Road Speed Bump Damage Scene Image Dataset

#Object detection #image classification #Traffic monitoring #road safety #intelligent transportation
Records
5000 records
Size
1.5G
Format
JPG/PNG/JSON
Provider
MOBIUSI INCMOBIUSI INC
Updated
v1.02026-11-05
AI Analysis & Value Prop
The current transportation industry faces traffic safety hazards caused by damaged speed bumps, which often lead to accidents and traffic congestion. Existing solutions mostly rely on manual inspection, which is inefficient and prone to errors. This dataset aims to improve the efficiency and accuracy of speed bump damage detection through image recognition technology. The dataset consists of images of damaged speed bumps in various environments, captured using high-resolution cameras under different lighting and weather conditions. During data collection, quality control measures such as multiple rounds of annotation and expert review were adopted to ensure the accuracy and consistency of the data, resulting in a well-annotated image dataset. Data is stored in JPG format with a clear structure, facilitating subsequent processing and analysis.

Overview

Dataset Insights

Preview

Sample Examples

e8eede10**.jpg|3072*4096|2.81 MB

62476da6**.jpg|3072*4096|3.29 MB

dd406f80**.jpg|4096*3072|2.67 MB

748b650e**.jpg|4096*3072|2.64 MB

4c6da6f8**.jpg|3072*4096|2.98 MB

Schema

Technical Specifications

file_namestringFile name
qualitystringResolution
damage_typestringThe specific type of damage to the speed bump, such as cracks, depressions, etc.
damage_severitystringThe severity of the damage condition, such as minor, moderate, or severe.
surface_materialstringThe type of material on the speed bump surface, such as asphalt or concrete.
lighting_conditionsstringThe lighting conditions during the photo capture, such as daytime, nighttime, or cloudy.
weather_conditionsstringThe weather conditions at the time of image capture, like sunny, rainy, etc.
road_typestringThe type of road where the speed bump is located, such as urban road or highway.
traffic_densitystringThe traffic density on the road at the time of capture, such as high or low.
damage_locationstringThe specific location of the damage on the speed bump, such as left, center, or right.
image_qualitystringThe quality of the image, such as good, blurry, etc.
vegetation_coverbooleanWhether there is vegetation cover around the speed bump.

Trust

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

FAQ

Frequently Asked Questions

What is the Road Speed Bump Damage Scene Image Dataset?
The Road Speed Bump Damage Scene Image Dataset is a collection of images used for detecting and analyzing the damage to road speed bumps, aiding in object detection research in the transportation sector.
What fields of research is this dataset suitable for?
This dataset is suitable for the transportation field, especially for research involving road infrastructure monitoring and maintenance.
How can this dataset be used to detect damage to road speed bumps?
Target detection algorithms such as YOLO and Faster R-CNN can be trained on this dataset to detect and identify damage to road speed bumps.
What are the applications of image data in road traffic research?
Applications of image data in traffic research include vehicle detection, road sign recognition, and infrastructure condition monitoring.
How does this dataset help improve road safety?
By detecting and identifying damage to speed bumps, timely repairs can be made, which helps improve road safety and prevent traffic accidents.

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Cite this Work

@dataset{Mobiusi2025,
  title={Road Speed Bump Damage Scene Image Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/80998136b59878e59c0e56f8a6614abe?dataset_scene_id=1},
  urldate={2025-09-15},
  keywords={speed bump dataset, object detection, traffic safety, image recognition},
  version={1.0}
}

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