FireFall
About FireFall
What is FireFall?
FireFall project aims at proactively predicting potential fires in various US zipcode based on existing weather conditions and other factors described later. In this project, the FireFall team were able acquire some data from Kaggle related to weather. However, the team's research found that insufficient; hence, added two more essential factors: first, native animal concentration to each region second, number of campers in the area.
The FireFall team, developed a risk score (from 1 to 10) based on the above data, where 10 is the highest risk. Due to lack of real data, the team wrote a simulation engine in python to randomly generate data that feeds to the ratinng engine. all data is stored in postgres relational database and displayed in realtime (set refresh rate) in grafana. the team also integrated into ARCGIS API to zoom on the area of highest fire risk.
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FireFall is a program that uses open source databases, stored in SQL Postgres. Also using data we found from wildlife and their interactions with forest fires, FireFall can help with the process of finding the risk factor for a fire. Based on the analysis gathered from the open source data set, we can show the likelihood of a wildfire in the area based off that area's zip code.
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Map created with ArcGIS API
What tools/data did we use?
The tools and data that we used were open source databases from zip codes from data.gov. Kaggle provided us with data based on weather, rainfall, wind, Fine Fuel, Moisture Code(FFMC), Duff Moisture Code(DMC), Drought Code(DC), and Initial Spread Index(ISI). Most of the code was written using Python, and importing the 'psycopg2' driver library to access the postgres relational database server and manipulate data. Also, python was used for analysis, simulation and rating. We implemented the ArcGIS API to include maps which update based on the risk factor which on its own required us to use HTML, PHP, and JavaScript. Due to an insufficient amount of data found from the open source databases, we had to use custom data for animals, campers, and their relation with forest fires.
What does it do?
Data example from Grafana
Using Grafara, the tables are produced and update based on a time interval. In a separate html link, the map will be produced, which is connected to the Grafara data, and also updates. Back in Grafara the risk factors are also displayed, showing the likeliness of a forest fire from a scale of 0-10.
How will it impact the world?
Our project can impact the world by making people much more effective in knowing when there is a forest fire and much quicker in trying to stop them when they happen and even before they happen. We also believe that this project will emphasize the factor of climate change and its effects on the world's forests, and how it affects people too by destroying homes and food supplies.
Example of code used in project
What is our experience with this project?
For us, this was a very new topic and seemed like a difficult task to overcome. Having come from a background in C++ and Java, Python, and SQL was a new experience, especially working with all these new API's for the challenges, which was difficult to do. Implementing the ArcGIS API was difficult because in order to make data from it work, we needed to use JavaScript, which we do not know.