VisionAssist is a next-generation Apple Vision Pro application that redefines spatial interaction through gesture recognition, real-time environment mapping, and AI-driven context awareness.
Built on VisionOS, it bridges the gap between human intuition and spatial computing — merging augmented reality, machine learning, and computer vision into a single immersive platform.
VisionAssist leverages the Apple Vision Pro’s advanced sensor array and VisionOS SDK to interpret user gestures, facial cues, and real-world objects. The system integrates spatial mapping, hand tracking, and scene understanding to enable natural, touchless interaction in 3D space.
Core innovations include:
- Spatial Anchoring: Persistent digital overlays attached to real-world coordinates.
- Hand Gesture Recognition: Dynamic gesture input powered by VisionOS frameworks and ML models.
- AI Context Engine: On-device neural model that predicts user intent and optimizes UI flow.
- Realtime Raycasting: Detects object boundaries for precise interaction with virtual interfaces.
- ✋ Gesture-Based Navigation — Control apps and content through natural motion and hand signals.
- 🌍 Spatial Awareness — Uses LiDAR and VisionOS spatial mapping to render AR overlays in real-time.
- 🧩 Adaptive UI Layer — Interfaces dynamically adjust based on gaze, gesture, and context.
- 🔊 Seamless Multimodal Input — Integrates gaze, gesture, and voice for a unified interaction model.
- ⚡ On-Device Inference — AI runs locally for low-latency feedback and privacy preservation.
| Component | Technology |
|---|---|
| Platform | VisionOS (Apple Vision Pro) |
| Language | Swift / SwiftUI |
| Frameworks | RealityKit, ARKit, CoreML, Vision |
| AI/ML | On-device CoreML models (gesture classification & object recognition) |
| 3D Rendering | Reality Composer Pro / SceneKit |
| Backend (optional) | Python / FastAPI microservice (for analytics or model updates) |
+--------------------------+ | VisionAssist (VisionOS) | +-----------+--------------+ | v +-----------+--------------+ | Vision + CoreML Engine | | - Gesture Recognition | | - Scene Understanding | +-----------+--------------+ | v +-----------+--------------+ | RealityKit UI Renderer | | - 3D Overlays | | - Spatial Anchors | +-----------+--------------+ | v +-----------+--------------+ | Backend API (optional) | | - Data sync / analytics | +--------------------------+
- macOS 14.0+ with Xcode 15+
- Apple Vision Pro device or VisionOS simulator
- VisionOS SDK installed via Xcode
# Clone the repository
git clone https://github.com/yourusername/VisionAssist.git
cd VisionAssist
# Open the Xcode project
open VisionAssist.xcodeproj
# Build & deploy to Vision Pro / VisionOS Simulator
📈 Impact
Designed and prototyped under HackHarvard 2025, demonstrating real-world applications of spatial AI and mixed reality.
Showcases how Apple Vision Pro can revolutionize education, accessibility, and productivity through gesture-first interaction.
Developed with a focus on low-latency UX, energy efficiency, and on-device ML inference.
🧑💻 Team & Credits
Developer: Gary Samuel, Eason Ying, Kyle Kelly, Nancy Pazzi
Event: HackHarvard 2025 — Harvard University
Category: Spatial Computing / AI Interaction
Location: Cambridge, MA
🎓 HackHarvard Prestige
This project was conceptualized and built during HackHarvard 2025, one of the world’s most prestigious university hackathons.
It embodies the event’s mission — innovation through interdisciplinary technology, merging AI, AR, and human-centered design to define the future of spatial computing.
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Would you like me to make a **README variant** focused more on **“pitch-style storytelling”** (like what you’d show HackHarvard judges during demo day — elegant, slightly marketing-driven, and visually structured)?
That version reads like a **startup launch page**, not just a technical doc.