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The Internet of Things is likely to reshape the world as we know it. According to Gartner, Inc., there will be nearly 26 billion connected devices by 2020. From wearables to home automation, to manufacturing optimization, the possibilities are immense, but so are the challenges.
Making the IoT work for the masses is more of a data challenge than a device connectivity problem. We first have to extract the data from devices then figure out what it all means. So far, the market has been focused on getting smart gadgets online. We’ve seen little innovation to help us consume all the data that these gadgets and machines collect. As a result, many IoT solutions suffer from the last-mile problem. In other words, these solutions are gathering data, but fail to help people see and understand the data they mine.
What good is data you can’t use? And if you can’t use it, why go through the trouble of collecting it? So how do we read, interpret, and understand this IoT data, be it from a smart home appliance, a wearable, or an industry-scale solution like GE’s Predix platform? We have to address four hurdles that stand in the way.
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