason is because wildfires can get out of control rapidly and can damage more things at once. For example, it can burn down houses and animals much quicker. I believe that the smoke from the wildfires can pose health risks to elderly people and young aged kids that might have lung or heart problems. How am I going to solve the problem I built a wildfire detection device that will predict if a wildfire will happen by using the data from using temperature, humidity, gas, and air pressure. Based on that data, it can be able to predict the situation and can be able to alert the authorities before a wildfire might happen. Demonstration In this project, instead of using temperature , humidity , and gas separately, I used this sensor board called a bme680 environmental sensor that has all of these sensors in-built along with air pressure. I used a raspberry pi and a raspberry pi Cam. The reason why I used the raspberry pi Cam is because when it is obtaining the data from the sensor board, it will also get a picture of the surrounding area so that they can be able to tell how dry it is by actually looking at the image. To store all that data from the bme680 and the image, I used a website called Ubibots. In Ubidots, you can be able to make a dashboard to show all that data and every 5 minutes it is sending the data from the raspberry pi to Ubidots. What else could I have done if I had more time If I had more time, then I would have added Machine Learning. The reason why it would have been much more efficient with Machine Learning is because instead of having to write hundreds of if else logics, all you have to do is get sample data and you can be able to label them for different things. For example, for one set of data you could label it based on how the data is being represented. The data would have also been more precise than just giving hard code data.


About the team

  • United States

Team members

  • Sashrika