Amazon Web Services Inc. today announced the general availability of AWS IoT SiteWise Edge, a tool that helps industrial companies process sensor data from their equipment to perform tasks such as detecting technical issues.

Manufacturers and other industrial companies are incorporating more software into their day-to-day operations. As part of the trend, many firms are adopting artificial intelligence applications that can analyze sensory logs from equipment to automatically find issues. In some cases, AI makes it possible to detect malfunctions even before they cause an outage, which avoids business disruptions while saving work for technicians.

But AI alone is not sufficient to catch maintenance issues early. Companies also need a second software system to manage the logistics of collecting sensory data from industrial equipment, organize the data and then stream it to the applications responsible for detecting technical issues.

That’s the requirement AWS is addressing with IoT SiteWise Edge. It’s a version of the cloud giant’s existing AWS IoT SiteWise service. The difference between the two is that the latter is delivered as a cloud service while the former offering, the one that launched into general availability today, runs on-premises.

“With AWS IoT SiteWise Edge, you can organize and process your equipment data in the on-premises SiteWise gateway using AWS IoT SiteWise asset models,” explained AWS principal developer advocate Channy Yun. “You can then read the equipment data locally from the gateway using the same application programming interfaces that you use with AWS IoT SiteWise in the cloud.”

Companies can deploy IoT SiteWise Edge on the cloud giant’s AWS Outposts and AWS Snow on-premises appliances. Outposts appliances make it possible to create a miniature on-site version of the AWS public cloud that lends itself to, among tasks, analyzing data from industrial equipment. The Snow system series can run analytics applications as well, but has a different focus. The systems are mainly used to move on-premises data to the AWS cloud when transferring information over the web is not practical.

Notably, IoT SiteWise Edge can also run on Linux-powered industrial computers made by other companies. 

One reason an enterprise may wish to deploy IoT SiteWise Edge is to help it prepare against internet outages. A wind farm operator, for example, might have an application that automatically alerts on-site technicians when a wind turbine experiences a malfunction. To ensure technicians are notified about malfunctions even when there’s no internet access, the company could run the application on an on-site machine in the immediate vicinity of its wind turbines.

Manufacturing is another area where AWS sees IoT SiteWise Edge providing benefits for enterprises. A factory operator could use the tool to power applications that track equipment health or monitor the production line for product quality issues. 

As far as its analytics capabilities are concerned, IoT SiteWise Edge provides a similar set of features as the cloud-based IoT SiteWise service. It can ingest sensory logs from multiple industrial systems even if the information is stored in different formats. From there, the tool is capable of adding in descriptive labels to provide context on each piece of data. Such labels make it easier for analytics applications to find the specific pieces of information they need to carry out calculations.

In some cases, an analytics application may not be capable of analyzing sensory data in its raw form. IoT SiteWise Edge can in such scenarios edit the information to facilitate analysis. For example, a company could use the service to automatically switch temperature measurements from Fahrenheit to Celsius. Or it might have IoT SiteWise Edge enrich sensory logs with additional information such as statistics about the average output of a production line.

Image: AWS