MEEPS

Inspiration

There are about 81 million people nationwide that suffer from a pollen allergy. Being one of them, I would like to know when and where it is best to go and enjoy my afternoons outside in the warm spring weather. However, I have no information if outside has an abundance of pollen that would trigger my allergies or not. We wanted to expand on the idea of providing our users with pollen allergies a way to be informed about the pollen in the air. Our inspiration was then to provide users with health conditions that have an environmental vulnerability, a preventative defense so that they may be informed about the environment around them.

What it does

First, users input information that the app needs to give them personalized suggestions along with the most relevant recommendations. Most notably, this includes their age, location, and any relevant physical conditions that may affect their environmental vulnerability. To preserve trust, security, and anonymity, we do not persist any of this user data.

Given this input, we create a heatmap showing the severity of relevant environmental risks. Additionally, we give the user a detailed but clear explanation of the risks that they may incur so that they can take the proper precaution, keeping our users healthy and safe.

How we built it

This app was primarily built using a React-Tailwind frontend with a Spring Boot backend using Maven Apache. This app was primarily made possible by utilizing a variety of APIs, including the Meersens API for getting up-to-date environmental data/risks, the google maps api for location, geocoding, and mapping.

Challenges we ran into

Most of our challenges for this application involved having to learn a multitude of frameworks and APIs and get them to work together in one cohesive app. For example, before stumbling across Meersens, it took a lot of searching to find an api that was both intuitive and free to use while giving us all of the data that we needed to map out. Additionally, it was difficult to get certain APIs working, as they often involved a lot of communication between front end requests and backend endpoints. Our biggest challenge was creating a functional heatmap that showed users their relevant risks in a meaningful way.

Accomplishments that we're proud of

We are immensely proud that we were able to create an app that helps to solve a meaningful goal. We were able to combine varying levels of experience and areas of expertise to learn from each other while performing our specific roles. What we are most proud of is that we worked together to create and execute our idea in a way that was fun, insightful, and incredibly rewarding.

What we learned

We learned how different health conditions are vulnerable to our environment. This gave all of us insight into being more considerate for environmental health in our community. Additionally, those of us that were new to Spring boot learned more about the framework. The crunch time forced us to develop new skills regarding the connection and understanding of frontend and backend, how Spring boot backend functions and many specific edge cases in each framework.

What's next for MEEPS

Future plans would include a more ambitious number of conditions listed, pulling from an API or dataset with a bigger sample size than our test cases so that all clients can utilize MEEPS. The OpenAI API would be sourced to provide users with personalized recommendations regarding education about the environmental pollutants the software deems users susceptible too. The app would also be able to save users, persist certain data and streamline the input form experience for clients.