clip_id stringclasses 10
values | agent_id stringclasses 5
values | start_time_sec float64 0 30 | end_time_sec float64 1 31 | activity stringclasses 8
values |
|---|---|---|---|---|
SRC_021_t000060_000090 | worker_03 | 0 | 1 | walking |
SRC_021_t000060_000090 | worker_02 | 0 | 1 | inspecting |
SRC_021_t000060_000090 | worker_04 | 0 | 1 | walking |
SRC_021_t000060_000090 | worker_01 | 0 | 6 | carrying_object |
SRC_021_t000060_000090 | worker_03 | 6 | 7 | carrying_object |
SRC_021_t000060_000090 | worker_04 | 6 | 7 | assembling |
SRC_021_t000060_000090 | worker_02 | 6 | 7 | carrying_object |
SRC_021_t000060_000090 | worker_04 | 12 | 13 | working |
SRC_021_t000060_000090 | worker_03 | 12 | 13 | working |
SRC_021_t000060_000090 | worker_04 | 18 | 24 | standing_idle |
SRC_021_t000060_000090 | worker_01 | 12 | 13 | walking |
SRC_021_t000060_000090 | worker_02 | 12 | 18 | assembling |
SRC_021_t000060_000090 | worker_04 | 30 | 31 | walking |
SRC_021_t000060_000090 | worker_03 | 24 | 30 | assembling |
SRC_021_t000060_000090 | worker_05 | 6 | 30 | assembling |
SRC_022_t000030_000060 | worker_01 | 0 | 24 | carrying_object |
SRC_022_t000030_000060 | worker_01 | 30 | 31 | assembling |
SRC_022_t000030_000060 | worker_02 | 6 | 30 | operating_machine |
SRC_024_t000030_000060 | worker_01 | 0 | 6 | cleaning |
SRC_024_t000030_000060 | worker_01 | 12 | 13 | walking |
SRC_024_t000030_000060 | worker_02 | 0 | 30 | cleaning |
SRC_024_t000030_000060 | worker_03 | 0 | 12 | cleaning |
SRC_025_t000030_000060 | worker_01 | 0 | 30 | cleaning |
SRC_028_t000000_000030 | worker_01 | 6 | 7 | inspecting |
SRC_028_t000000_000030 | worker_01 | 12 | 13 | standing_idle |
SRC_028_t000000_000030 | worker_01 | 18 | 30 | working |
SRC_029_t000030_000060 | worker_01 | 0 | 30 | cleaning |
SRC_031_t000060_000090 | worker_01 | 0 | 12 | carrying_object |
SRC_031_t000060_000090 | worker_02 | 12 | 13 | working |
SRC_031_t000060_000090 | worker_03 | 18 | 19 | inspecting |
SRC_031_t000060_000090 | worker_01 | 18 | 19 | walking |
SRC_031_t000060_000090 | worker_02 | 24 | 30 | standing_idle |
SRC_031_t000060_000090 | worker_03 | 24 | 25 | standing_idle |
SRC_039_t000030_000060 | worker_01 | 18 | 19 | walking |
SRC_039_t000030_000060 | worker_01 | 24 | 25 | carrying_object |
SRC_039_t000030_000060 | worker_01 | 30 | 31 | walking |
SRC_086_t000060_000090 | worker_01 | 0 | 30 | carrying_object |
SRC_088_t000000_000030 | worker_02 | 6 | 7 | assembling |
SRC_088_t000000_000030 | worker_02 | 12 | 13 | cleaning |
SRC_088_t000000_000030 | worker_01 | 0 | 18 | cleaning |
SRC_088_t000000_000030 | worker_01 | 24 | 25 | inspecting |
SRC_088_t000000_000030 | worker_01 | 30 | 31 | cleaning |
SRC_088_t000000_000030 | worker_02 | 18 | 19 | walking |
Real industrial data, AI-ready for Physical AI
ORION WWF1 β Enriched Sample Pack v1.5 (Physical AI Edition)
π The Evolution: Beyond Anonymization
The ORION WWF1 v1.5 Enriched pack is the professional evolution of our baseline industrial dataset. While version 1.0 focused on privacy-first anonymization, v1.5 transforms raw video into actionable intelligence.
