As the IIoT is formed through the web of devices on legacy protocols and newer IP based MAC/PHY implementations, information volume on a new scale is being realized. In executing on their IIoT vision, organizations' biggest challenges are no longer the connection and consumption of their IIoT property, it's the utilization of the data. This challenge clarifies the need to deliver IIoT implementations with a strong device/application profile model allowing this vast information to be sorted, and organized. These application profile models allow the creation of actionable business intelligence.
Interoperability organizations that tout standard device profiles such as LonMark International are realizing their value as repositories of application profiles that will fuel the IIoT. If interested on more, see an article on page 20 here at http://www.lmimagazine.com/files/lmi_magazine_v6_i5.pdf that discusses looking beyond communication protocols to information models.
But we also must remember that some parts of the industrial market have become "networked" (usually via wired). They are gradually becoming wireless and, one step further, they are going IP route. See the interview we did with Dust.
@Hillol, it's a great point. Some companies will implement faster, much faster than others. For example, smartphone-based (Apple, Google) will be much faster than household appliances (GE, Panasonic, etc.). Infrastructure and medical, it should be relatively straightforward, but reliability must be guaranteed so that would be the only limiting factor of rollout.
I think people may not know how to implement IOT because it is new to many people. Direct OEM such as energy companies can deploy IOT much faster than many Industrial companies. Wi-Fi will enhance that process. Need more time to do these as it is not that simple to execute Industrial applications. Medical segment, it will go fast as it is required immediately.
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.