One of the major promises that discussions of the Internet of Things (IoT) have put forward, is the advances to be made in consumer insight. The idea is that sensors and connected devices can send data on an open loop back to the manufacturer for analysis. This process would presumably secure many advances in a wide variety of things; not only would companies be able to understand their clients, but sensors may even be able to tell us more about the product in general. For example, pedometers on livestock have given scientists more knowledge about when cows are in heat, allowing for a 66% increase in insemination rates.
Many have referenced discoveries such as these to be the real goldmine of the IoT. Using big data analytics, manufacturers could generate the type of insight that could propel future developments. However, the concept of big data analytics is still a bit fuzzy to most people. A lot of the general knowledge of analytics is overshadowed by the half-belief that information is fed to a group of ancient mystic palm readers who come up with practical applications for the infinite mass of soundbite data. In reality, the sorting mechanism used to interpret the data from connected sensors is rarely earth-shattering and could even be accomplished on a closed loop. This is critical to keep in mind, especially as companies make decisions regarding data security.
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