UniSphere | Devpost

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Inspiration

There is a pressing need for an innovative method of connecting with students from various parts of the campus.

What it does

Our initiative seeks to create a campus-wide platform that facilitates student connections based on their majors or enrolled courses. Moreover, it allows individuals to interact with an integrated AI subject matter expert across various fields to receive educational assistance. The chatbot's capabilities are consistently improved through ongoing interactions.

How we built it

Our frontend was developed using ReactJS, a versatile and popular JavaScript library for building user interfaces. React allowed us to create a dynamic and responsive user interface that enhances the overall user experience.

On the backend, we built a custom API system using Node.js and Express. Node.js's non-blocking, event-driven architecture enabled efficient handling of concurrent requests, while Express provided a robust framework for routing and middleware management.

To facilitate real-time communication between clients and the server, we leveraged WebSockets, ensuring instant updates and a smooth interactive experience for our users.

For data storage, we chose MongoDB, a NoSQL database known for its flexibility and scalability. MongoDB allowed us to efficiently manage and retrieve data related to user profiles, courses, and majors.

To optimize performance and reduce latency, we implemented Redis as a caching layer. Redis's in-memory data store ensured rapid data retrieval and minimized the load on our backend servers.

For certain AI-related features, we integrated Python and LLM (Large Language Model).

Lastly, our project relied on Google Cloud for hosting and various cloud services, ensuring scalability, security, and reliable uptime.

By combining these technologies, we created a robust, scalable, and feature-rich platform that delivers a seamless and enjoyable experience for our users.