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An autonomous boat helps monitor water quality, predicting when toxic algae may form

OSU Research Matters is a bi-weekly look inside the work of Oklahoma State University faculty, staff and students.

According to the U.S. Bureau of Reclamation, only 3% of the water in the world is fresh and of that, only half a percent is available for our use. Due to modern-day pollution from industries and run off from agricultural farmlands, natural water sources such as lakes when not properly maintained can be harmful to our life by exposing us to polluted drinking water, contaminated food sources, and can even be harmful when swimming.

In this episode, Meghan Robinson speaks with Muwanika Jdiobe, a PhD candidate at Oklahoma State’s College of Engineering, Architecture and Technology. He has developed an autonomous boat that helps monitor water quality around the state.

TRANSCRIPT:

JDIOBE: If we look at the Grand Lake at the Horseshoe Creek Cove here in Oklahoma. For the 4th of July, they had to close down this place. And the reason to why they had to close it down, it was because of a harmful algae bloom that was going on. So, this impacted the economy of this small town. So my advisor, Dr. [Jamey] Jacob, then said, well, can we come up with ways we can forecast or predict these algae blooms before they happen. We need something inexpensive because the current methodologies that are implemented, they are very expensive. They are very manpower intensive.

Because I was a graduate student for the USRI, the Unmanned Research Institute, we mostly deal with unmanned systems, right? So, my first solution was, well, we have to have something that can operate autonomously but should also be able to get us good enough data. So, can we reduce the manpower that is required, reduce the number of scientists that can be involved in the process, and that's how we came up with an autonomous boat, MANUEL [Mobile Autonomously Navigable USV for Evaluation of Lakes].

So, MANUEL is, an autonomous boat that is capable of collecting water qualities, things such as temperature, turbidity, chlorophyll. Because all these water qualities, when you put them together, you have the capability of telling how safe your water is for drinking or for swimming or playing with. So, we needed a way of how we do that, but if you look in the industry, such platforms are extremely expensive. In fact, when I was looking at the high-end solutions, I came to see that some websites had a very expensive processes that they would use that probably a local community would not be able to afford.

ROBINSON: What is the ultimate goal of the research with MANUEL?

JDIOBE: For us to be able to build prediction models that can capture and forecast the water quality. Just like how you leave your house in the morning, and you look at your phone, and you say, oh, okay, today it is going to be extremely cold, so I probably need a heavy jacket.

It's the same thing that MANUEL is built for. We want the data that Manuel is constantly collecting to go into some type of modeling, that then is going to be able to forecast and say, we think this water is going to be hit by a harmful algae bloom. The data that we get from MANUEL can be used by the scientists to come up with possible solutions ahead of time to make sure that the harmful algae bloom does not happen.

Now this can help many, many local communities here in Oklahoma, but also in places like where I'm from whereby clean water is not readily available. If we have this tool supplied to all these local communities, probably we would be improving the health of the people because by the time you take the water, you already know more about the water you're taking, not taking it, and then you end up with some kind of diarrhea and say, 'oh the water I took is not healthy.'

ROBINSON: For OSU Research Matters, I’m Meghan Robinson.

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