Autonomous robot fleet to generate water quality data for North Carolina’s shellfish industry

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Researchers at North Carolina State University (NCSU) continue to pioneer new methods to increase marine aquaculture yields, ensure food safety and decrease the pressure to harvest wild seafood, as they seek to help the southern US state achieve its proposed goal of growing shellfish farming into a US$100-million-a-year industry by 2030.

Aquaculture is the world’s fastest-growing animal-protein production sector, while the use of robots in many industries continues to grow equally rapidly. With these two trends firmly in mind, NCSU researchers plan to use small fleets of unmanned vehicles on the water and in the air to improve oyster production near the North Carolina coastline. The goal is to get the vehicles to work with each other to monitor water quality in areas that are difficult and dangerous for people to access.

The researchers say the project will provide valuable data to inform management decisions that are key to unlocking sustainable growth of nearshore production of shellfish in North Carolina and beyond. The four-year project was funded last autumn by a US$1 million grant from the US Department of Agriculture’s National Institute for Food and Agriculture, through the multiagency National Robotics Initiative 2.0.

The NCSU team is focusing on water quality because it has important implications for the safety of consumers’ food and for producers’ profitability. Bacteria and other pollutants carried by stormwater into the ocean can cause nearshore producers to halt their harvests temporarily, until the bacteria reach safe levels. These closures are estimated to cost producers 25% of their average annual income.

We hope to automate water testing and sample collection by creating a data-driven process that makes the window [of closure]as small as it needs to be,” explained Sierra Young, an assistant professor in the NCSU’s Department of Biological and Agricultural Engineering (BAE), and the project’s principal investigator. Her fellow collaborators include three other faculty members from BAE – Steven Hall, Natalie Nelson and Celso Castro-Bolinaga – as well as John-Paul Ore, from the Department of Computer Science.

Sierra Young, left, and doctoral student Hemanth Narayan Dakshinamurthy are part of a team of NCSU researchers working to integrate unmanned surface and aerial vehicles to improve farming of oysters and other shellfish. (Photo by Marc Hall)

Sierra Young, left, and doctoral student Hemanth Narayan Dakshinamurthy are part of a team of NCSU researchers working to integrate unmanned surface and aerial vehicles to improve farming of oysters and other shellfish. (Photo: by Marc Hall)

Predicting bacterial hotspots in aquaculture

The researchers plan to develop computer models that let them know which areas of an operation are most likely to become bacterial hotspots – places “where we can predict there might be higher levels of bacteria or other water-quality parameters of interest, such as dissolved oxygen or pH,” noted Young.

Within those hotspots, the robots will use sensor probes to measure conditions and take samples that can be returned for laboratory analysis. “We’re looking to not just have robots that autonomously monitor the same area over and over,” said Young, “but we are integrating that water quality modelling with robot path planning to direct the robots to the most important and informative areas within a shellfish growing area,” she continued. “The idea is to get the most value out of a single deployment, especially when the number of water samples the robots can take is limited.”

The researchers will also be looking at ways to ensure unmanned surface vehicles (USVs) moving along the water can communicate and work with unmanned aerial vehicles (UAVs), or drones. UAVs could, for example, be used to scout areas and let the USVs know where conditions might be unsafe to enter, and the USVs, or drone ships, could be used as landing and docking stations for the UAVs to expand the survey area. The researchers plan to initially test their system in local lakes and ponds, as well as at NC State and the university’s Marine Aquaculture Research Center. Full-scale testing will also occur in commercial oyster-growing areas.

We’re designing our autonomous robot fleet to generate water quality data not only to inform management decisions in real-time but also to improve bacteria load forecasts and predictions,” concluded Young. “Our long-term goal is to get this information – and ultimately these robotic tools – in the hands of growers to help mitigate production and income loss due to shellfish mortality and unanticipated closures.

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