229K+ Hours Electronic Manufacturing Gadgets Egocentric Video Dataset
Generative AI & Computer Vision
Tags and Keywords
£356,400
About
229K+ Hours Electronic Manufacturing Gadgets Egocentric Video Dataset
Description
The 229K+ Hours Electronic Manufacturing Gadgets Egocentric Video Dataset is a high-quality collection of first-person (egocentric) videos capturing real-world electronic manufacturing, assembly, inspection, testing, and production workflows. Recorded from a wearable camera perspective, the dataset provides an immersive view of hands-on interactions with electronic components, tools, machinery, and manufacturing equipment.
Designed for AI, computer vision, robotics, industrial automation, and embodied AI applications, this dataset enables the development of intelligent systems capable of understanding manufacturing processes, recognizing assembly actions, detecting tools and components, monitoring quality control, and improving human-robot collaboration. The dataset is suitable for training, fine-tuning, and benchmarking advanced machine learning and multimodal AI models in smart manufacturing environments.
Note: The listed price applies to the specified initial batch of 30,000 hours of manufacturing egocentric video. Pricing for larger batches or the complete dataset library varies depending on total video duration, video quality and resolution, manufacturing task diversity, annotation complexity, number of attributes, metadata availability, camera perspective, file formats, licensing terms, and customization needs. Final pricing will be determined based on the specific dataset requirements.
Data Product Features
| Feature | Description |
|---|---|
| File Format | Video format (e.g., MP4). |
| Video Duration | Total duration of the recorded video. |
| Frame Rate (FPS) | Number of frames captured per second. |
| Camera Perspective | First-person viewpoint recorded using a wearable or head-mounted camera. |
| Manufacturing Process | Manufacturing stage captured, such as assembly, soldering, inspection, testing, packaging, or repair. |
| Electronic Components | Components visible in the video, including PCBs, chips, connectors, resistors, capacitors, cables, and sensors. |
| Tools Used | Manufacturing tools and equipment utilized during the process. |
| Human-Object Interaction | Interaction between operators and electronic components or manufacturing equipment. |
| Workstation Type | Type of production station, such as assembly line, inspection bench, testing station, or repair workstation. |
| Camera Motion | Camera movement during recording (stationary, walking, hand movement, etc.). |
Distribution
- Formats: MP4
Data Volume
- Volume: 229K+ Hours
- Media Type: High-quality egocentric manufacturing videos
- Dataset Size: The dataset size may vary depending on video resolution, duration, frame rate, file formats, compression quality, metadata availability, annotations, and dataset version.
Usage
This data product is ideal for a variety of industrial AI applications:
- Manufacturing Process Recognition: Train AI models to recognize electronics manufacturing and assembly workflows.
- Action Recognition: Identify operator actions such as soldering, assembling, testing, and inspection.
- Object Detection: Detect electronic components, tools, and manufacturing equipment.
- Quality Inspection: Develop automated visual quality assurance systems.
- Industrial Robotics: Improve robotic manipulation and collaborative robot perception.
- Human-Object Interaction: Analyze interactions between workers, tools, and electronic components.
- Smart Factory AI: Support intelligent manufacturing and Industry 4.0 solutions.
- Predictive Manufacturing Analytics: Enable AI-driven monitoring of production processes.
- Safety Monitoring: Develop systems for workplace safety and operational compliance.
- Embodied AI: Train intelligent agents to understand first-person industrial environments.
Coverage
- Geographic Coverage: Global
- Industries: Electronics manufacturing, PCB assembly, consumer electronics, industrial electronics, repair centers, and quality inspection facilities
License
CC BY 4.0 (Creative Commons Attribution 4.0 International)
AI Training Rights
InfoBay.AI ensures that all datasets are sourced, curated, and managed with proper ownership verification, licensing documentation, and data provenance records. We hold the necessary rights to license and sublicense the datasets we provide through formal agreements with our data vendors, which grant us the required permissions for commercial licensing and AI training use cases. To ensure transparency and compliance, we maintain relevant documentation and have previously shared redacted agreements for selected datasets as evidence of our data rights and licensing authority.
Data Dictionary
| Column Name | Data Type | Description | Possible Values/Notes |
|---|---|---|---|
| File_Format | String | Video format | MP4 |
| Video_Duration | Float | Duration of the video | Minutes or hours |
| Frame_Rate | Integer | Frames captured per second | 24, 30, 60 FPS |
| Camera_Perspective | String | Recording viewpoint | First-Person / Egocentric |
| Manufacturing_Process | String | Manufacturing activity | Assembly, Soldering, Inspection, Testing, Packaging, Repair |
| Electronic_Components | String/Array | Components appearing in the video | PCB, IC, Capacitor, Resistor, Connector, Sensor, Cable, etc. |
| Tools_Used | String/Array | Manufacturing tools | Soldering Iron, Screwdriver, Tweezers, Testing Equipment, etc. |
| Human_Object_Interaction | String | Interaction with components or equipment | Holding, Assembling, Connecting, Testing, Repairing |
| Workstation_Type | String | Production workstation | Assembly Line, Inspection Bench, Testing Station, Repair Station |
| Camera_Motion | String | Camera movement | Stationary, Walking, Hand Movement |
Considerations
This dataset is provided for research and educational purposes only. It contains only sample data.
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£356,400
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