Dust Cup Not Closed Detection Dataset for Vacuum Cleaners
#Image classification #object detection #fault identification #Industrial inspection #quality control #equipment maintenance
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-07-13
AI Analysis & Value Prop
In the current industrial sector, vacuum cleaners, as important cleaning equipment, can have their suction and sealing performance severely affected if the dust cup is not closed, leading to a decrease in user experience. Existing detection methods mainly rely on manual inspection, which is inefficient and prone to misjudgment. This dataset aims to enhance the detection accuracy of dust cup closure status through machine vision technology, meeting the industrial need for efficient and accurate detection. The dataset is captured using high-resolution cameras in a standard environment to ensure image quality. We ensure the consistency and accuracy of annotations through multiple rounds of labeling and expert review, and it is ultimately stored in JPG format for ease of subsequent model training and testing.
Dataset Insights
Sample Examples
86049ab0**.jpg|1280*1280|483.24 KB
6d58dc35**.jpg|2668*2000|538.38 KB
a83e4bae**.jpg|1080*1441|543.76 KB
116bcfe9**.jpg|1080*1920|439.10 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| cup_status | string | Checking whether the dust cup of the vacuum cleaner is closed. |
| confidence_score | float | The confidence score of the model's judgment on the dust cup's closed status. |
| bounding_box | string | The bounding box coordinates identifying the dust cup area, formatted as (x, y, width, height). |
| image_quality | float | The sharpness or quality rating of the picture. |
| illumination_level | float | The brightness level of lighting in the image. |
| image_clarity | float | The level of clarity of the image. |
| object_count | int | The number of objects (dust cups) detected in the image. |
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 Vacuum Cleaner Dust Cup Unclosed Detection Dataset?
- The Vacuum Cleaner Dust Cup Unclosed Detection Dataset is an image dataset used to detect whether the dust cup of a vacuum cleaner is closed.
- Which industry is this dataset mainly applied to?
- This dataset is mainly applied in the industrial sector, particularly to enhance the efficiency of industrial equipment detection.
- What type of data modality does this dataset include?
- This dataset includes image modality data.
- What is the purpose of the Vacuum Cleaner Dust Cup Unclosed Detection Dataset?
- The dataset is used to detect the status of a vacuum cleaner's dust cup, aiding in improved detection accuracy and efficiency.
- How can this dataset improve industrial detection efficiency?
- Models trained using this dataset can quickly and accurately detect equipment issues, thereby improving industrial detection efficiency.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Dust Cup Not Closed Detection Dataset for Vacuum Cleaners},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/45ca2b39bc5c706c5426f1f511680af2},
urldate={2025-09-15},
keywords={vacuum cleaner, dust cup detection, industrial dataset, image recognition, machine vision},
version={1.0}
}Using this in research? Please cite us.
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