Image Dataset of Water Samples with Suspended Solids under LED Ring Light for Deep Learning Classification

This dataset contains labeled images of water samples with varying concentrations of total suspended solids (TSS), acquired under controlled experimental conditions using a white LED ring light as the illumination source. Water samples were prepared using distilled water and controlled concentrations of suspended solids ranging from 40 to 6000 mg/L, allowing classification into four water quality levels: good, acceptable, contaminated, and strongly contaminated. Images were captured using a standardized experimental setup, including controlled camera positioning, fixed distance, and continuous agitation to maintain particle suspension. The dataset is designed for the development and validation of machine learning and computer vision models, particularly convolutional neural networks, for automated water quality classification. This dataset corresponds to one of the experimental conditions analyzed in the associated research study and contributes to the development of low-cost, non-invasive environmental monitoring methods.