Addressing the challenges of embedded analytics

Mark Nadeski, Texas Instruments
August 31, 2015

Analytics are often touted as the solution to many problems across a variety of embedded applications such as surveillance, automotive, industrial, and even purpose-built high-performance compute servers. While there are a variety of processing solutions to run the many analytic algorithms that exist, it’s important that designers pick the technology that will be the most efficient and effective for their design. This is even more important in the area of embedded analytics where solutions are often extremely size and power constrained. In these embedded spaces especially, the real-time, math intensive architecture of digital signal processors (DSPs) are proving to be an extremely efficient processing solution.

Embedded analytics are all around us. They’re in our cars and our places of work and in our homes. Most new automobiles are great examples of intelligent analytics systems. Whether helping people to parallel park or automatically accelerating and braking as part of an adaptive cruise control system, advanced driver assistance systems (ADAS) are becoming increasingly commonplace.

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