Every year, there are thousands of wildfires around the world resulting billions of dollars in damages to the communities impacted by this natural disaster.
Unfortunately, the rates of wildfires have been increasing significantly due to global warming. That's why we created Forest Vision to identify locations that are most susceptible to wildfires and prevent them by notifying the fire departments.
Using the wildfire dataset from the government of British Columbia for the past decade, we have been able to identify the regions with a high rate of wildfire incidents and draw a heat map using the data.
To encourage community engagement, we enable local people to take pictures of biomass and plants in forests and we use those picture to predict the chance of wildfire happening in future using Azure Computer Vision.
Also, users can see live Tweets about natural disasters that are happening at the present moment.
How we built it We used Microsoft Azure computer vision API for predicting the chance of wildfire given an image. We also used other full-stack frameworks such as React JS, Redux, HTML, CSS, Material UI.
Parsing the wildfire data for the past decade and extracting useful data was a huge challenge. Also setting up a cloud architecture was difficult and
We have created a solution to address one of the biggest natural disasters in the world and hope that apps such as Forest Vision will be able to prevent wildfires so we can protect our planet.
Charlotte is one of our team members and she has studied environmental science and using her knowledge about natural habitat preservation, our team was able to learn so much about the issue of global warming and create a solution to address that.
We plan to expand our Forest Vision to different regions of the world by gathering their natural disaster data to prevent wildfires globally.
- azure
- react
- redux
- material-ui
- google-maps
- python
- azure-functions
- azure-blob