We're Team Arson and we're using the power of predictive modeling to combat wildfires.

Overview

Logo We're Team Arson and we're using the power of predictive modeling to combat wildfires.

Arson Map

Inspiration

There’s been a lot of wildfires in California in recent years, and a lot of the most recent wildfires have been uncontained. The government does not have the capacity to deal with such a huge amount of wildfires so it has to pick and choose which fires to bring under control. This picking and choosing should be done based on wildfire and wind data in order to minimize the damage caused by wildfires We should also prioritize mitigating fires that can spread across many counties/ have a large chance of spreading further

What it does

Our project consists of a web app with an interactive map. We represent our wildfire as a MDP and determine how at risk counties are based on the fire location(s).

How we built it

We split the project into 2 main parts: web app and AI

Website

Artificial Intelligence

  • Represent the wildfire as a MDP (Markov Decision Process)
    • States: Counties
    • Actions: Traversing Counties
    • Probability distribution: generated from wind data
    • Transition Model: generated from wind data
    • Reward function: Uniform for every county burned (prone to change if scaled up)
  • Use bellman equation to iterate through counties and propagate the fire
    • Utility values ranging between 0 and 1 represent how at risk a county is
    • Screenshot
    • Run until utility values reach equilibrium or until 100 iterations are run
    • Gamma = 0.8
  • Represent the map as a graph
    • Counties are nodes
    • Wind speeds are edges
    • Assign each county with a risk (for reward function)
    • Spawn fires on specific counties

Challenges we ran into

Our project has a pretty large scope. We needed to develop a model and integrate it with a web app. This required extensive knowledge on AWS utilities and crisp communication between team members. The machine learning portion of this hackathon was difficult as we had to decide on what type of model to use for the wildfire and how to assign reward and utility values.

Accomplishments that we're proud of

We were able to integrate the web app with the model really quickly. This was surprising since usually connecting the pieces together will have a lot of bugs. It was also Austin, Raaj, and Romuz's first hackathons and this was a fairly complex project compared to a standard web app.

What we learned

This hackathon was a first for many of us. This was the first time any of us had implemented a machine learning model and connected it to a web app.

This was my first time at a hackathon and I couldn't have asked for better teammates than Jerry, Raaj, and Romuz. I learned so much over the last two days about machine learning, data science, React, and working as a team to help tackle some of California's greatest challenges. - Austin Rivard

As a first-year student, I have learned a lot of new skill sets while working with this team. I was happy to be a member of such an agile team. I learned numerous of new concepts, such as working with AWS, writing algorithms, and the graph data structures. - Romuz Abdulhamidov

What's next for Arson

  • Scale up to entire California to generate a better map during wildfire season
  • Generate more accurate Reward values for each county burned
  • Incorporate type 2 rewards based on R(state, action)
    • Wildfire gets bigger as it burns more land
    • Wildfire gets smaller in the presence of firefighters
  • Automatically train and deploy models by integrating real-time data for wind and wildfires

Demo

Screenshot

Owner
Jerry Lee
software engineer
Jerry Lee
This cosmetics generator allows you to generate the new Fortnite cosmetics, Search pak and search cosmetics!

COSMETICS GENERATOR This cosmetics generator allows you to generate the new Fortnite cosmetics, Search pak and search cosmetics! Remember to put the l

ᴅᴊʟᴏʀ3xᴢᴏ 11 Dec 13, 2022
Feature engineering and machine learning: together at last

Feature engineering and machine learning: together at last! Lambdo is a workflow engine which significantly simplifies data analysis by unifying featu

Alexandr Savinov 14 Sep 15, 2022
Detailed analysis on fraud claims in insurance companies, gives you information as to why huge loss take place in insurance companies

Insurance-Fraud-Claims Detailed analysis on fraud claims in insurance companies, gives you information as to why huge loss take place in insurance com

1 Jan 27, 2022
Fitting thermodynamic models with pycalphad

ESPEI ESPEI, or Extensible Self-optimizing Phase Equilibria Infrastructure, is a tool for thermodynamic database development within the CALPHAD method

Phases Research Lab 42 Sep 12, 2022
Gaussian processes in TensorFlow

Website | Documentation (release) | Documentation (develop) | Glossary Table of Contents What does GPflow do? Installation Getting Started with GPflow

GPflow 1.7k Jan 06, 2023
My first Python project is a simple Mad Libs program.

