IPN students develop AI tool to monitor water quality

Students from the Instituto Politécnico Nacional (IPN) have developed ‘Deep Bug’, an artificial intelligence-driven system designed to streamline the assessment of water quality. The tool uses macroinvertebrates as bioindicators, as their presence or absence reflects the environmental health and contamination levels of water bodies.

The system integrates a mobile application for field data collection, a web platform for data management, and an AI model utilizing convolutional neural networks to classify macroinvertebrates from photographs. The mobile app is capable of operating offline, storing data locally until a connection is restored.

Developed by students Desiré Cuevas Romero, Didier González Ferreira, and Óscar Leyva Rodríguez, the project has already been tested in the Tehuacán-Cuicatlán Biosphere Reserve located between Puebla and Oaxaca. The team aims to expand the image database and increase identification precision to make the tool functional for biologists and local communities.