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President & CTO / Cirrus Link Solutions
Arlen Nipper President & CTO / Cirrus Link Solutions
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Big Access: Unleashing the Real Value of Your IIOT Data
(without Big Access you can’t realize Big Data) Arlen Nipper President & CTO / Cirrus Link Solutions
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What is the difference between an embedded computer and a “Internet of Things” device?
“ An embedded computer system is typically any microprocessor-based device that encapsulates a basic process knowledge.” IT integration and communications connectivity is at best an effort in hindsight and at worst ignored altogether. “ Internet of Things provides technology and infrastructure to enable the process knowledge and associated parameters to be distributed within the enterprise … and beyond” IT integration and communications becomes a native capability of the system. So use the Pressure transmitter but tell the Peanut packaging machine story ONE TO ONE Versus MANY TO MANY I’ve wrestled with this question for the last 15 years of my career. The answer to this question lies at the core of whether the transition to the IoT will be successful or not. So tell the Zurich story here…. “ An embedded computer system is typically any microprocessor-based device that encapsulates a basic process knowledge.” Don’t Forget – results in the development of a protocol and result in an application that results in Connecting a device to an application! This way an epiphany moment to me because now I saw the disconnect between the “EMBEDDED”computer mindset and the rest of the world at large. Embedded devices use protocols. Embedded devices connect to applications. Pervasive devices use message transports. Pervasive devices connect to middleware. Connecting devices to applications versus the design of the Internet of Things. Peanut packaging machine example. I want to make a very important point here… we are talking about the “Internet of Things” and NOT the Internet of Devices! (smartphone, tablets, etc). So the easy stuff’s already been taken care of. Now the real IoT is staring us in the face. It figuring out how to get into the the deep vertical knowledge … the “process knowledge” of the many divergent sectors that use embedded computer technology today and make it to where these devices process knowledge can contribute in some way to the the larger IoT. How can we get all of these “Things” connected? When we set out to design an IOT Device the good news is that “We know what we know” …. We know exactly what the process is, what data is required, what the engineering units are, power requirements, memory footprint, etc, etc. The BAD news is that we don’t know what we don’t know. We don’t know how this device will interact with other devices it might be installed with, we don’t know what other interesting ways our device data might be used. This comes down to what we call Serendipitous Data Discovery It’s a producer/consumer model that is completely different from the Internet of People Lets do the math here. An IoT for RFID Tags… An IoT for smart meters… An IoT for medical devices… An IoT for industrial devices… … It will never scale! IoT sits between two very mature and entrenched engineering disciplines. On the one side you have conventional embedded products development in market sectors with entrenched notions, process, procedures, data representations and the “that’s the way we’ve been doing it for the last 30 years. On the other side of IoT you have the WEB Tooling moving at the speed of light in many cases developing technology looking for a solution. But IOT has to address both of these disiplines - Very HARD. Serendipitous Discovery “The many nodes of a network – be they machines, people, sensors or physical systems –may not be very “smart” in themselves, but if they are networked in a way that allows them to connect effortlessly and interpret seamlessly, they begin to give rise to complex, system-wide behavior that usually goes by the name “emergence.” That is, an entirely new order of intelligence “emerges” from the system as a whole – an intelligence that could not have been predicted by looking at any of the nodes individually. There’s a distinct magic to emergence, but it happens only if the network’s nodes are free to share information and freely participate in interactions.” Glen Allmendinger – Harbor Research, 2011
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The Journey ICC 2015 ICC 2016 ICC 2017 Leveraging IIoT Technology:
Building for Tomorrow with Ignition and MQTT ICC 2016 Accelerate IIoT Solution Deployment Using Ignition and MQTT ICC 2017 Big Access: Unleashing the Real Value of your IIoT Data
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The Sparkplug Specification
Sparkplug is a specification that defines how to use MQTT in a mission critical, real time environment. Defines MQTT Topic Namespace Defines MQTT Payload Definition Defines MQTT State Management High Availability / Redundancy / Scale
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Ecosystems for the Outcome Economy
“For industrial businesses ecosystems are unavoidable.” “They should first and foremost aim to create these as parts of viable networks of partners with the shared aim of developing new products and services targeted at outcome focused customers.” Industry X.0 Pages
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The Ecosystem
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New Features Automatic tag history during network outages.
