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If you've been reading about the Internet of Things (IoT) market, you're probably wondering why all the buzz is about consumer products - wearables for health improvement, smart home technologies for better control over your life, smart vehicles for safer driving. There's no question that the consumer products being hyped right now are provoking thoughtful discussions in boardrooms and lots of investments by venture firms. The reason for this is that the world has always been fascinated by ways to use technology to improve our lives. The interest in futuristic technology gives us hope that we can find solutions to complex problems and daily challenges.
Being able to adjust your thermostat from your smartphone, however, does not fully embody the opportunity that the IoT represents. The truth is that the full range of possibilities created by the IoT continues to grow and is now being realized by enterprises across the world. The impact of these technologies are fundamentally revolutionizing the way enterprises do business and are allowing for advancements in productivity which compare with the advent of computing itself. Just imagine the transformation taking place on railways across the country. Where once a conductor manually applied the brakes when he saw a locomotive that was a little too close, rail companies are now operating with centralized systems that know the exact locations and actions of every locomotive in their network. Train speed is automatically adjusted to not only avoid collisions, but to optimize fuel consumption and improve overall efficiency, with the potential to drive an estimated $200m in profit for each 1 mph increase in average fleet speed.
So while smart phones, smart TVs, smart appliances and smart cars may continue to capture the imagination of consumers, you can see there is much to be gained with enterprise implementations. However, there is a fundamental difference when deploying IoT initiatives in enterprises. Let's explore why.
Consumer driven IoT use cases have typically been built on a two-tier architecture in which the device connects directly back to a cloud/datacenter-based service. In this model, the device transmits all data to a datacenter where analysis occurs and, if action is required, the action is then communicated back to the edge device. Fundamentally, this architecture works for consumer use cases for two reasons: availability of bandwidth and a lack of time-critical decision making.
In a consumer application, the consumer is paying for the bandwidth, so creating an application that is relatively bandwidth intensive does not impact the application vendor. Not so in the enterprise. Every byte counts. In fact, shaving a single byte from a message can save an enterprise millions of dollars in transmission costs in industrial IoT use cases. Therefore, it has become crucial for enterprise IoT architects to consider bandwidth implications in their designs.
Secondly, consumers are not overly concerned about the amount of time that it takes for decisions to be made. For example, when you tell your Nest thermometer to turn up your air conditioning by three degrees, it's probably okay if it takes a couple minutes to do so. Again, not so in the enterprise. In a mission-critical enterprise environment, decisions are measured in fractions of a second. Imagine if the under voltage sensor on your electrical grid waited three minutes to bring an additional capacity online when voltage started to drop. Entire power grids could go down and billions of dollars worth of equipment could be lost.
These considerations ultimately leave us realizing that a two-tier architecture is too slow for important data and too expensive for unimportant data. Instead, a three-tier architecture built around a new, functionally capable middle (or controller) tier has emerged. This controller tier essentially acts as a frontline datacenter; collecting, analyzing, and taking action upon data from its connected sensors and devices. These controllers are smart enough to take required action quickly, while sending only the most important summary data back to the datacenter. This concept of Near Field Processing allows for decisions to be made as close as possible to the edge of the network, and requires less data to travel all the way to the datacenter. Taking action close to the edge ultimately minimizes transmission costs and reduces decision time horizons, enabling you to go from data to decision faster and making the Internet of Things a reality for the enterprise.
In the past, only companies with the very deepest pockets were able to benefit from gathering data from distributed devices to drive better decision making and realize additional revenue. Today, the economics of the IoT architecture: the hardware, the ubiquitous nature of connectivity, big data and analysis, and customer expectations are dramatically expanding the IoT and making it possible for every enterprise – and not just consumers - to benefit.
In future posts, I'll tell you more about the economics of the IoT architecture and other considerations for the enterprise. And how you can build innovative, perhaps even futuristic, IoT solutions for your customers.

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