Increasingly, autonomous and automated vehicle systems (e.g. surface, underwater, aerial) in aquaculture are applied in North Carolina and other locations. This talk will provide an update on our project focusing on using multiple vehicles (primarily aerial and surface) to assess and manage oyster aquaculture. Modeling and assessing water quality to better determine optimal timing for harvest; and optimizing the process are critical. This update will include field data and modeling efforts to assess location, time, flow, temperature, nitrate, pH and other water quality parameters and link these to measured bacterial loads (captured manually) under different conditions.
Updates on software including “digital twin” modeling in different situations; open source code including enhanced learning and use of multi-vehicle automated systems will be included. Preliminary work with collaborators in nearshore oyster leases to assess effectiveness, speed, accuracy and improve understanding of limits to autonomy and human-robot interfaces are ongoing.
The coastal environment is dynamic and subject to high energy events, but is also an extremely productive zone. These systems should enhance sustainability, improve monitoring and productivity, and may be able to provide improved information on coastal water quality, biological and ecological conditions, thus allowing improved decision making by farmers, managers and others.
This presentation will provide an update on current work, relevant findings, and direction of future work, in the hopes that coastal and offshore zones will enhance wise use of automated systems in aquaculture.