It takes time for information to travel from the edge of the Internet of Things (IoT) to the cloud and back. That’s what happens every time a node takes a measurement, sends it to the cloud to do some sort of analytical calculation, then sends it back to the edge for an action to occur. Unfortunately, there are instances where this is not a viable scenario, including those in the medical, automotive, and military markets. With Industrial IoT (IIoT) hitting the mainstream, the need for a real-time response is growing quickly.
If you could do those calculations at the edge and avoid going up to the cloud except when absolutely necessary or when there’s a down time, you could save in various areas, not the least of which is the cost of sending that data back and forth, possibly through a cellular carrier.
You may think such a scenario would be difficult to implement, but fortunately it’s quite the opposite thanks to a technology partnership between Wind River, a global leader in delivering software for the IoT, and Greenwave Systems, a managed services company. The two companies have done the hard part for you, as they integrate Wind River’s real-time operating system (RTOS) with Greenwave’s IoT analytics tools.
The partnership results in a very tight integration between the RTOS and the analytics. It’s designed such that any product being developed with VxWorks can be made more intelligent, with most decisions being made as close to the product as possible, minimizing the need to go out to the cloud.
As people understand the cloud, there’s a common debate about how to segment the workload between it and the edge. Obviously, it depends on your application, configuration, environment, use case, and so on. We’ve found that there’s a real need to have real-time control close to the edge so there are no latency or data loss ramifications.
One example of an industrial application that can benefit from such technology is a wind farm comprised of a series of wind turbines. Typically located in remote places, including miles out at sea or in a desert, the cloud is usually accessed over a cellular link or an even more costly satellite connection. That high cost usually negates the use of a real-time link.
Wind River will be demonstrating such a scenario at Embedded World in Nuremberg, Germany, March 14-16 in the AXON Predictive Analytics for VxWorks Wind Farm demo in Hall 4, Booth 158. The demo is built upon Greenwave’s AXON Predict analytics solution coupled with the VxWorks RTOS. The combined solution results in a smart and dynamically optimized energy production system, as the AXON Predict engine enables analytic scripts to be deployed to the individual wind turbines, where information from the sensors within the turbines is processed in real-time to understand turbine health and performance.
By embedding the analytics on top of VxWorks, we can provide on-device, real-time intelligence and ensure that expensive assets (the wind turbines) continue to operate as expected. In addition, performance can be maximized in relation to other turbines, and any predicted downtime can be arranged in advance. Anomalies discovered within the wind turbine operation or performance can trigger actions that notify repair personnel or take a turbine offline to prevent further degradation or failure.
This integration also adds a layer of security for VxWorks customers, especially at the edge. We view it like a trip wire for when there’s an attack. With all the edge devices deployed in the field, any one of them can act like a scout and report back that unwanted access has been attempted.
Security is an aspect of an IoT system that can’t be stressed enough, particularly in an industrial setting. But as we know, anything with a connection is a potential target, and getting security right in a connected world poses extreme challenges. This is clearly an area where VxWorks shines. When you add in the high level of security that comes with the VxWorks Security Profile, you gain advanced partitioning capabilities that enable reliable application consolidation.
via IOT Design