Cooling Pump Detection Dataset

#Image Classification #Object Detection #Anomaly Detection #Industrial Inspection #Quality Control #Fault Detection
  • 25000 records
  • 3.2G
  • JPG/PNG/JSON
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-03-11

AI Analysis & Value Prop

The Cooling Pump Detection Dataset aims to address the challenges in monitoring the performance of cooling systems in industrial settings. Currently, many industries face issues with inefficient cooling system operation, leading to equipment failures and increased maintenance costs. Existing solutions often lack the precision required for real-time monitoring and fail to detect anomalies early enough. This dataset is designed to specifically tackle the technical problems of identifying critical components in cooling systems through image analysis. Data was collected using high-resolution cameras in controlled environments, ensuring clarity and detail. Quality control measures include multiple rounds of annotation, consistency checks among annotators, and expert reviews to ensure high-quality labels. The dataset is organized in JPEG format for images, each linked with metadata regarding labels and timestamps.

Dataset Insights

Sample Examples

d1add223**.jpg|1224*1632|282.75 KB

cea655be**.jpg|1224*1632|229.22 KB

e6da6a76**.jpg|1885*1060|264.55 KB

a1b3b0d8**.jpg|1242*887|46.54 KB

40c20210**.jpg|1600*1600|335.70 KB

Technical Specifications

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

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Cite this Work

@dataset{Mobiusiundefined,
  title={},
  author={Mobiusi},
  year={undefined},
  url={https://www.mobiusi.com/datasets/24f05ebef8c5d69046b3d3261ec7cbec},
  urldate={},
  keywords={},
  version={}
}

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