Recently I read an interesting blog by Greg Memo on Lighting as the killer app for IoT. He had recently attended the Lightfair International 2014 Conference in Las Vegas. His big takeaway was that LED lighting could be a killer app for IoT. He said:
“The big wave of IoT adoption will occur when: 1) consumers believe that the solution offers tangible lifestyle benefits; and 2) these benefits come at an affordable price. Time and again, history has shown that the combination of perceived value and affordability is what drives mass adoption.”
His hypothesis is that the combination of low-cost wireless connectivity (using System on a Chip or SoC), and LED lighting would allow low cost, energy efficient personal lighting. Not only would people have a new experience; it would be to experience something so fundamental as light, but in new way. Plus, it would have the side benefit of being energy and cost efficient.
My observation is that this concept of low cost intelligence can be extrapolated to one of an intelligent environment – one that could not only encompass homes, automobiles and work spaces, but also agriculture, manufacturing and other industrial endeavors. With the advantage of fine grain optimizations and adaptations leading to enhanced experiences for both work and leisure, and at the same time reducing resource consumption (energy, water, etc.).
So, how do we get there? I think the quote: “the devil is in the detail”, applies. It is our ability to create inflection points for new experiences via Moore’s law combined with effective R&D and manufacturing streamlining. The streamlining bit is the hard part. Manufacturers of components will have to become even more efficient within their design cycles, both reusing exiting designs and also being able to propose, design, test, and manufacture new variations, all the while integrating new technologies and IP as quickly as possible. This will require the ability to virtually model and validate not only new components and devices but also new design chains, supply chains, etc., all together so that change risk and time-to-volume can be minimized. The key will be to correctly model the dependencies between the products and their design and manufacturing systems at the same time. The complexity of this challenge will require agile, yet robust design data structures that can be created, documented, simulated and communicated in new ways beyond what we have been doing in the last 5 years.
