IRA: Infection Risk Analysis
IRA is a web app that helps organizations and schools model the spread of COVID-19 and other diseases. The simulation is based on multiple factors that users can modify: human behavior (social distancing, hygiene practices, etc.), location models (office, school, mall), and preset diseases (COVID-19, SARS, Flu).
AI Agents representing people move in a realistic fashion, going into rooms, around walls, and staying still.
Not only does the web app help determine when to reopen businesses, it's also an educational tool teaching people infectious rates of several diseases and also the risks when not following proper lock-down procedures. Future and past diseases can also be inputted with a few data points, creating a simple yet realistic emulation.
Inspirations
After seeing graphs showing the spread of COVID-19, I noticed that there was a lack of helpful visuals. Being just numbers, graphs are often hard to scale or interpret for people. That's why I decided to create a browser app, allowing anyone with an internet connection to view and modify the simulation. Additionally, many organizations are having a hard time in deciding when to reopen. With this tool, universities and offices can determine the feasibility of returning to physical interactions.
What I learned
From this project, I learned how to implement simple AI Agents with pathfinding, delving in to heuristics such as A* search. I also learned how to create wall matrices and converting them into physical planes in WebGL. During research, I explored into different diseases, the categories of infection, and measurement units such as r0.
Challenges
The most challenging part of my app is the pathfinding. Determining the movements to be random yet still realistic was difficult.
How I built it
I used HTML, CSS, JS and hosted the project on Github Pages. For WebGL / graphics I used the Three.JS library, and I used the javascript-astar library by Brian Grinstead, which are all open sourced.
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