MusselAI

This proposed project aims to apply precision aquaculture technology in helping farmers find environmentally friendly ways to run and grow their operations with the goal of making a significant contribution to both for feeding humanity and protecting the health of the ocean. Mussel farmers rely on gut-feel and infrequent manual checks on their mussels to make decisions about predation management, harvest times and hiring (additional) seasonal workforce. To increase plot efficiency and de-risk operations, farmers need frequent, complete and timely information. The result of the MusselAI project will be a service, based on regular, automated data collection of the mussel farms by underwater robots. The collected data is uploaded to the cloud where it is processed using adaptive-learning AI. The service provides the end-users with the latest information about mussel health, predator populations and recommendations to increase the mussel plot’s yields. The information and recommended actions will be presented to the user in a browser based ‘dashboard’. Through exploring new robotics and machine learning technologies that can help mussel farmers run and grow their operations more sustainably, RS and LI are excited to make progress towards solving the problems facing sustainable food production. Moreover, the team will continue to work with ocean health experts to determine how machine learning models and underwater vision and sensing systems can help find new ways to protect the ocean.