Machine Learning Enabled Smart Nets to Optimize Sustainable Fisheries Technologies

The proposal targets novel CPS challenges by aiming to develop a system that provides dynamic assessment of the interaction between sea life and smart nets. The CPS explores challenges in machine learning to continuously assess the response to sensory cues for individual species that must be determined in real time to enable modulation of the sensory cues to determine efficacy per species. This must occur in one of the most dynamic and physically challenging environments necessitating the constant adjustment of imaging parameters and sensory cues to provide equivalent identification capabilities and perceived cues.