Python CLI Mad Libs Game My first Python project is a simple Mad Libs program. Mad Libs is a phrasal template word game created by Leonard Stern and R

Carson Johnson 1 Dec 10, 2021
Analysiscsv.py for extracting analysis and exporting as CSV

wcc_analysis Lichess page documentation: https://lichess.org/page/world-championships Each WCC has a study, studies are fetched using: https://lichess

32 Apr 25, 2022
Open-Domain Question-Answering for COVID-19 and Other Emergent Domains

Open-Domain Question-Answering for COVID-19 and Other Emergent Domains This repository contains the source code for an end-to-end open-domain question

7 Sep 27, 2022
Finding project directories in Python (data science) projects, just like there R rprojroot and here packages

Find relative paths from a project root directory Finding project directories in Python (data science) projects, just like there R here and rprojroot

Daniel Chen 102 Nov 16, 2022
An ETL Pipeline of a large data set from a fictitious music streaming service named Sparkify.

An ETL Pipeline of a large data set from a fictitious music streaming service named Sparkify. The ETL process flows from AWS's S3 into staging tables in AWS Redshift.

1 Feb 11, 2022
Pandas on AWS - Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretManager, PostgreSQL, MySQL, SQLServer and S3 (Parquet, CSV, JSON and EXCEL).

AWS Data Wrangler Pandas on AWS Easy integration with Athena, Glue, Redshift, Timestream, QuickSight, Chime, CloudWatchLogs, DynamoDB, EMR, SecretMana

Amazon Web Services - Labs 3.3k Jan 04, 2023
wikirepo is a Python package that provides a framework to easily source and leverage standardized Wikidata information

Python based Wikidata framework for easy dataframe extraction wikirepo is a Python package that provides a framework to easily source and leverage sta

Andrew Tavis McAllister 35 Jan 04, 2023
Flexible HDF5 saving/loading and other data science tools from the University of Chicago

deepdish Flexible HDF5 saving/loading and other data science tools from the University of Chicago. This repository also host a Deep Learning blog: htt

UChicago - Department of Computer Science 255 Dec 10, 2022
The official pytorch implementation of ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias

ViTAE: Vision Transformer Advanced by Exploring Intrinsic Inductive Bias Introduction | Updates | Usage | Results&Pretrained Models | Statement | Intr

104 Nov 27, 2022
OpenARB is an open source program aiming to emulate a free market while encouraging players to participate in arbitrage in order to increase working capital.

Overview OpenARB is an open source program aiming to emulate a free market while encouraging players to participate in arbitrage in order to increase

Tom 3 Feb 12, 2022
BigDL - Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems

Evaluate the performance of BigDL (Distributed Deep Learning on Apache Spark) in big data analysis problems.

Vo Cong Thanh 1 Jan 06, 2022
Falcon: Interactive Visual Analysis for Big Data

Falcon: Interactive Visual Analysis for Big Data Crossfilter millions of records without latencies. This project is work in progress and not documente

Vega 803 Dec 27, 2022
PrimaryBid - Transform application Lifecycle Data and Design and ETL pipeline architecture for ingesting data from multiple sources to redshift

Transform application Lifecycle Data and Design and ETL pipeline architecture for ingesting data from multiple sources to redshift This project is composed of two parts: Part1 and Part2

Emmanuel Boateng Sifah 1 Jan 19, 2022
Data Analytics: Modeling and Studying data relating to climate change and adoption of electric vehicles

Correlation-Study-Climate-Change-EV-Adoption Data Analytics: Modeling and Studying data relating to climate change and adoption of electric vehicles I

Jonathan Feng 1 Jan 03, 2022
Techdegree Data Analysis Project 2

Basketball Team Stats Tool In this project you will be writing a program that reads from the "constants" data (PLAYERS and TEAMS) in constants.py. Thi

2 Oct 23, 2021