When you think about artificial intelligence (AI), you probably don’t imagine using it for a farm. But you should: this week, IBM is bringing data and AI together with the global release of the Watson Decision Platform for Agriculture to help growers makes better decisions. This new platform is an innovation that draws upon IBM’s most advanced capabilities in AI, analytics, IoT, Cloud, and weather to create a powerful new resource that spans the full farm-to-fork ecosystem.
Farming has always been a complex undertaking that requires growers to manage an interconnected web of pre-season and in-season decisions while at the mercy of mother nature. With the explosion of data from farm equipment, environmental sensors, and remote input, it’s impractical to rely on intuition or traditional technology to understand what drives variation in yield or provide guidance to growers. IBM is filling this gap by applying Watson AI to the data to generate the decision support growers need to make confident, evidence-based decisions.
In parallel, food companies are looking for ways to meet consumer demand for better food quality and sustainability. IBM’s solution will bridge food companies and their grower suppliers to better manage the inputs and farming practices that can deliver on the promise of improved food quality. IBM is drawing on its experience with improving products ranging from wine to tomatoes to make this vision a reality.
Growers are already benefiting from IBM’s efforts to integrate data sources while extracting insights from them. “Until now, nobody has tackled putting all this information into one place,” says 3rd-generation farmer Roric Paulman. “I’ve got 40 different ag apps on my phone. It just stops being useful.”
Paulman has 10,000 acres under cultivation in Nebraska and he generates one terabyte of data every month. IBM’s new platform allows him to bring everything together on his phone so he has a powerful, unified view of his farm.
For Paulman and other farmers, bringing AI to bear on data provides startling new powers. Growers can now film a field of corn from a drone and use AI-enabled visual recognition analysis to identify crop disease or a pest infestation. The app also allows the grower to photograph struggling plants up-close and identify the exact pest or disease. On Paulman’s farm, an agronomist currently visits once a week to analyze infestations and blight. Now, with a simple photo, Paulman can immediately find out what type of insect is affecting his plants and he can take remediation action.
“That means I can react in real-time and won’t lose yield waiting for the agronomist,” Paulman says. It also allows him to better target pesticide use, reducing environmental impact and lowering cost.
For large food producers, the platform offers an opportunity to “see” the fields in a new way. If a farmer is willing to share select data with downstream partners, producers will know precisely when the harvest is likely to happen and how much it will yield. That provides new transparency to a system that was once opaque.
The platform also seeks to solve problems before they start. The platform helps farmers understand critical factors such as soil temperature and moisture levels, crop stress, pest and disease risk and identification, yield predictions, and alerts. That helps inform decisions like irrigation, planting, fertilization, worker safety, trading, and pest and disease eradication.
One of the biggest challenges farmers face is knowing when exactly to sell their crops. Prices fluctuate constantly and theres an overwhelming amount of information to process. The platform offers a tool that brings some clarity: it marshals huge amounts of pricing data-from the local grain elevator to the futures markets-and recommends the best time to sell a crop in order to maximize profit. It’s the type of data gathering and analysis that would take weeks of work, if it was possible at all. In fact, farmers have had little choice in the past but to guess what will happen.
“I’ve been waiting for something like this,” Paulman says. “IBM has independence. They’re not trying to sell me more fertilizer or machines. They don’t have a horse in the race. It’s a trust thing.”
The platform is just one piece of IBM’s larger effort to improve agriculture. The Weather Company enables a host of other agricultural partners to deliver hyper-local forecasts to growers in their local dialects – and IBM Research is helping fuel a wave of innovation in the agricultural technology sector.
• In India, IBM Research has partnered with NITI Aayog, a government think tank to explore how AI can be used to leveraging AI to issue early warning on pest and disease outbreaks.
• In Brazil, researchers have built a prototype, The AgroPad, which uses AI and a mobile app to analyze soil and water samples, which could help growers make better choices about how to water or fertilize their farms.
• In Kenya, IBM scientists in Nairobi partnered with Twiga Foods to build and test a blockchain-enabled microfinance lending platform which helps small farmers and food vendors get access to lending capital.
The IBM PARIS Geoscope is a cloud-based platform that can quickly provide contextual information about a specific location using geospatial-temporal information. Using machine learning techniques and analytics on satellite imagery, weather data, census data, land use and business location data, it can help companies make predictions about the future of their farms.
In each case, from Brazil to India to North America, AI is helping feed us while making the lives of growers easier. Benjamin Franklin would have been proud.
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