By DEBORAH BEHRENDS
ARMONK, N.Y. — IBM is moving its Watson supercomputer into the agriculture sector, giving a huge boost to an industry struggling to meet ever-growing global food supply needs.
The company recently introduced its Watson Decision Platform for Smarter Farms, putting artificial intelligence (AI), supercomputing and predictive insights into the hands of even the smallest-scale of farmers. Automatic data collection, AI-driven insights and clear decision support can help food companies, farmers and financiers meet increasing consumer demand.
The new platform combines AI, the Internet of Things (IoT) and predictive analytics to help ag enterprises and farmers gain insights into projected yields and potential problems, such as soil temperature, moisture levels, crop stress, pests and diseases.
Farmers can upload aerial drone pictures or even photos from their phones to the IBM Cloud for supercomputer analysis to detect potential problems they can’t see with the naked eye. These types of tasks previously required a lot of time and many steps now can be accomplished – with better results – in minutes.
According to Mark Gildersleeve, vice president and head of business solutions for Watson Media and Weather, there's an overarching story with three goals. First, to bring broader, unique data to the people who need it; second, to bring Watson and AI to agriculture; third, to build decision support solutions for the grower and the enterprise overall, including input providers, food companies and the pertinent government agencies.
"The most important thing to understand about the data is we are trying to collect a broader range of data – weather, farm practices, et cetera – and aggregating all of that in the IBM platform, and then applying AI to that data," Gildersleeve said.
"Some examples, we're using AI to create crop stress maps; we create our analysis of soil moisture and temperature; a broad range of pest and disease models.
"Let's say a grower is scouting the field and doesn't know what disease is on their corn. They can take a picture and we'll (get back with) you with a confident estimate what the disease is, anticipating an outbreak and then identifying what it is once the outbreak occurs."
Gildersleeve said Watson is using the local knowledge being gathered to correct national models, helping estimate yields and prices.
"Producers can bring AI to bear in a large number of areas to help people make good decisions earlier. It's also an interesting blend where food companies have growers under contract; it's helpful for the grower and the company to have a common situational awareness about what's going on in the fields so there are no surprises.”
He added, “It has taken advantage of the work of research teams around the world over the past decade leveraging IBM, the IBM food trust, IBM research, a lot of IBM clients to get us going fast. I hate to sound like a giddy schoolgirl, but I am giddy."
And he pointed out Watson's decision tool is not coming from a seed, equipment or chemical company looking to sell only its own products.
One of the early adopters is of the platform is Roric Paulman of Nebraska. With 10,000 acres cultivated in a variety of crops, the Paulman family has a concern many in the Midwest often don't: Water.
"Working with IBM looked like a good fit for us," he said. He explained he has numerous apps on his smart phone, but he needed to be able to turn all that data into a decision tool.
"We took a few of our fields and put them into the platform. I was pleasantly surprised at the accuracy and resolution," Paulman said.
Because they irrigate, it's crucial he has real-time data in his decision-making, not data that are several days old. "If we're able to see a rain event to get validation from a real-time weather model, we can save the resource and the energy for irrigation and make decisions sooner.”
"As these tools become available, the impacts for my son and my grandson, the legacy of natural resource management is going to be a big deal. It becomes a bigger deal every year,” Paulman added.