A Web Application to Determine the Quality of Water Through the Identification of Macroinvertebrates

The quality of water present in rivers can be determined through the presence of certain types of aquatic macroinvertebrates. This work shows the development of a mobile application that determines water quality through the identification of aquatic macroinvertebrates present in a river. For the identification of macroinvertebrates, computer vision techniques were used, a convolutional neural network was trained using images of aquatic macroinvertebrates found in the Paute River basin (Cuenca - Ecuador) considering the analysis methods (ICA-NSF) and (BMWP/Col), to determine water quality. The investigation further explores key performance metrics like precision, recall, F1-score, and support percentages. The study extends its application to automated analysis of water quality indicators in organisms, utilizing computer vision techniques like OpenCV. This approach ensures instant, efficient information retrieval while maintaining ecological integrity. The integration of computer vision technologies opens ways to determine the quality of water in a river, in these places, without the need to transport samples to laboratories or know the types of macroinvertebrates that correspond to a certain level of water quality.