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Home Solutions Industrial Machinery Solutions Smart Machine Control A Practical
Guide for Connecting LabVIEW to the Industrial IoT
A PRACTICAL GUIDE FOR CONNECTING LABVIEW TO THE INDUSTRIAL IOT
Updated May 22, 2023
*
*
OVERVIEW
In this white paper, learn about the three most prevalent communication
protocols to connect to cloud-based development platforms for Internet of Things
(IoT) applications. You can also find information on some of the most common IoT
cloud development platforms such as Amazon Web Services, IBM Bluemix, PTC
ThingWorx, and Microsoft Azure. Plus, learn how to connect an NI embedded
system, such as CompactRIO, to these cloud platforms through the LabVIEW open
graphical development environment.
CONTENTS
* The IoT Will Change the World
* MQTT
* AMQP
* DDS
* Amazon AWS IoT
* IBM Watson IoT for Bluemix
* PTC ThingWorx
* Microsoft Azure IoT Suite
THE IOT WILL CHANGE THE WORLD
The world economy will greatly change in the next decade as new Internet-enabled
applications are rolled out. Some of these applications are likely to be
disruptive and innovative as well as have a large economic impact. This will
affect many industries and sectors, as already seen in consumer sectors like
hotels (Airbnb) and taxis (Uber).
This trend is also noticeable in the industry, for example, Germany’s Industry
4.0 initiative. Within Industry 4.0 or the Industrial IoT (IIoT), the focus is
on integration and better use of existing technologies. In this sense, industry,
machines, products, and people are all digitally connected. Manufacturers are
mass producing bespoke products in quantities of one. Intelligent software in
the cloud connects enterprise IT systems with the operational world, machines,
devices, and sensors to control and optimize production flow.
Figure 1 – Common Architecture of the Industrial IoT: Intelligent Edge Nodes
Connect Sensors, Actuators and Devices to IT Systems
Because of the decrease in cost of connectivity, processing devices and sensors
adoption of IIoT has grown tremendously. Sensor data can be captured and
preprocessed close to the machines by a smart edge device such as a CompactRIO
or a PXI automated test system. The edge device can send the data in real time
to the virtual world (IT cloud platform) where it can be stored, monitored, and
analyzed or trigger an action.
The value of the IIoT is not in the connectivity of the devices, but in what a
company unlocks from the stream of data the smart devices supply. Cloud
computing platforms and their services help provide this insight.
Many significant challenges need to be taken into account when implementing an
IoT solution. Challenges such as standardization, interoperability, Big Analog
Data™ handling, security, and privacy. It is important to be aware of these
challenges and give special care to security. Security is a crucial component
for any IoT application. IIoT devices should enforce a strong security policy
and be updated regularly with the latest security patches. To learn more about
best practices for security on CompactRIO and receive the latest security
announcements from NI, visit ni.com/support/security. All cloud computing
platforms securely send and receive data, use strong authentication and
authorization methods, and use encryption. The majority also have audit
capabilities.
CLOUD COMPUTING
Cloud computing refers to a flexible way of delivering hardware, software, or
data resources via the network on a user’s request. This is opposite to the use
of running a software application on a local computer.
Figure 2 - Overview of Cloud Computing Elements (image source: Sam Johnston
https://commons.wikimedia.org/wiki/File:Cloud_computing.svg)
The table below shows three service levels of cloud computing that are commonly
encountered.
SaaS
Software as a Service
Provides a full business service. The service provider runs and manages the
complete platform. Examples: Gmail, Salesforce.com
PaaS
Platform as a Service
Provides a platform. You need to build and deploy your own cloud application,
leveraging the run time and services the vendor provides. Examples: IBM Bluemix,
Microsoft Azure, AWS IoT
IaaS
Infrastructure as a Service
Provides the basic building blocks such as server hardware, storage, and network
capabilities. You may need to install the OS and applications. Examples: Amazon
EC2 (a virtual machine that Amazon provides to you), IBM SoftLayer
Clouds can be deployed as public—all services run in a secure environment hosted
in the cloud, where servers may be shared with others—or private, which is
available only to the user’s organization and may exist on or off premises. In
addition, clouds can be deployed as hybrids, where parts are on premises and
other services are in the cloud.
IOT APPLICATION PROTOCOLS
Communication protocols are responsible for the network connectivity to the
server. Protocols like Wi-Fi, Ethernet, cellular, and LoRaWAN are all
communication protocols that provide this level of connectivity. Application
protocols sit on top of them to communicate application-specific messages.
Multiple standards handle the communication between devices and the cloud. As
application requirements differ, specific IoT protocols have been developed and
therefore the confusion is understandable. Protocols may even have multiple
implementations and IoT platforms may have proprietary IoT solutions. To provide
a universal solution, devices, applications, and platforms need to be
interoperable. NI embedded systems provide an excellent solution by being open
and flexible. This success is achieved through the NI Linux Real-Time OS,
support for LabVIEW graphical and C/C++ programming environments, as well as
several Linux packages available through the vibrant ecosystem.
At a high level, there are three main use cases for the application protocols:
device to device (D2D or M2M), device to server (D2S), and server to server
(S2S) communication. IoT application protocols have different levels of
real-time behavior and other characteristics. The table below provides an
overview.
