Real-time data Integration on the Cloud :: Sensors, Industrial IT and Smart grids,OPC-UA demonstration

The objective of this post is to share my  thoughts that

  • There is a huge scope for integrating and processing real-time data/ information on the Cloud. There are several industries/verticals where this may be enabled and leveraged.Optimal reaction to dynamic business scenarios requires real-time knowledge based on events that occur, or will occur.
    • There is scope for a number of ‘Application scenarios’ to integrate real-time information to the cloud.
  • Leveraging Cloud computing may offer several business benefits for organisations producing real-time data. (Cost,Productivity & Efficiencies,Reduced risks,Improved ROI etc)
  • Cloud provides a significant opportunity to enable extremely powerful and smart real-time information processing in an  inexpensive manner which may not have been possible until recent times. This may be more interesting for small and  mid size organisations (SMB) who didn’t  have access to expensive computing systems and software or who didn’t have the funds. (SMBs :- Both end users and Solution providers)
  • Real-time data+Cloud computing provides an opportunity to accelerate innovation in new ways for the end users as well as for solution providers.
  • OPC-UA   and its eco-system in my view point is a significant enabler in realizing the above (See demo video below)
  • Demonstrate a prototype app. I have developed (See Video below)

The Real-time  Context

The context of my post here basically pertains to scenarios where  real-time data is received from the field and onboard sensors. While I wouldn’t not discuss about sensors ,it’s just the fact that   most of the real-time scenarios considered mostly deal with sensor-fusion.

I would like to classify the scope and case for this in to three broad areas

a. (Real-time) Industrial IT Systems which has a huge scope in this context and probably has more drivers for Cloud enablement
b. Non-Industrial Real-time systems (e.g. Automotive & Transportation,Medical & Healthcare , Building & Facilities management etc)

c. Smart grids  (digitally enabled electrical grid that gathers, distributes, and acts on information about the behavior of all participants (suppliers and consumers) in order to improve the efficiency, importance, reliability, economics, and sustainability of electricity services) .

Industrial IT :

Industrial IT is typically related to processing information in process and production oriented industries . Significant  part of this includes processing real-time data and information. from  process control,PLC and SCADA Systems.(Primarily sensors driven)

Industrial IT for instance deals with

  • Enterprise shop floor integration
  • Enterprise real-time performance management
  • Management of production and supply chain optimization
  • Operations reports (dash boards) and Active risk management

Chemical,Oil & Gas,Power&Energy,Steel,F&B,Manufacturing industries rely heavily on Industrial IT. Some of the global vendors in this space are Siemens,ABB,Allen-Bradley,Honeywell,Omron,Honeywell,Johnson controls so on.

Non-Industrial Real-time Systems :-

I would consider real-time data from Medical,Automotive,Transportation, Building and Facilities management sensors and Information systems.


Real-time data and cloud computing context to smart grids can be related to concepts,products and organisations working on digitally enabled electrical grids.(Also related to the above) 

Smart Grids can have some co-relation to products or industries pertaining to a and b cited above. They deserve a special treatment there is a significant  scope and opportunity to apply real-time data integration to Cloud computing and innovate. I believe this area requires a special attention.

IDC predicts a number of things to emerge in the smart grid space such as

Yesterday, Gigaom had published a very interesting article about some of the emerging start up companies in the smart grid business. I suggest a read  and visiting the websites of some of the companies mentioned (eMeter,Ecologic Analytics,Opower,Control4,Axeda,First fuel software,Regen energy,GridMobility)
These companies  integrate and process real-time data, some or perhaps all of them on the cloud in their products.

Hard Vs Soft-realtime systems  (Caution)

All the thoughts  that I have shared here deals with scenarios that typically has a “near real-time” characteristic. Integrating Hard-real-time systems especially their critical functions on the cloud may not be feasible at this point of time in my understanding.

Importance of OPC-Unified Architecture (OPC-UA)

I wish to stress the importance of seriously evaluating and considering OPC Unified Architecture (OPC-UA) in enabling real-time data integration to the Cloud. OPC-UA is OPC foundation’s next generation technology for secure,inter-operable transport of raw data and pre-processed information from  the plant floor.

