New IBM Cognitive IoT Learning Lab Could Bring Deeper Shopper Insights to Retailers

IBM is opening the global headquarters in Munich for the Watson IoT unit, its first European Watson innovation center and the company’s largest investment in Europe in more than two decades, it said Tuesday. In a blog post, Harriet Green, general manager of Watson IoT, said it's “a major down payment” on IBM’s $3 billion commitment (see 1503310032) to IoT over the next three years. Some 1,000 IBM developers, consultants, researchers and designers will work at the Munich campus, described as an innovation lab for “a new class of connected solutions at the intersection of cognitive computing and the IoT.” IBM is adding machine learning, natural language processing, video and image analytics and text analytics to its IoT portfolio for the second wave of IoT that it calls "cognitive IoT," she said. Roughly 90 percent of data gathered by sensors today is lost or thrown away due to bandwidth limitations and security and privacy constraints, said Green, and other unstructured data is available from news websites, call centers, social networks and other sources. Cognitive IoT will enable IBM clients to combine diverse sources of data in real time to understand what’s going on in their operations on a deeper level. Green gave the example of a retail store equipped with video cameras and networked sensors. Using cognitive IoT, a store could communicate with shoppers, who have agreed to be connected via smart phone apps, through speakers that gather information from the conversation, she said. “A cognitive system combines all of this sensor data with information gathered about the local weather and news, social networking streams, and sales trends.” With those capabilities, store managers could understand what’s going on in the store in real time, interact with shoppers, and react to changes, she said. “If it’s raining outside, digital signs in the store might direct shoppers to umbrellas, rain gear or hair-care products,” she said. Video analytics tools discover the demographics of people buying certain items. If a large number of shoppers pick up an item but don’t buy it, machine-learning algorithms can spot patterns to determine the cause. Stores will be able to provide shoppers with “cognitive assistants” -- via their smartphones -- that know them and provide them with “superior in-store experiences,” she said.