It seems all eyes are on IoT and IIoT trends in the world of information technology as the globe heads into the year 2017.  The potential to reach a new, even more exciting level of technological innovation through further product development and refinement of IoT and IIoT sensors, gadgets and smart devices is just starting to form.  Many experts speculate that edge computing will be one of the key factors that will enable IIoT to produce a notable level of maturity in the new year.  In the coming months, those interested in being on the forefront of IIoT trends will want to keep their eye on edge computing.

What is Edge Computing?

Edge computing is essentially pushing the intelligence needed by “things” to properly perform their functions, to the outer edges of networks.  For example, it is one thing to have a drone or a smart traffic light performing simple functions out in the world, it’s another thing to have a drone or traffic light that is able to operate independently, without needing to “call home” for instructions or data analysis.  With edge computing, smart devices and gadgets already have enough built-in intelligence to work autonomously, perform their own analytics on streaming data and communicate with other devices on their own in order to accomplish a set of tasks.

Decisive Impact with IIoT and Edge Computing

Consider the impact of edge computing, along with the IIoT in the following examples.  What if a series of air or land-based drones were able to remotely examine and analyze a forest fire or a collapsed building on their own?  What if the drones were able to understand the context of their mission without having to send data back to a command center for analysis?  If the drones were able to analyze their own data and provide that data to the nearest available person in the field, the potential to successfully rescue humans in danger and/or minimize property damage is significant.

Even farmers could benefit from edge computing when they have vast tracts of farmland to cover when checking on livestock or property fencing.  In remote areas, it is often challenging to connect and send large quantities of information over wireless networks or to receive instructions in a timely fashion.  If a smart device was able to determine on its own whether there was a break in a fencing line or if livestock was down and needed assistance, a farmer or rancher’s ability to respond to the situation is made that much more timely and efficient.

Edge Computing Challenges

Although it seems that edge computing can add real business value to IIoT sensors devices and the like, as with any newer technology there are some challenges.  Security and privacy issues remain in the forefront, and rightly so, when considering the potential for negative outcomes if hackers decide to take over a sensor or device and steal the internal data and/or use the device for nefarious purposes.

Inferential controls are a key component of any IIoT smart device.  Building a device that is able to accurately interpret its surrounding environment without error and then make vital decisions based upon its own ability to infer is a formidable task.  It is one thing to design a device to handle defined, even complex tasks, but what happens to the device and its ability to analyze when the unexpected occurs?

Another challenge is to determine how much intelligence to build into devices and when to remove humans from the equation, all the while still allowing people to leverage the industrial internet of things in a controlled and effective manner.  There is a tremendous potential for great power to be placed into the hands of machines and the question is, who is in control of the oversight of some of these power exchanges?  In some instances, companies can expect government bodies to insist on inclusion in decision-making processes.

Despite some challenges, companies can probably expect to see continued product innovation, further development of industrial internet of things and creative solutions to resolve issues.