Aquaculture is the world’s fastest-growing animal-protein
production sector, and the use of robots in many industries is
growing quickly, as well. At North Carolina State University,
researchers are finding ways to build on these trends to increase
marine aquaculture yields, ensure food safety and decrease the
pressure to harvest wild seafood.
It’s a step that could help the state on its way to a proposed
goal of growing shellfish farming into a $100-million-a-year
industry by 2030.
The 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.
Sierra Young, an assistant professor in the Department of
Biological and Agricultural Engineering, is the project’s
principal investigator. 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.
Focus: Water Quality
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
The four-year project was funded this fall by a $1 million grant
from the U.S. Department of Agriculture’s National Institute for
Food and Agriculture through the multiagency National Robotics
Young says that the 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
As Young explains, “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.”
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,” Young says.
Within those hotspots, the robots will use sensor probes to
measure conditions, and they’ll 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,” Young says, “but we are
integrating that water quality modeling with robot path planning to
direct the robots to the most important and informative areas
within a shellfish growing area.
“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,” she says.
Getting Robots to Work Together
The researchers will also be looking at ways they can have
unmanned surface vehicles (USVs) moving along the water 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 NCState and the universityâs
Marine Aquaculture Research Center in Carteret County. Full-scale
testing will also occur in commercial oyster-growing areas.
âWeâre 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,â Young says. âOur long-term goal is to get this
information â and ultimately these robotic tools â in the hands
of growers to help mitigate production and income loss due to
shellfish mortality and unanticipated closures.â
This post was originally
published in College of Agriculture and Life Sciences News.