Inspiration
RealityShift was inspired by the transformative potential of immersive technologies like VR and AR to create realistic, hands-on learning experiences. Our goal was to bridge the gap between theoretical knowledge and practical skills, providing users with virtual training that feels as real as the physical world.
What It Does
RealityShift combines VR and AR to offer realistic training simulations for fields such as medicine, engineering, and the arts. Users can practice complex tasks, visualize 3D models, and collaborate with others in an interactive environment, all tailored to real-world applications.
How We Built It
RealityShift was developed using:
- Languages/Frameworks: Unity and C# for VR/AR functionality and React Native for mobile compatibility.
- Machine Learning Models: TensorFlow for real-time user feedback and performance tracking.
- Platforms: Meta Quest 3 for VR, Snap AR for mobile AR.
- Cloud Services: AWS for data synchronization across devices.
Challenges We Ran Into
Integrating VR and AR to ensure a seamless experience was a technical challenge. We also addressed performance issues to ensure smooth simulations in high-detail environments.
Accomplishments That We’re Proud Of
We’re proud of developing an XR solution that offers adaptable training for various fields. The app’s immersive design allows users to engage in realistic training scenarios, enhancing learning outcomes in a way that traditional methods cannot.
What We Learned
Building RealityShift taught us valuable lessons about optimizing XR experiences for different user needs. We also deepened our understanding of balancing immersive graphics with real-time interactivity, which is crucial for a smooth user experience.
What’s Next for RealityShift
Our next steps include adding more training modules, enhancing multi-user collaboration, and exploring AI-driven adaptive learning features. We aim to partner with educational institutions to test RealityShift in real-world training programs.
Built With
- amazon-web-services
- c#
- javascript
- meta
- react
- snap
- tensorflow
- unity
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