This pack includes 10 representative clips from a high-intensity wood-processing facility, now featuring Certified Human-in-the-Loop (HITL) annotations across three distinct enrichment layers: Safety Compliance (PPE), Activity Recognition (HAR), and Industrial Environment (Physical AI).
Visual Preview (Certified Annotations)
| Clip SRC_021 | Clip SRC_029 | Clip SRC_039 |
|---|---|---|
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| PPE & HAR Audit | Physical AI Context | Operational Logic |
1. Dataset Summary & Mission
ORION WWF1 is a specialized dataset for Physical AI and Industrial Safety. It captures authentic 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.
- Enrichment: Every frame is enriched with spatial and temporal metadata, audited by human experts to ensure "Zero False Negative" reliability.
2. Enrichment Layers (The "Triple Threat")
π’ Layer 1: HAR (Human Activity Recognition)
Full temporal sequences of worker actions.
- Format:
har_annotations.csv - Labels:
cutting_wood,carrying_object,assembling,operating_machine,standing_idle,walking,inspecting,cleaning. - Accuracy: Audited at 1.0s temporal resolution.
π΅ Layer 2: PPE (Safety Compliance)
Multi-zone equipment verification per worker.
- Format:
ppe_summary.csv+compliance_report.html - Zones: Head, Eye, Hearing, Respiratory, Hand, Body, Legs, Foot.
- Standards: Compliant with industrial HSE (Health, Safety, Environment) reporting.
π£ Layer 3: PHYSICAL AI (Environmental Context)
Deep semantic understanding of the industrial workspace.
- Format:
physical_ai_environment.json - Data: Machine types ("cnc_machine"), floor conditions, navigation hazards, camera POV parameters.
- Geography: Documented industrial hub in Romania.
3. Dataset Structure (Premium Layout)
ORION_WWF1_v1.5_ENRICHED/
βββ samples/ # Final MP4 Deliverables (1080p, Anonymized)
βββ previews/ # Visual thumbnails and previews
βββ integrity/ # Master raw annotations & manifest
βββ har_annotations.csv # activity recognition sequences (HAR)
βββ ppe_summary.csv # worker safety compliance records (PPE)
βββ physical_ai_environment.json # industrial context & Physical AI metadata
βββ orion_v1.5_technical_spec.json # Unified field specifications
βββ DATASHEET.md # technical deep-dive & methodology
βββ LICENSE # usage terms (v1.5 Enriched)
βββ README.md # this documentation
4. Collection & Methodology
Data was collected using calibrated industrial POV and fixed-angle cameras during active production cycles.
- Environment: Woodworking factory (high noise, dust, variable artificial lighting).
- Privacy: Irreversible Gaussian Anonymization (V4 Pipeline) applied to all human subjects.
5. Annotation & HITL Process
Unlike purely automated datasets, the ORION Enriched v1.5 utility follows our Proprietary Adjudicator Workflow:
- AI Predetection: Automated BBox and Activity proposals.
- Human-in-the-loop (HITL): 100% manual review of every frame and sequence.
- QA Certification: Final signature verifying zero-leak privacy and annotation accuracy.
6. Certified Feature Metadata
| Feature | Status | Specification |
|---|---|---|
| Clip Count | 10 Clips | HD 1080p, 30fps (Anonymized) |
| BBox Annotations | β Included | Professional COCO JSON format |
| PPE Detection | β Certified | 8-Zone Compliance Audit (Humanified) |
| HAR Action Sequences | β Certified | Temporal Temporal localization (HITL) |
| Physical AI Context | β Included | Scene Graph & Industrial Metadata |
| Integrity | β 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
manifest.sha256). - License: Distributed under the ORION Sample Data License (v1.5 Enriched). Pro R&D use permitted.
π About ORION
ORION β 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
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