Inspiration

One of our teams mates (Nat) was a wildland firefighter in Northern Ontario before she made the switch to comp sci. One thing Nat noticed is that other provinces such as BC and Alberta have mobile apps to track where fires are in the province and give general information about the forest fire situation. Ontario actually doesn't have anything like that. They do have a website and an interactive map but it's not very user friendly.

What it does

Our idea- built for residents in Ontario especially NorthEast and NorthWest where the fires prevail, it would be beneficial if the app provides real-time wildfire updates, reporting tools, and a Google Maps visualization for Ontario. It also features an AI-powered forest fire behavior prediction tool for localized queries. This way anyone can stay up-to-date and have all resources in one space.

How we built it

We used Flutter to make the app, google maps API with flutter to display a map with current fires and their statuses, python for csv/excel file conversions to json and finally OpenAI API with flutter which can be used to generate a predictive image of what the fire would look like as well as prediction based answers such as "how much is the fire intensity in x?"

Challenges we ran into

Getting started was a challenge considering for all members, it was our first time creating an application, first time using flutter, first time using API's, first time using AI. Later on, combining each persons page into one application linked to a navigation menu also took time and research.

Accomplishments that we're proud of

Considering it was our first time doing everything in this project so far, we are extremely proud of 1) finishing the envisioned idea 2)having it fully functioning the way we expected 3) having fun learning the new technologies in this short span of hours

What we learned

Overall we learnt to just get started from somewhere, anywhere as even any failures are signs of learning and progress.

What's next for Wildfyre

We hope to train Wildfyre with large amounts of data found online to create a more accurate prediction and reponse model as well as look at ways to be more efficient with flutter code.

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