Platform Structure Crack Detection Dataset
#Target detection #image recognition #Transportation monitoring #structure detection #safety evaluation
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-03-19
AI Analysis & Value Prop
The current transportation industry faces issues with infrastructure aging and safety hazards, particularly in the detection of platform structure cracks. Traditional manual detection is inefficient and inaccurate. Existing solutions often rely on manual inspections, which struggle to achieve high frequency and coverage. This dataset aims to help researchers and developers train more accurate automatic detection models by providing high-quality crack detection image data. The dataset contains 5000 images of platform cracks from various transportation environments. Data collection used high-definition cameras under different lighting and weather conditions to ensure diversity. Quality control measures include multiple rounds of annotation and expert review to ensure consistency and accuracy in labeling. Data is stored in JPG format, organized by image ID for easy access and processing.
Dataset Insights
Sample Examples
07737491**.jpg|1920*2560|639.95 KB
7bf98b1d**.jpg|1920*2560|548.46 KB
7b28d86a**.jpg|1920*2560|825.19 KB
5c923da8**.jpg|1920*2560|842.11 KB
88d5e897**.jpg|1920*2560|461.04 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| crack_type | string | Identifies the type of crack present in the platform structure, such as hairline crack, longitudinal crack, etc. |
| crack_location | string | Identifies the specific location of the crack on the platform structure. |
| crack_length | float | Measures the length of the crack in the platform structure, in meters. |
| crack_width | float | Measures the width of the crack in the platform structure, in millimeters. |
| crack_severity | string | Assesses the potential impact of the crack on the platform structure, categorized as minor, moderate, or severe. |
| crack_pattern | string | Describes the pattern and configuration of the crack, such as mesh or parallel. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What is the platform structure crack detection dataset?
- The platform structure crack detection dataset focuses on the automatic detection of cracks in platform structures as an object detection dataset.
- What is the use of the platform structure crack detection dataset?
- The dataset is used for safety monitoring and assessment in the transportation sector, helping detect cracks in platform structures.
- What data modality is used in the platform structure crack detection dataset?
- The dataset uses images as its data modality.
- How does this dataset enhance safety in the transportation industry?
- By automatically detecting cracks in platform structures, potential safety hazards can be identified early, enhancing safety in the transportation industry.
- Why is crack detection in platform structures important?
- Monitoring cracks can prevent structural failures and major accidents, ensuring the safety and reliability of transportation systems.
Can't find the data you need?
Post a request and let data providers reach out to you.
Get this Dataset
Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Platform Structure Crack Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/15b5a964af9bb164a430035783ce5c2f?dataset_scene_id=1},
urldate={2025-09-15},
keywords={crack detection, target detection dataset, transportation safety, image recognition, transportation monitoring},
version={1.0}
}Using this in research? Please cite us.
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder
placeholder