This project is developing two technologies related to JSATS autonomous acoustic receivers: 1) a system which can be used to estimate fish survival in near real-time for optimizing hydropower operations, hereafter referred to as the Real-time Autonomous Acoustic Detection System (RAADS); 2) an advanced machine learning based 3D acoustic-tagged fish tracking system, hereafter referred to as the Machine Learning Autonomous Tracking System (MLATS).RAADS will allow detection information from acoustic-tagged fish to be broadcast from underwater autonomous acoustic receivers to a surface-based receiver that would then transmit the data to an offsite location. This will generate timely information that can be input into models that would allow metrics of fish survival and behavior to be calculated and displayed on a dashboard.
