Turbidity monitoring

River contamination is an important environmental concern, which needs reliable real-time monitoring. Water clarity can be used as in indicator for water quality assessment, its spatio-temporal monitoring is important for the management of reservoirs, water management, and environmental protection of aquatic ecosystems.

photrack is developing a image-based continous system to monitor water clarity monitoring of small water bodies. The system uses RGB images and machine learning to monitor turbidity and Colored Dissolved Organic Matter.

Convolutional Neural Networks are used to learn and predict the described case of image to Colored Dissolved Organic Matter (CDOM) mapping.

Same machine learning methods have been implemented to continouns turbidty monitoring.