Complex data type support (UDT’s, Datasets, Arrays, Files). Tag properties support. Redundant Ignition Gateway support. Historical Data Inserts for Store & Forward Supports MQTT JSON connections Support New Sparkplug B Complex Data Types Compression & Tag Name Alias Support Redundant Ignition Gateway Support Store & Forward Server Sets – Send data to multiple endpoints Compression & Tag Alias Name Support Custom Transmitters- Added Tag Tree Flexibility Redundant Ignition Gateway support
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Big Access Connect devices to infrastructure, NOT to applications. Secure, remote originated connections. Ultra efficient network bandwidth utilization. Send more data over the same bandwidth. Provide a “Single Source of Truth” for tags and associated properties. Demonstrate a superior OT solution. Provide Plug-and-Play functionality. Eliminate SCADA system “cutovers.” Provide unlimited tags and unlimited clients. “The transformation to IIoT will NOT be an IT-down-to-OT exercise. It will require empowering OT with the tools and technology to execute an OT-to-IT migration. “ The transformation to IIoT will NOT be an IT down to OT exercise. It will require empowering OT with the tools and technology to exercise an OT to IT migration.
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The World Today! We live in a brownfield environment
Assets and devices already deployed will be there for the next decade or even longer. ROI’s rarely provide the rip and replace scenario Therefore, we MUST demonstrate migration technologies that mitigates risk and provide operational integrity, safety, and security of the system as a whole throughout the migration process. What are the entrenched players in the market offering here? Their migration strategy maintains status quo lock in to their product line. A Rip and Replace approach.
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The Power of the Ignition Platform
To migrate the brownfield world driving the business requirements, a “Swiss Army Knife” of tools is essential and Ignition. Ignition is much, much more than HMI / SCADA… MQTT to OPC-UA Bridge OT to IT Bridge MES & OEE Out at the Edge with Reporting & Alarming Cloud Connectivity
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Big Access to Big Data: Enable Ignition Connections to Cloud Services
These new Injector modules easily connect any tag data from the Ignition platform into the Amazon Web Services (AWS) and/or Microsoft Azure cloud services infrastructure. With a simple configuration, tag data will flow into the AWS or Azure cloud Big Data services. Connects to any TAG Data Easy to Configure Same efficient tag reporting scheme as used in MQTT Transmission For use on Gateway or Edge Supports Store & Forward – Coming Soon!
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AWS Injector Amazon Web Services Operational Data Serving Tier
Data Science Sandbox Operational Data Amazon Aurora Clusterless SQL Query Amazon Athena Amazon ElastiCache Relational Database Redis Amazon Redshift Data Warehouse Amazon DynamoDB NoSQL Database Amazon S3 Data Lake Batch Analytics Amazon Glue Visualization / Reporting Clusterless ETL Data Sources Any Open Source Tool of Choice on EC2 Amazon EMR Amazon Kinesis Streams & Firehose Hadoop / Spark Amazon Machine Learning Streaming/Real-time Analytics Predictive Analytics Streaming Analytics Tools AWS Lambda Spark Streaming on EMR Amazon Elasticsearch Service Apache Storm on EMR Apache Flink on EMR Amazon Kinesis Analytics
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Azure Injector Communication Transformation Storage Analytics
Visualization Operational Data Azure SQL Database Azure SQL Data Warehouse Web App Stream Analytics DocumentDB Azure IOT HUB Storage Blob HDInsight Data Factory Storage Table Machine Learning Cortana Data Lake
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Unleashing The REAL Value of Big Data
The Power of Big Data, Predictive Analytics & AI Gain insight needed to deliver intelligent actions Increase Revenue Lower Costs Improve Safety Increase Productivity We understand the Why? With Ignition and Cirrus Link, you have to the tools to Deliver!
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Big Access to Big Data to Real Value
Legacy SCADA Ethernet Azure IoT Hub VSAT OPC Cellular Kinesis DynamoDB TLS MQTT Server Infrastructure Leak Detection DMZ ACL The transformation to IIoT will NOT be an IT down to OT exercise. It will require empowering OT with the tools and technology to exercise an OT to IT migration. MES OEE Track Trace
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Call to Action Download Experiment
Demo – Brownfield to Cloud in 30 minutes Expose End Users and Line of Business Owners Implement Real IIoT – Real Value – Available NOW!! The transformation to IIoT will NOT be an IT down to OT exercise. It will require empowering OT with the tools and technology to exercise an OT to IT migration.
