AI-Powered Technical Skills Training System

Create an end-to-end vocational training platform leveraging computer vision (YOLO/MobileNet for object detection), AR frameworks (ARCore/ARKit), and voice recognition for completely hands-free operation in workshop environments. Cover minimum 5 technical skills (plumbing, electrical work, carpentry, welding, auto repair) with at least 20 guided procedures per skill. Implement real-time technique analysis using pose estimation (MediaPipe/OpenPose) to detect incorrect tool handling, unsafe body positions, and improper techniques with <100ms latency. Build comprehensive safety system including PPE detection (helmet, gloves, goggles), hazard identification, emergency stop commands, and fatigue monitoring. Develop adaptive learning paths that adjust difficulty based on performance metrics, provide multi-modal feedback (visual overlays, audio cues, haptic alerts), and track skill progression toward industry certification standards. Include offline mode with pre-downloaded content for areas with limited connectivity, support for at least 3 languages with technical terminology, and integration with existing vocational education curricula.

The AI-Powered Technical Skills Training System Challenge aims to revolutionize vocational education by creating immersive, hands-free learning experiences for technical trades. This challenge addresses the global skills gap in essential trades while making quality technical education accessible to anyone with a smartphone.

Participants will develop comprehensive training platforms that leverage computer vision, augmented reality, and voice commands to guide learners through practical skills including plumbing, electrical work, carpentry, welding, auto repair, and other trades. The system must work in real workshop environments where users' hands are occupied with tools and materials.

The platform should provide step-by-step visual guidance overlaid on the real world through AR, using computer vision to verify correct technique and provide real-time feedback. Voice commands should enable navigation through tutorials without touching the device. The system must recognize tools, materials, and hand positions to ensure safety and proper technique.

Key features should include skill progression tracking, safety alerts, mistake detection and correction, offline functionality for core features, and support for multiple languages. The platform should adapt to different skill levels, from complete beginners to those seeking certification preparation.

Special emphasis will be placed on solutions that partner with vocational schools, include culturally relevant content, address safety concerns in hazardous environments, and provide pathways to formal certification or employment.