“All of The Weather Company’s data can be accessed using a simple published Application Programming Interface (API),” says John Cohn, IBM fellow and chief scientist of design automation. Think of an API as a set of instructions for building a piece of software. It’s flexible in that the end-user company can choose what the software will look like. From this digital portal its employees will access the data drawn from weather stations and IoT-connected devices, and Watson ties it together by allowing them to ask questions the way a person asks another person.
“Our initial demonstration, which is already online and working, is around a project called EZ Buddy,” Cohn says, “developed by our IBM research lab in Kenya. EZ Buddy demonstrates how local weather data can be used with local irrigation monitoring and control to help farmers optimize their crop watering.” Farmers text the system from their mobile phones, asking questions such as ‘When should I water?’ and ‘How long until my water tanks are refilled by rain?’, and the system texts them answers. Once expanded beyond East Africa, WIoT (Watson IoT) will merge all WU’s weather stations with relevant satellite data, lift data from cell phones’ pressure sensors, and combine it with local information, such as soil measurements and nearby water stores, to sharpen its weather models both globally and locally. Farmers can use it to manage their irrigation, planting seasons, and pesticide schedules. “It’ll demonstrate how commercial interests such as insurers, commercial farming interests, and smarter cities can build commercial systems that combine hyperlocal weather data with cognitive IoT,” Cohn adds.
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