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Agile Computing Authors: Yeshim Deniz, David Dodd, Bill Szybillo, Elizabeth White, Dana Gardner

Related Topics: @ThingsExpo, Java IoT, Mobile IoT, Linux Containers, Agile Computing, @BigDataExpo

@ThingsExpo: Article

Microsoft Product Mapping for the Internet of Things

The market potential for IoT is in the trillions of dollars globally per year and growing

As suggested by numerous reports and white papers by both big players and analysts, the market potential for IoT is in the trillions of dollars globally per year and growing. Microsoft has rightly adopted the enablement of IoT with appropriate platform and tools. The Microsoft Azure Intelligent Systems Service helps enterprises embrace the Internet of Things (IoT) by securely connecting, managing and capturing machine-generated data from a variety of sensors and devices. While some of these services are still under limited public preview gaining appropriate expertise will help in meeting the challenges faced by new era of Ambient Intelligence.

Microsoft's Big Push on Machine Learning
The next big thing in computing is derived out of using Machine Learning techniques. Microsoft has come up with some important announcements recently.

The following announcements were made by Microsoft CEO in a recent customer event in San Francisco on April 15.

  • Limited public preview of the Microsoft Azure Intelligent Systems Service. This new Azure service helps customers embrace the Internet of Things and securely connect to, manage and capture machine-generated data from sensors and devices, regardless of operating system.
  • Launch of SQL Server 2014. The latest version of the world's most widely deployed database delivers real-time performance with built-in in-memory technology and public cloud scale and disaster recovery with Microsoft Azure.

While these services are still under public beta and will take mainstream in a short while from now, the following reference architecture will help to make best use of them in the era of internet of things.

Reference Architecture for Internet of Things Intelligence
The following diagram shows a vendor agonistic view of an Intelligent Insight Enabler for Internet Of Things.

Event Producer
This layer represents the raw devices like sensors, machine sources which can generate massive quantities of events. By classical definition events does not mean anything disruptive or useful information always, most of the times they may be just raw messages which will not provide any meaning unless viewed within a context. This layer typically presents at , Ón Premise' mainly in plant floor, hospitals or even in homes.

Event Preprocessor
Events do get generated in massive quantities and most times event information is repetitive and not useful and hence event preprocessing layer will be useful to filter the duplicate and unwanted events and consider relevant events for further processing. Also events do get more significance if they are semantically enriched with context. While a more advanced form of semantic enrichment can happen in the next layer (Event Intelligence Processor), but basic semantic enrichment about the event like, it's location, relationship with other objects of interest will happen in this layer.

Event Intelligence Processor
This is the most important layer in the whole eco system and it typically present in cloud, given its needs to scale rapidly and handle massive quantities of data. It can typically utilize two kinds of processing to produce the intelligence from raw data.

  • In Memory Processor: In memory analytical engine for real time analytics needs.
  • Massively Parallel Processor: Batch engine to analyse even large quantities of data in near real time basis.

Intelligence processor will utilize second level of semantic enrichment which will further annotate the events beyond what is done by the pre processor. Enrichment at this stage will take care correlation among events from disparate sources. Finally the machine learning engine will utilize the past data conditions of the events and come up predictive outcomes which is the ultimate goal of the engine.

Event Insights Consumer
As evident from the name, Intelligence extracted by the Intelligence Processor' will be consumed by this layer using rich visualization features across multiple channels. This layer will also facilitate end user specific views, drill down and other dynamic filtering of intelligence output. It is quite possible that a IoT device could be a consumer of the machine intelligence generated, so that the preventive maintenance of the device can be taken care.

Microsoft Product Mapping For Internet Of things Ambient Intelligence
The following diagram shows the product mapping aligned with Microsoft vision of Internet of Things and associated Ambient Intelligence which can be drawn out of it. The product mapping boxes have been aligned with reference architecture so that a one to one mapping between the building blocks and associated products can be realized.

The following are the brief descriptions of the product mapping and their fitment , a detailed explanation about these products can be obtained from Microsoft web site and documentation.

Event Producer
The Windows Embedded family of operating systems and tools extends the power of Windows and Microsoft technologies, allowing you to create powerful, connected, industry devices and intelligent systems that can transform your business.

Event Preprocessor
Microsoft StreamInsightTM is a powerful platform that you can use to develop and deploy complex event processing (CEP) applications. Its high-throughput stream processing architecture and the Microsoft .NET Framework-based development platform enable you to quickly implement robust and highly efficient event processing applications.

Event Intelligence Processor
SQL Server 2014 delivers mission critical performance across all workloads with in-memory built in, faster insights from any data with familiar tools. It's In Memory analytics can process billion of rows in seconds as per Microsoft data sheet.

HDInsight is a Hadoop-based service from Microsoft that brings a 100 percent Apache Hadoop solution to the cloud. A modern, cloud-based data platform that manages data of any type, whether structured or unstructured, and of any size, HDInsight makes it possible for you to gain the full value of big data.

Polybase is a integration technology between structured data stored in SQL Server and Unstructured data stored in HDinsight HDFS. The Analytics Platform System brings Microsoft's massively parallel processing (MPP) data warehouse technology-the SQL Server Parallel Data Warehouse (PDW)-together with HDInsight, Microsoft's 100% Apache Hadoop distribution, and delivers it as a turnkey appliance. To integrate data from SQL Server PDW with data from Hadoop, APS offers the PolyBase data querying technology.

Though the Polybase technology is part of a platform appliance, it is expected that in a Hybrid Cloud scenario enterprises can always make use of it and this may technology may also be available as part of Azure later.

SQL Server Analysis Services is probably most important part of this whole solution. It is often under looked from its capabilities perspective. However it has got very important algorithms to provide the required Machine Learning Capabilities for Internet Of things domain. The following are the important algorithms that will play a major role in machine learning.

Event Insights Consumer
Microsoft Power BI for Office 365 is a collection of features and services that enable you to visualize data, share discoveries, and collaborate in intuitive new ways. Microsoft Power BI for Office 365 provides an organization-wide self-service business intelligence (BI) infrastructure, and brings Excel workbook sharing, online collaboration, and IT infrastructure together into a holistic offering.


As suggested by numerous reports and white papers by both big players and analysts, the market potential for IoT is in the trillions of dollars globally per year and growing. Microsoft has rightly adopted the enablement of IoT with appropriate platform and tools. The Microsoft Azure Intelligent Systems Service helps enterprises embrace the Internet of Things (IoT) by securely connecting, managing and capturing machine-generated data from a variety of sensors and devices. While some of these services are still under limited public preview gaining appropriate expertise will help in meeting the challenges faced by new era of Ambient Intelligence.

More Stories By Srinivasan Sundara Rajan

Srinivasan is passionate about ownership and driving things on his own, with his breadth and depth on Enterprise Technology he could run any aspect of IT Industry and make it a success.

He is a seasoned Enterprise IT Expert, mainly in the areas of Solution, Integration and Architecture, across Structured, Unstructured data sources, especially in manufacturing domain.

He currently works as Technology Head For GAVS Technologies.

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