Towards a seamless integration of the physical and virtual worlds

Our day-to-day lives are being filled with
more and more devices that let users find out the status of an object via the
Internet or the Cloud. Examples of this trend include fitness-trackers, sensors
that monitor plants’ moisture levels, and houses that learn to set their heat
and lighting to f

This paradigm of the Internet of Things (IoT) opens up immense opportunities for
Siemens. After all, Siemens is a major player in combining hardware and
software – for example, in automation solutions for production, in rail and
traffic management systems, and in the decentralized delivery of electric
power.

All the same, factories, traffic networks and
utility grids are a good deal more complex than smartphones and fitness tracker.
All are examples of real and virtual systems that have been intermeshed and
that often even involve critical infrastructures. Customers in such critical
areas have entirely different expectations about safety, reliability and
durability than those purchasing a smart thermostat or plant moisture tracking
system. What’s more, such customers want to enrich their existing equipment
through the advantages of the evolving digital universe without endangering or
sacrificing either data protection or intellectual property.

That’s why Siemens has expanded the concept
of the Internet of Things for industrial applications to create the Web of
Systems, meaning systems that are digital, communicate with each other, and can
act autonomously. Siemens’ vision is that as this ecosystem takes shape its
elements will be managed via future Web technologies that use standardized
protocols and languages of the kind that are used for the Internet today.

This linking up of the real world and the
virtual world of data offers multiple advantages for Siemens customers. It
enables them to capture and analyze the current status of a system and its
parts anytime, in detail. This in turn yields immense opportunities for savings
through predictive maintenance, as well as major potential for optimizing
systems. Using today’s technologies from the World Wide Web environment,
systems can often be implemented and commissioned faster and more economically.
A system’s intelligence can be distributed as needed between real components
and virtual systems in the Cloud, resulting in enhanced robustness and customer
data protection.

Finally, as the digital landscape is
transformed along these lines, it will become easier to update systems with new
functions, or to update system software on the fly, in much the same way as
smartphones and other devices are updated through apps.

One of many examples where our Web of Systems
offers advantages is smart grids. Until just a few years ago, electric power
grids were organized in a strict hierarchy. But today they’ve become
decentralized systems. Photovoltaic installations and other renewable energy
sources feed electricity into the grid on an unregulated, fluctuating basis, at
voltage levels that used to apply only to consumers, not generators. In a
worst-case scenario, that can make a grid unstable.

So grids have to be given the ability to
counteract that shifting environment. One component here is distribution
transformers that can adjust independently and cooperatively to smooth out
voltage fluctuations within their local areas. But for that they need their own
intelligence and communication capability – in other words, they need to be
“smart” and networked. And this is where one important difference from the
typical Internet of Things scenario comes in. The Internet of Things is
connected to the Cloud, and the Cloud is where the data – for example from the
equipment’s sensors – is primarily processed. Response times and reliability
are often a secondary priority. But in a Web of Systems, things themselves have
intelligence. They can respond locally, fast, and reliably, while at the same
time drawing on the power of the Cloud for optimization.

In order to realize the vision of a Web of
Systems, associated software has to be able to understand the data, so it can
derive intelligent conclusions from it. And that’s possible only if information
that describes the data’s meaning is either already present or supplied
alongside it. Human experts can respond to this kind of challenge because they understand
the context in which data is embedded. But software has to be told the context
explicitly. Yet that context includes important information about the system in
question and its associated processes, which in many cases are valuable
business secrets that an operator would be very unwilling to deliver unfiltered
into the Cloud. In view of this, it is better if machines can draw conclusions
themselves, locally, so that the context remains protected. With regard to
distribution transformers, for instance, they can assess independently whether
to smooth out a critical grid state or whether they will need help from a
higher level, thus ensuring a high level of data protection by restricting
secrets to local systems.

Although localized, this information can
nevertheless be used to generate value – for example by using predictive
maintenance or developing new services. To make use of this and other data from
industrial systems, trains or gas turbines, Siemens relies on Sinalytics. This
is a new platform for industrial data analysis that makes it possible to offer
new digital services to every customer. Sinalytics processes data from many
different distributed systems and their sensors in real time and also supports
local data processing directly in devices.

Another advantage of the Web of Systems
approach is that it opens the door to a platform approach in which functions
can be distributed and installed like apps, and run in much the same way. For
example, services can easily be distributed that make the systems environment
more attractive not just for Siemens, but for its customers and even their own
customers. In such an environment, a distribution transformer could, for
instance, run applications for energy-efficient management of neighborhood
street lighting. When an update is due or a new function is needed, the
software can be uploaded remotely.

The smart distribution transformer – a new
Siemens development – is already being used in practice for voltage regulation
in the low-voltage grid, and is thus a key part of a future system known as an
intelligent secondary substation node (iSSN). With its computing power and
optional communication connection, the iSSN will provide the possibility for
far more than supplying households with the right voltage. It will enable the
power grid to cope with additional feed-ins or loads with no need for massive
infrastructure expansions.

This iSSN is currently being developed
further in the context of the Web of Systems project. Its Web connection, for
example, will make it significantly easier to commission, maintain, and update
it. And each such substation will supply a wealth of data that will make it
possible to identify potentially destabilizing grid conditions, thus providing
an important additional tool for predictive power grid planning.

But a distribution transformer doesn’t add up
to a Web of Systems all by itself. The other components in the electric network
– meters, building distribution systems, photovoltaic systems, electric cars –
must also be equipped with sensors, local intelligence, and the ability to
communicate. That is already becoming the case. For Siemens, that means new
opportunities in virtually every one of the sectors in which it does business.

Siemens is already using Webs of Systems to
implement solutions that used to involve a great deal of engineering or
installation work. One example is the electric bus charging system that Siemens
has installed in a number of European cities. Here, everything from bus
electronics and fast charging stations to the management backend systems
communicate over the Web in order to coordinate and optimize the charging
process.

Another example is the optimization of water
distribution networks with a sensor network that detects leaks and minimizes
pumps’ energy consumption. An important point here is that data integration is
taking place in the context of existing control systems. Siemens is looking at
similar situations in many other existing installations. The reason for this is
clear: customers want the reliability and flexibility that are the hallmarks of
advanced digital systems. The Web of Systems can be the essential key to
opening up these benefits.