A common thread among next generation embedded Cloud deployment is the increasing volume of data being transmitted and the subsequent need for solutions to turn that information into actionable intelligence – often on a real-time basis.
Clearly this data explosion is well documented for the tech market at large, but the potential impact in embedded not well understood. Although the information above from Cisco shows that non-PC devices are expected to have the highest growth rates in data generation, by and large, organizations are not yet taking advantage of this information to its fullest.
While some of this need can drive more computation to the datacenter and back-end business intelligence support, it also further complicates the convergence of the embedded and IT domains. This requisite compute power can be addressed by either (or in part by) embedded devices, edge computing and IT. So the fundamental question for OEMs is not just how the demand for rich media/big data is influencing system requirements, but also how this new functionality and intelligence translates to new business opportunities and risks from previously discrete technology domains.
So with this huge opportunity to monetize data capture, who can capture this product and service opportunity?
We are now in a place where IT business intelligence is in some ways going head-to-head with artificial intelligence on devices. However, we believe that with the continued growth in sophistication of embedded processors and software, OEMs have more latitude to bundle in differentiating artificial intelligence IP with their core offerings that can also add net new revenue streams.
To a large degree, the ability to capitalize on these new business opportunities resulting from Cloud connectivity will still fall back on OEMs' foresight and willingness to design in more sophisticated processors capable of delivering next generation analytics – on the device. We believe that this concept of “future proofing” is quickly evolving from a mechanism to reduce future operational expenses and rework to one of overall corporate strategic importance.
So Is your engineering organization taking the steps necessary to capitalize on Rich Media & Big Data for embedded systems?