Orion-The-Lab/wooden_window_factory_01_enriched_v2

Real industrial data, AI-ready for Physical AI

ORION WWF1 – Certified Sample Pack v2.0 (Enriched)

Version	Status	Sector	Pipeline
v2.0-Enriched	🟢 Level 3 Certified	Industrial-Manufacturing	Orion Unified V5.2

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🌟 The Evolution: Beyond Anonymization

The ORION WWF1 v2.0 Enriched pack represents the professional evolution of our baseline industrial dataset. While previous versions focused on privacy-first anonymization, v2.0 transforms raw video into actionable, multi-layered intelligence for Physical AI.

This pack includes 10 representative clips from a high-intensity wood-processing facility, now featuring Certified Human-in-the-Loop (HITL) annotations across four distinct enrichment layers: Safety Compliance (PPE), Activity Recognition (HAR), Industrial Environment (Physical AI), and Machine Learning Detection (COCO).

📸 Visual Preview (Certified Annotations)

Clip SRC_021	Clip SRC_029	Clip SRC_039
PPE & HAR Audit	Physical AI Context	Operational Logic

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1. Dataset Summary & Mission

ORION WWF1 is a specialized dataset designed for the next generation of Physical AI and Industrial Safety models. It captures authentic, complex worker-machine interactions in a Wooden Window Factory (WWF1).

• Mission: To provide high-fidelity, privacy-compliant data for training models that understand complex industrial workflows, hazardous environments, and safety protocols.
• Enrichment: Every frame is enriched with spatial and temporal metadata, audited by human experts to ensure "Zero False Negative" reliability and absolute privacy.
• Certification: Every asset is Level 3 Certified, meaning it has passed a dual-pass AI anonymization process followed by a 100% manual human audit.

2. Enrichment Layers (The "Multi-Layer Stack")

🟢 Layer 1: HAR (Human Activity Recognition)

Full temporal sequences of worker actions, essential for cycle-time analysis and workflow optimization.

• Format: har_annotations.csv
• Labels: cutting_wood, carrying_object, assembling, operating_machine, standing_idle, walking, inspecting, cleaning.
• Accuracy: Audited at 1.0s temporal resolution with precise start/end timestamps.

🔵 Layer 2: PPE (Safety Compliance)

Multi-zone equipment verification per worker, compliant with international HSE standards.

• Format: ppe_summary.csv + compliance_report.html
• Zones Monitoring: Head (Hardhat), Eye (Glasses), Hearing, Respiratory, Hand (Gloves), Body (Vest), Legs, Foot (Safety shoes).
• Standard: 8-category compliance audit (YES / NO / HIDDEN).

🟣 Layer 3: PHYSICAL AI (Environmental Context)

Deep semantic understanding of the industrial workspace for robotics and digital twin training.

• Format: physical_ai_environment.json
• Data: Machine types, floor conditions (concrete), navigation hazards, camera POV parameters (height/angle).
• Geography: Documented industrial hub in Romania.

🟡 Layer 4: ML TRAINING (COCO Annotations)

High-quality keyframes for object detection and computer vision training.

• Format: coco_annotations.json
• Details: 310 certified keyframes with high-density bounding boxes.
• Privacy: All frames are extracted after anonymization to guarantee 100% privacy compliance.

3. Dataset Structure (v2.0 Premium Layout)

ORION_WWF1_v2.0_ENRICHED/
├── ORION_WWF1_SAMPLES_v2.zip  # Single-click download for the full pack
├── samples/                   # Final MP4 Deliverables (1080p, Dual-Pass Anonymized)
├── enrichments/               # 🆕 All Intelligence Layers (CSV, JSON, HTML)
│   ├── har_annotations.csv    # Activity sequences
│   ├── ppe_summary.csv        # Worker safety records
│   ├── physical_ai_environment.json # Scene context
│   └── coco_annotations.json  # ML-ready Bounding Boxes
├── previews/                  # High-resolution visual thumbnails
├── integrity/                 # SHA-256 Master Manifest & Checksums
├── metadata/                  # Unified Field Specs & Pipeline Schema
├── DATASHEET.md               # Technical Deep-Dive & Ethics
├── METHODOLOGY.md             # Dual-Pass Anonymization & HITL Process
└── README.md                  # This documentation

4. Collection & Methodology

Data was collected using calibrated industrial cameras during active production cycles.

• Environment: Real woodworking factory (high ambient noise, industrial dust, variable lighting).
• Anonymization: Our proprietary Dual-Pass Pipeline (V4.2 Industrial) applies irreversible Gaussian Anonymization to all human subjects, ensuring zero-leak privacy.
• Verification: Secondary scan for residual leaks using Vertical/Horizontal Flip TTA.

5. Annotation & HITL Process

Unlike purely automated datasets, the ORION v2.0 utility follows our proprietary Adjudicator Workflow:

1. AI Predetection: Specialized models propose initial BBoxes and Activity segments.
2. Human-in-the-loop (HITL): 100% manual review and correction of every single frame and sequence by industrial analysts.
3. QA Certification: Final signature verifying zero-leak privacy and 100% annotation integrity.

6. Certified Feature Metadata

Feature	Status	Specification
Clip Count	10 Clips	HD 1080p, 59.94 fps
Anonymization	🟢 Dual-Pass	Faces & Heads (Irreversible Blur)
BBox Annotations	✅ Included	Professional COCO JSON format
PPE Detection	✅ Certified	8-Zone Compliance Audit
HAR Actions	✅ Certified	Temporal localization (HITL verified)
Integrity	✅ Verified	Full SHA-256 Recursive Manifest

7. Use Cases

• Safety Analysis (HSE): Building models for automated safety non-compliance alerts.
• Production Efficiency: Cycle time analysis and bottleneck identification.
• Robotics & Digital Twins: Training autonomous agents to navigate and interact with industrial assets.

8. Integrity & Licensing

• Integrity: Every file is signed via SHA-256 (see integrity/manifest.sha256).
• License: Distributed under the ORION Sample Data License (v2.0 Enriched). Commercial R&D use permitted.

🚀 About ORION ORION – Industrial AI Data Lab is the bridge between industrial privacy and AI performance. We deliver "Small Data with Big Impact" for the manufacturing sector.

Explore more: orion-the-lab.com | LinkedIn