Proving the Business Case for the Internet of Things

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The IoT. Where are we now? Where are we going?

Right now we're at the beginning of a rapid expansion of the Industrial Internet of Things (IIoT).  The McKinsey Global Institute predicts that the IoT will drive productivity growth of 2.5 to 5% over the next ten years, which translates into cost savings of $900 billion a year just for the manufacturing sector. 

We're also witnessing a slew of enabling technology developments.  Processing costs have declined dramatically in recent years and so-called multi-core chips allow intelligence and advanced computing power to be embedded in devices. Apps, software and operating systems can function autonomously and/or connect to other machines in a synchronized manner. GE (General Electric) calls them “Brilliant Machines”.

Where are we going?

Apart from onwards and upwards, the market is focusing on the deliverable, the information on which real-time, C-level decisions can be made.  The industry is moving away from the way data is delivered, the so-called value chain.  Telit and other leading vendors have been building bottom-up solutions that go from the edge of the network, where the devices are located, through to the Cloud and enterprise environments.  That is a done deal.
There isn't going to be any significant change to the value chain — data will continue to be acquired, aggregated, transmitted and processed - but we will witness the value of real-time intelligence being extended and enhanced.

The next level

Right now we can handle data and information in a structured and machine-readable way, but longer-term we need a deeper, semantic understanding of all that aggregated data. When information is enhanced in this way the intelligence is actionable and can be used, for example, by decision support systems.  

Semantically annotated m2m resources enable more meaningful descriptions: they provide consistent data translation and data interoperability between heterogeneous applications. Semantic descriptions are, in fact, necessary to secure interoperability between applications.  This is work in progress and it forms part of the mission of the European Commission's new Alliance for Internet of Things Innovation.
Self-learning systems are another interesting development.The main idea is to get computers to "learn" rules that are difficult for a human programmer to define using standard programming methods. It leverages massive amounts of data, internal, external, sensor, social and so on to identify and define associations between data sets. 

Finally, it's worth noting that machines don't solve real, complex business problems. That's what people do. Machines can compute at incredible speed. Only people can think creatively and in context.