sdmay24-48 • Allergy Prediction using Artificial Intelligence [Team 2]

Senior Design Team Website

Project Overview

The goal of this project is to design and build an artificial intelligence model to predict if someone has an allergy to a chemical or medicine based on simple biological information. This allows for simpler and easier allergy testing.
There are three major components to our project: a React-based front-end, a Python-based backend, and a Keras-based model. The front-end is a single-page application, which sends anonymous user or chemical data to the backend. The backend is a set of cloud functions designed to send data between the front-end and the model. It validates the data sent to ensure it is in the correct format, and puts the data in the model for a prediction. The model implements a neural network to predict whether the user data sent is similar to other patients that have allergies to certain chemicals.
Our design will be hosted on both AWS and Google Cloud to evaluate between the two platforms.

The client sends a request to the web page from a web browser. This initial web page is stored using a static web site built in React on the cloud providers. This makes the page dynamic without needing to provision new servers. Once a request is submitted through the page, it is passed on to the cloud functions which leverage serverless computing so that we do not use bulky servers for the requests. After validating and preprocessing the data, it gets passed to the model, which gives a set of predicted allergens in the form of ingredient ids. This prediction goes to the front-end, updating and displaying the result to the client in a clear view.

Team Members

Joseph Trembley

Client Lead

Joseph is a Software Engineering major minoring in Data Science. He has 6 summers of experience interning in the technology department for State Farm. In that time, he has had the opportunity to gain a deep understanding of Java, Spring Boot, and AWS. He has also achieved the AWS Cloud Practitioner certification.

Noah Ross

Team Lead

Noah Ross is a Computer Engineering major with 2 summers of experience working with UI/UX teams, and spent last summer working with John Deere. He has a interest in front end development and infotainment systems both for highway and off highway vehicles, and has spent much of his professional time learning about QML and QT.

Xerxes Tarman

Research Lead

Currently studying software engineering, I've garnered two summers of invaluable experience as a system and embedded software engineer at John Deere and Collins Aerospace. Currently, I contribute part-time to radio software development at Collins Aerospace in Huntsville

Alex Ong

Quality Assurance

Alex is a Software Engineering major and has had two internships with PayPal & Workiva. Between the two internships, he contributed to both front-end and backend projects, giving a range of full-stack industry experience. In addition, he has experience with personal and ecommerce full-stack websites.

Ella Godfrey

Scribe

Ella Godfrey is currently pursuing her studies in Software Engineering. She brings real-world experience to her academic journey, having completed an internship at Alliant Energy, where she actively contributed to the frontend development of applications, gaining valuable insights into the industry.