Inspiration

To better understand what neurodivergent might want to avoid within a college campus when they are feeling anxious, stressed, neutral or happy.

What it does

Our project uses FER technology in order to determine the mood of a neurodivergent person. After determining the mood of the person, the model then suggests the best route through Temple University's campus in order to avoid various stress-inducing environmental factors (such as noise, light and construction zones).

How we built it

We built it using Java and React + Vite for the frontend work in order to display the Google Maps API for the user, offering an interactive map of Temple University, including where noise and light pollution might bt the highest. For the backend, we integrated a robust handling of Python and DeepFace for the backend data sets and error handling, while using DeepFace for FER.

Challenges we ran into

Struggle in organizing the team and determining a project. We also had a difficult time adapting to new technology (including the FER), but were able to overcome it through various research on the different interfaces.

Accomplishments that we're proud of

We are proud of the fact that the DeepFace API integrates seamlessly with our frontend and is able to detect the mood of a person just through the lens of their camera. We are also proud that we were able to implement Google Navigation and Maps API, which gives the user a chance to traverse the area of Temple University with an interactive map.

What we learned

We learned about the new technologies within DeepFace and React, and were able to implement a better understanding of both the DeepFace and Google Maps API through thorough research.

What's next for MindScape Compass

Make it more widely available for all neurodivergent students in other colleges that might struggle with the same issues as living in a busy and loud city such as Philadelphia.

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