While OPC-UA widely deals with Industrial IT/ shop floor sensor ,monitoring & SCADA systems, OPC-UA standards based modules are today are available for popular building management systems(Johnson controls),embedded real-time operating systems such as QNX Neutrino and Altys etc.

It is also available in Integrated chips (micro-controllers and processors)! This means virtually any real-time sensor or a system supported by these vendors can be made OPC-UA Aware.

Benefits of OPC-UA standards based integration

Excellent portability and interoperability means less vendor lockins and wider integration possibilities – Time to deliver solutions can be slashed.

Several Realtime hardware and software vendors are supporting OPC-UA in their products and an equal  number of SDKs are available – Wider choice, flexibility,easy portability

For instance, the OPC-UA Client application I have written in the demo cited  below,can be seamlessly connected to different vendor’s realtime systems
(e,g. Siemens,Rockwell,ABB,Honeywell,Jonson controls so on). This is a huge benefit.

Standards based implementation – This means existing technologies and skills can be applied effectively.

Support available for various industry standard platforms (OS) and different programming languages like Java,Python,C#,Perl etc – Existing resources can be efficiently used. Software developers can apply their existing skills with less learning curve and be highly productive.

Essentially OPC-UA fosters transparent implementation,productivity,efficiency,better ROI and Innovation

Leveraging Cloud computing

Now with powerful standards  based OPC-UA interfaces , there are powerful means of  integrating (near) real-time data from the real-time sensors and field systems to Cloud based application services that can effectively process the information. Powerful and intelligent application services can be developed and deployed to derive more value out of the real-time data that is integrated for a business. Realtime information and Cloud computing is a very potent combination that is evolving at present.

With the assumption that you are aware of the basic models and advantages of Cloud computing. I would like to share some of the areas and application scenarios where I believe there are significant opportunities to integrate real-time information/data to the cloud .

I have provided this information as a presentation that you can view below. As mentioned in my presentation, There is a huge scope to leverage cloud computing model in key areas such as

  • Moving [Logging]  , Analyzing and presenting real-time data on the cloud (Organisational Intelligence)
  • Analyzing and Processing large volumes of data ( Big-data) correlated to realtime data streams  for various technical and business objectives (Realtime analysis,data mining, analytics,optimization,decision-making etc)
  • Complex event processing (Realtime information processing,smart logic,decision-making, Multi-channel and Intelligent information delivery etc
  • For most of these things, the availability of huge computing power provided by the cloud combined with its elastic nature and different services (Server,DB,Messaging,Automation etc) on a pay-per use model offers significant benefits.

Real-time data integration to the cloud 

Demonstration of OPC-UA based Real-time data integration to  the Cloud

Below is a Video where  I talk about this and demonstrate a prototype software I have developed to  integrate Real-time data to the Cloud . I have  used a OPC-UA Simulator from HB-Softsolution e.U.,Germany for sensors and data. The demo is about sending alarm event data based on a monitored (fire)sensor to the cloud and processing it to make an outbound telephone call through a cloud telephony service that will use pre-defined text to voice conversion based on alarm event process to intelligently notify people who can take action.

Real-time data integration to the cloud 

Mentions : I would like to thank Mr.Hannes Bichler from HB-Soft Solution e.u,Germany   who provided me quick support  inspite of the holiday times last week,while I developed my prototype application. Not to mention that HB-Soft Solutions’ OPC UA SDK is a powerful and impressive product.


I believe there is a lot of work that can be done in the confluence of real-time information systems and Cloud computing. It is a promising area to explore further    in the next few years with the advancements in technologies in sensors,real-time systems,cloud computing and a bunch of other Information technologies. I believe that there is scope for significant innovation across a gamut of  industries under this eco-system. I believe it presents opportunities to evolve disruptive business models and organisations enabling such models offering tremendous value and wealth creation possibilities to owners and end users.

Further work..

I am presently exploring/working on certain ideas and initiatives on this front

I would be interested to collaborate with individuals or organisations  who are working in this space. my contact- sankar[at]cloudshoring[dot]in

Thanks for the time and patience  in reading this long post!


About Cloudshoring

Cloudshoring is a popular blog on Cloud computing and Big data
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