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The Internet of Intelligent Things: <br>Powered by Edge Computing

Earlier this week in cooperation with ABI Research we published a white paper titled Evolution of the Internet of Things: From Connected to Intelligent Devices. The white paper outlined some key advantages such as lower total cost of ownership (TCO) that edge computing is poised to bring to the Internet of Things (IoT) market (if you didn’t have a chance to review it, it can be found here). As the cost of processing continues to fall, the value proposition of deploying more intelligence at the network’s end-points is becoming increasingly attractive thus transforming IoT into what we call the Internet of Intelligent Things (IoIT).

Per the white paper, this assumption is primarily based on edge computing’s ability to better manage data communications and power consumption. As it relates to IoIT, these benefits translate into lower TCO when considering large-scale enterprise deployments and the long-term costs associated with bandwidth and backend-storage. Moreover, given the energy efficiency of today’s embedded processor technologies, low-power, battery operated IoIT solutions bring yet another dimension of value when considering the costs of deploying electricity to support remote applications such as smart cities, smart agriculture and smart infrastructure.

With this in mind, Egburt leverages a novel edge computing architecture that enables IoIT solutions that support lower TCO compared to traditional cloud computing techniques. Unlike these centralized processing architectures, Egburt’s embedded edge computing runs advanced real-time sensor processing and analytics software that has been fully optimized for performance and power consumption. Using data derived from Egburt’s design, the white paper illustrates significant reductions in bandwidth requirements for a specific use case leveraging edge-processing techniques (e.g. > 20X when comparing different operational profiles) without compromising data analysis objectives. Comparison of battery life for the same use case and profiles yields similar results with a > 10X overall improvement.

As we work with clients in the enterprise sector, it is clear that improved TCO will be one of the major requirements that will spawn faster IoT adoption. While traditional cloud computing approaches to IoT have represented the early solution space, factors such as TCO, reliability, network performance, control latency and security will drive an inevitable paradigm shift in many markets to distributed IoIT architectures such as Egburt. 46 days and counting.

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