Fog Computing: IT Compute Stacks meet Open Architecture Control

Fog computing is getting more popular and is breaking ground as a concept for deploying the Industrial IoT. Fog computing is defined by the OpenFog Consortium as “a system-level horizontal architecture that distributes resources and services of computing, storage, control and networking anywhere along the continuum from Cloud to Things.” Looking further into the definition, the purpose is to provide low-latency, near-edge data management and compute resources to support autonomy and contextually-aware, intelligent systems.

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A Foggy Forecast for the Industrial Internet of Things

Signs on I-280 up the San Francisco peninsula proclaim it the “World's Most Beautiful Freeway.” It’s best when the fog rolls over the hills into the valley, as in this picture I took last summer.

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Building Flexible Manufacturing Systems for Industrie 4.0

Many discussions on the industrial internet of things (IIoT) describe how all kind of sensors will be connected to the cloud, where the big data analytics beast will consume lots of data to provide you with efficiency optimizations. Huge cost savings are especially promised in the energy and transportation sectors. The medical industry, on the other hand, sees an opportunity to provide better and safer care, by integrating patient monitoring devices, and correlating the data or by merely reducing the amount of erroneous alarms.

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An IIoT Sensor to Cloud Gateway Solution

One of the primary use cases for the IIoT (Industrial Internet of Things) is to collect sensor data and deliver that to an enterprise cloud for enhanced real-time visibility in to remote operational systems. This is very important for applications such as Oil & Gas, Manufacturing Plant Production monitoring, Healthcare Patient Monitoring and Power Substation Monitoring. With advances in network infrastructure and the promise of higher bandwidth WAN (Wide Area Network) connections, the ability to pull raw sensor data across the WAN to a backend enterprise cloud where data processing and predictive maintenance solutions can be implemented, and monitored. Enabling this type of architecture provides great agility for organizations to respond and react to changing conditions for their deployed systems.

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