bCreatiq Lab: Vision AI Smart Glasses | Edge-Computing Hardware Prototype Role: Lead AI Hardware ...bCreatiq Lab: Vision AI Smart Glasses | Edge-Computing Hardware Prototype Role: Lead AI Hardware ...
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bCreatiq Lab: Vision AI Smart Glasses | Edge-Computing Hardware Prototype
Role: Lead AI Hardware Engineer & Computer Vision Developer
Category: Edge AI, Hardware Prototyping, Computer Vision, Embedded Systems
A lightweight, privacy-first wearable Smart Glasses prototype designed to process real-time Computer Vision models entirely on the edge (on-device processing) for zero latency and maximum privacy.
Key Features & Technical Highlights
Edge AI & Zero-Cloud Latency: Processes neural networks directly on local hardware without sending video feeds to external cloud servers, guaranteeing zero latency and data privacy.
Real-Time Object & Text Detection: Runs lightweight computer vision models (such as YOLOv8-Nano) to identify objects, text, and environmental data directly within the wearer's field of view.
Micro-HUD Projection Integration: Engineered to project critical Heads-Up Display (HUD) telemetry and visual cues directly onto the lens.
B2B Enterprise Applications: Purpose-built prototype for warehouse inventory tracking, security surveillance, and accessibility assistance.
Hardware & Technical Specifications
Processing Unit (MCU): ESP32-S3 Dual-Core 240MHz Processor
Memory & Storage: 8MB PSRAM for real-time frame buffering
Camera Sensor: OV2640 2MP High-Efficiency Module
Power Architecture: 3.7V LiPo 500mAh Rechargeable Setup
AI Model & Performance: YOLOv8-Nano (24.5 FPS, ~42ms inference time, Edge mode)
Results & Impact
Cloud Independence: Proves that high-speed computer vision can run on compact microcontrollers without active internet connectivity.
Hardware-Software Integration: Successfully bridges deep learning software architecture with physical wearable circuitry.
 
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