Air Conditioner Inlet Filter Blockage Image Recognition Dataset

In the current industrial field, predicting maintenance cycles of air conditioning equipment is an important issue, especially in situations of filter blockage, which can easily lead to reduced efficiency or even equipment failure. However, existing monitoring solutions heavily rely on manual inspection, which is inefficient and prone to errors. This dataset aims to automatically recognize the dust accumulation status of filters through image recognition technology to predict maintenance needs in advance. The data is collected using high-resolution images from multiple industrial environments to ensure coverage of different dust conditions. Quality control involves multiple rounds of annotation and expert review to ensure data consistency and accuracy. The data is stored in JPEG format, categorized by time and dust level for easy subsequent processing and analysis.