Home Edge Computing The Cost of IIoT: How Will This Impact Cloud and Edge Strategies?

The Cost of IIoT: How Will This Impact Cloud and Edge Strategies?

by John Fryer

As previously published on IoT Evolution
The Industrial Internet of Things (IIoT) has many advantages for industrial organizations, enabling them to generate valuable business insights that can improve everything from efficiency to productivity. Yet, as these enterprises begin adopting IIoT strategies, questions surface around the cost implications of these implementations – particularly, which type of computing is right for my business?

The truth is that both cloud and edge computing are essential for a successful IIoT framework – however, cost of IIoT and ROI will dictate the level to which each play a role.

As businesses begin to leverage analytics and wireless connectivity in the cloud, the costs can escalate quickly. The very nature of the cloud model is pay-by-usage, therefore, as enterprises move forward with their IIoT strategies and start to make progress, they’re realizing that cloud infrastructure is just one part of their overall IIoT equation.

It’s a Hybrid Cloud World

Operators are learning that certain processes cannot be pushed to the cloud when it comes to real-time computing requirements. Edge computing platforms, however, can act as localized storage points from multiple sensors, allowing analytics more real-time feedback, and performing pre-processing so only necessary data is sent to the cloud. This hybrid method also reduces the number of attack surfaces if data is collected from multiple sensor points.

Edge systems support a wide range of applications, including localized SCADA, HMIs, Historians, and can be delivered at competitive price points. The data they gather can be used for real-time analytics on the plant floor to enhance operations, including advanced process control and predictive device failure. Edge devices also forward certain information upstream to control systems and the cloud to be used for asset performance management, post-processing analytics or planning.

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