@dnandy, thanks for the interesting comments. I can understand how a dedicated hardware architecture results in better efficiency (i.e. performance improvement), but I am not clear as to how power consumption is reduced. e.g. we are comparing power consumption for gesture recognition between the MM-3101 and an ARM Cortex A9.
This is a comment to both.Image understand tasks require 2-D area based image processing, best applied using vector processors and data-flow architectures. Doing this is SW really reduces it multiple for loop structures, which consume cycles and power. A dedicated data-flow vector processing pipeline can do it efficiently at lower power. The key is to balance the HW flexibility so that programability is not impacted
I suspect that this will either be a short-lived product or end up only in niche applications. The next generation of processors will likely have enough horsepower to do the same tasks in software without a significant performance hit.
What are the engineering and design challenges in creating successful IoT devices? These devices are usually small, resource-constrained electronics designed to sense, collect, send, and/or interpret data. Some of the devices need to be smart enough to act upon data in real time, 24/7. Are the design challenges the same as with embedded systems, but with a little developer- and IT-skills added in? What do engineers need to know? Rick Merritt talks with two experts about the tools and best options for designing IoT devices in 2016. Specifically the guests will discuss sensors, security, and lessons from IoT deployments.