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This is a public Edge Impulse project, use the navigation bar to see all data and models in this project; or clone to retrain or deploy to any edge device.
AI-driven HVAC Fault Diagnosis (Thermal)
About this project
This FOMO-AD visual anomaly detection model diagnoses thermal cooling malfunctions of HVAC system components based on thermal images:
- no anomaly
- anomaly
After building my visual anomaly detection model, I deployed my model as a fully optimized and customizable Linux (x86_64) application (.eim) and uploaded it to LattePanda Mu. Thus, the device is capable of diagnosing thermal cooling abnormalities based on the specifically produced thermal images by running the visual anomaly detection model without any additional procedures, reduced accuracy, or latency.
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Dataset summary
Data collected
70 itemsLabels
no anomalyProject info
| Project ID | 419123 |
| Project version | 1 |
| License | Apache 2.0 |
| No. of views | 7,907 |
| No. of clones | 0 |
