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The Industrial Internet of Things (IIoT) relies on smart IoT




Guest post by Arthur Cole

Smart thermostats, automated garage doors, smart sprinkler systems—all these Internet of Things (IoT) devices are impacting our lives. But the Industrial Internet of Things (IIoT) is doing more than automating mundane tasks: from smart power grids to embedded sensors in water treatment facilities, the IIoT is changing manufacturing and industrial control. Every bit as challenging and complex as the IoT, it's creating opportunities and problems of its own, especially with data security.

Just as in the data center, the shop floor is mired in legacy infrastructure and processes that simply place too much of a drag on businesses as they try to meet the demands of a digital economy. These points of failure exist not only on the assembly line, but also in areas like procurement, development, distribution, and lifecycle support. Using the same kind of intelligent monitoring and control found in the IoT, coupled with high-speed predictive analytics, industrial production across the globe will become more streamlined, more efficient, and more responsive to the needs of consumers.

Capitalizing on next-generation IIoT

This transition will involve more than just the deployment of intelligent IoT devices on heavy machinery, according to Tripwire's David Bisson. The smarter you make your endpoints, the smarter your data infrastructure will have to be to capitalize on these advanced data sets. The first big challenge, in fact, will be to power up the IIoT without crashing existing industrial control systems. After that, organizations will have to consider the interconnectivity of devices and the level of machine-to-machine (M2M) communications and control they need. At the same time, they'll need to deal with the security risks that come with adding hundreds, if not thousands, of new devices to their networks. Bisson recommends that enterprises integrate cyber threat protection into their networks to protect from malicious malware and other threats.

Naturally, this will not only require a new type of industrial monitoring and control, but new versions of software to oversee them, says Meridium's Matt Cicciari. Next-generation IIoT software should be cloud-based in order to accommodate the immense scale that is endemic to IoT infrastructure, and it should also easily connect field-based industrial devices with enterprise asset management and computerized maintenance management systems (CMMS). With fine-grain data streams providing deep visibility into industrial infrastructure, organizations should have little trouble not only repairing and maintaining complex systems, but optimizing them for peak performance and productivity as well.

Adaptation without disruption

Change is never easy, particularly when it encompasses literally the whole of the manufacturing and distribution process. How are today's businesses supposed to prepare for this level of change without unwittingly disrupting their own processes? According to Maria Ferrante, senior director of marketing communications for the Association for Packaging and Processing Technologies, the key is to introduce systems and functions on a measured basis and then maintain adequate monitoring to ensure they are doing no harm. In the meantime, it will help to shore up support infrastructure, such as networking, to meet the added demands of M2M and device intelligence. Research firm The MPI Group estimates that about a quarter of manufacturers have deployed smart devices and embedded intelligence into the production lines, but far fewer have upgraded data infrastructure to handle the increased load.

In many ways, the IIoT will have a more profound impact on the world than the IoT. True, data is emerging as the new driver of economic growth, but at some point the improvement in data and data services has to translate into something real—a tangible asset that can be bought and sold. By improving the way their products are made, organizations will drive more value from both the product itself and the infrastructure used to create it.

To hear developer-led discussions and customer use cases on Big Data analytics, register for Hewlett Packard Enterprise's Big Data Conference 2016 in Boston, Aug. 29-Sept. 1.

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