Scalability of Industrial IoT applications

Scalability of Industrial IoT applications
by Akeel Attar on 12-04-2016 at 7:00 am

Industrial IoT applications typically start with a small scale pilot application to demonstrate how some items of equipment and their related sensors can be connected to the cloud and to understand what algorithms are required to automatically extract value from the arriving streams of measurement data. Following on from a successful pilot application the next step will usually be scaling up the solution to automatically monitor many more items of equipment which is likely to require a solution capable of processing data from thousands of devices and hundreds of thousands of measurements.

The XpertRule Rules, Decision & Analytics engine supports large scale IoT deployments through its unique ability to deploy distributed decision making to any part of the IoT ecosystem; IoT edge/fog, Cloud and Mobile devices all from the web / cloud based Decision authoring environment.


Cloud based deployment
The cloud based Decision Engine deployment supports large scale applications through its modular software structure and ability to automatically deploy mirrored instances of the same application across multiple servers. The modular software structure allows separate definition of libraries of data processing and predictive algorithms and rules based templates for monitoring different types of equipment and devices. This makes adding new equipment straightforward and changes to monitoring algorithms and templates are automatically propagated across all equipment types using these libraries. As more devices and equipment are monitored further servers and instances of the XpertRule engine are used to provide increased processing capacity.


IoT edge hub deployment
Deploying Rules, Decision and analytics engine at the IoT edge reduces the reliance on a connection to the cloud and can provide real time response to local problems and minimise the amount and frequency of data sent to the cloud. In addition data remains local where there are restrictions on sharing with the cloud due to confidentiality / security requirements. Reduction in data traffic between edge devices and the cloud can be substantial as there is only a need to report significant events or aggregated data to the cloud. This in turn greatly reduces the requirements for cloud based monitoring algorithms and minimises the need for increased processing capacity as more devices and equipment are added.

 Mobile device deployment
Deployment of the XpertRule Decision and Analytics engine on mobile devices supports local troubleshooting of equipment and device problems by field personnel. Guided workflows can guide non expert users through diagnosing and resolving problems so that the requirement for visits from centralised specialist resources are minimised. This has the advantage of the faster resolution of problems as well as preventing the availability of specialist resources becoming a bottleneck to large scale solution deployment.


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