RU Makerspace/Makerverse

Inspiration

At Rutgers Makerspace, students and faculty frequently rely on 3D printing to bring ideas to life — from academic prototypes to personal innovation projects. However, the submission process is currently slow, manual, and often confusing. Users must know specific printer settings, materials, and file preparation steps that vary by machine, leading to errors, delays, and unnecessary staff overhead.
We wanted to make the experience smarter, faster, and more accessible — a single intelligent platform that could handle everything from file submission to cost analytics, powered by AI.

What it does

The RU Makerspace 3D Printing Portal (Makerverse) centralizes and automates the entire 3D printing process for the Rutgers community.
Users upload their 3D model (.STL or .OBJ) and a short description — and the system, powered by Google Gemini AI, automatically generates the optimal print configuration: printer type, material, color, temperature, and speed.

It also integrates:

Firebase Authentication for secure login and Rutgers NetID verification.
Snowflake SQL for real-time material cost, printer utilization, and trend analytics.
Google Cloud Storage for secure file management and render storage.

Everything connects through a React + Node.js dashboard, allowing users to track their print jobs while staff manage and approve requests in one centralized system.

How we built it

We built the backend using Express.js (Node.js) for API routing, with modular, object-oriented service layers for Gemini AI, Firebase, and Snowflake integration.
The frontend is built in React with Tailwind CSS for a responsive, Rutgers-branded design.
Data is stored locally in MySQL for development and synchronized to Snowflake SQL in production for analytics.
Firebase Authentication handles user security and access control, while Google Cloud Functions process AI model analysis and cost computations asynchronously.

Tech Stack:

Frontend: React.js, Tailwind CSS
Backend: Node.js (Express), MySQL
AI: Google Gemini API
Authentication: Firebase Auth
Analytics: Snowflake SQL
Cloud Infrastructure: Google Cloud Run + Cloud Storage

Challenges we ran into

AI Context Optimization: Training Gemini to interpret vague or incomplete project descriptions required prompt refinement and structured context mapping.
Database Integration: Synchronizing local MySQL development data with Snowflake analytics pipelines without redundancy.
Authentication Logic: Aligning Firebase user roles with Rutgers NetID standards.
Scalability: Ensuring real-time performance for potentially hundreds of active requests without overloading the API.
File Security: Handling large 3D files safely within Rutgers’ privacy and IT compliance frameworks.

Accomplishments that we're proud of

Successfully built a fully modular backend that connects Gemini AI, Firebase, and Snowflake seamlessly.
Created a working prototype that intelligently recommends print settings from a user’s 3D model and description.
Designed a scalable architecture deployable both locally and in Google Cloud.
Integrated analytics for real-time cost, usage, and efficiency tracking — the first of its kind for Rutgers Makerspace.
Developed a secure, student-friendly interface that streamlines the entire print submission process.

What we learned

How to structure AI-driven workflows within traditional backend architectures.
How Gemini API can be used to automate technical decision-making (like 3D printer configuration).
How to connect Firebase Authentication and Snowflake SQL into one coherent cloud ecosystem.
The importance of modular and consistent code patterns for collaboration and debugging.
The value of designing software that bridges both technical and non-technical users in a makerspace environment.

What's next for RU Makerspace / Makerverse

Full Deployment: Integrate directly with Rutgers Makerspace’s existing systems for live pilot testing.
Expanded AI Capabilities: Allow Gemini to provide printability analysis and error predictions.
Student Dashboard: Add project history, analytics, and material cost tracking per user.
Mobile Access: Develop a mobile-friendly PWA for real-time notifications and job approvals.
Cross-campus Integration: Extend the platform to other Rutgers campuses and departments to unify fabrication resources under one ecosystem.
Open Source Framework: Adapt the system for other universities and community makerspaces to improve global access to fabrication tools.