Advanced cloud platforms with the integration of artificial intelligence (AI) tie together entire work sites – even distributed supply chains. Big data, connectivity, control systems, smart sensors and other automated technologies have been largely isolated from each other until now. Contextual understanding of the data obtained from connected devices is the key element in adding business value from the Industrial IoT. However, having real-time information is not useful unless it can be acted on quickly. This could mean distributing information to individuals inside the organization, other systems in the network, other devices, or back to the device itself. No context to the data means that we end up with a big mess (instead of big data), and the analytics can deliver the wrong result (that may look right).
By bringing actionable intelligence and advanced analytics together on one common technology platform, it becomes possible to clearly see broader patterns, predict device performance and asset health through simulations, as well as identify logistical bottlenecks. Organizations can now take preventive action to avoid evolving conflicts or costly maintenance and safety issues that were completely unforeseeable before.
For example, at remote oil & gas fields, collaborative operations such as security, control loops, alarms, rotating equipment and safety systems can all be managed through secure connectivity and data management while accommodating for future scalability needs. Remote problem resolution can result in significant cost reductions; for instance, just an eight hour stop in operations can cost operators $1 million.
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