COMMON APPLICATION PROTOCOLS FOR IOT CONNECTIVITY
HTTP/HTTPS
WebSocket
DDS
MQTT
AMQP
Description
Transmit data over Internet from applications, websites, and so on
Transmit data over Internet from applications, websites, and so on
Communication bus to connect intelligent machines
Lightweight protocol for collecting data and publishing it to servers and
subscribers
Queue system to reliably transfer messages between applications and processes
(servers)
Typical Use Case
Web
Web
D2D
D2S
S2S, (D2S)
Real-Time Behavior
No
No
Yes, us–ms range
No, ms–s range
No, seconds range
Messaging
Request/Response
Request/Response
Databus
Publish/Subscribe
Publish/Subscribe
Transport
TCP
TCP
TCP, UDP, shared memory, and so on
TCP
TCP
Security
Yes: HTTPS (SSL or TLS)
Yes: wss:// (SSL/TLS)
Yes
Possible: SSL or TLS
Yes: TLS or SASL (Simple authentication and Security layer)
LabVIEW Support
Yes, native
Yes, via VI Package Manager (MediaMongrels)
Yes, via VI Package Manager (RTI)
Yes, Implementations on VI Package Manager, LabVIEW Tools Network, and GitHub
Implementations on VI Package Manager (LabbitMQ) and GitHub
Quality of Service
No
No
Yes, over 20 levels
Yes, 3 levels
Yes
The next section describes the most common protocols, MQTT, AMQP and DDS, in
further detail.
Back to top
MQTT
Message Queueing Telemetry Transport (MQTT) is an IoT connectivity protocol.
MQTT is used in applications with thousands of sensors, including power usage
monitoring and oil pipeline monitoring. MQTT is efficient in terms of bandwidth,
battery, and resources. MQTT uses a publish/subscribe model. The IoT devices
publish data to an MQTT broker over TCP as a topic. An authorized client can
subscribe to any topic and receive the value from the broker as they arrive from
the publisher. The publisher (device) does not need to know about any of the
subscribers, which makes the management easier at the device level. The broker
can support multiple concurrent connections from many devices. A topic is a
simple string that can have hierarchical levels and supports also wildcards. An
example of a topic is GothamCityPlant/Building1/Pump7/Power. The message data is
transmitted in JSON format and may be specific to the cloud platforms’ IoT
service.
Figure 3 – Edge Devices Sent MQTT Messages over the Internet to a Central Broker
Which Distributes the Messages to Authorized Subscribers
MQTT supports three quality-of-service levels:
* QoS 0—At most once
* QoS 1—At least once
* QoS 2—Exactly once
MQTT can be implemented using standard HTTP calls within LabVIEW. NI Partner
Program and other third-party implementations exist on the NI Tools Network and
GitHub.
To debug MQTT communications, a MQTT client can be installed on a local
computer. A popular free MQTT client is MQTTfx, available at mqttfx.org/.
Several MQTT brokers to test communication are on the Internet. One of the most
popular is mosquitto. To test the communication, you can publish topics to
test.mosquitto.org. The mosquitto broker is open source and can also be used
in-house for sandbox testing or production use of MQTT communication.
Back to top
AMQP
Advanced Message Queuing Protocol (AMQP) is an open message protocol that can
send transactional messages between servers and from devices to servers and vice
versa. Advantages of AMQP are the reliable communication (data is received
reliably exactly once at the receiving end) and interoperability. AMQP uses a
broker to receive data from a client. The client (or publisher) then publishes
the message to the broker, where it is processed and routed to a queue. From the
queue, the message is sent to any client who has subscribed to this data. AMQP
focuses on tracking all messages and ensuring each is delivered as intended,
even if a device is temporarily offline. Devices that generate loads of data can
stream to AMQP servers, which is then consumed by receivers to perform
monitoring and analytics. An example application for AMQP is the analysis of
automotive driving behavior at the data center. Some cloud development platforms
support device connectivity to AMQP or AMQP over WebSocket. Popular open-source
AMQP brokers you may come across are RabbitMQ, ActiveMQ, and Kafka.
LabbitMQ is an AMQP library for LabVIEW that can be installed from the VI
Package manager. An open-source AMQP client implementation in LabVIEW is
available on GitHub.
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DDS
The Data Distribution Service (DDS) main use case is to distribute data directly
to other devices, although it can also distribute data to enterprise systems and
mobile devices. Applications are found in wind farms, automotive test, asset
tracking, and defense and big physics. Devices often need each other’s data in
real time measured in milliseconds. All of this needs to happen reliably and
usually with large data streams. DDS offers a detailed quality of service
control, with configurable reliability, redundancy, and filtering, and selects
exactly which data goes where. To do so, DDS uses a device-to-device bus
communication, which can deliver the data to thousands of devices.
LabVIEW support for DDS can be installed through the VI Package Manager. RTI
provides an excellent tutorial on the use of DDS with LabVIEW.
CLOUD DEVELOPMENT PLATFORMS
Disclaimer: National Instruments does not endorse any cloud platforms. The
intent is to give a brief introduction to the major platforms. You should make a
thorough investigation before deciding which platform is most suitable for your
application.
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AMAZON AWS IOT
Amazon Web Services (AWS) offers IT infrastructure as cloud computing, database
storage, content delivery, and more. AWS IoT is a managed cloud platform that
enables devices to connect and interact with other AWS cloud applications and
services through a rules engine. AWS IoT also provides a device gateway and
device shadows. The device gateway is the service that manages the device
connectivity to AWS IoT and supports MQTT, WebSocket, and HTTP protocols. Device
shadows can create a virtual device that retain the device’s latest state, even
when it is offline. Applications within AWS can publish to the virtual device
and when the device is back online, the state is synchronized. AWS provides
open-source IoT SDKs to help connecting hardware devices with AWS IoT.
AWS uses an IoT rules engine that applies an SQL-like syntax to select data
received from a device and perform actions. The rules engine makes it possible
to build IoT applications that can gather, analyze, process, and act on the data
received from the device. The rules engine can route the message to AWS
endpoints like AWS Lambda (a compute service to run your uploaded code), Amazon
Kinesis (to process a large stream of data in real time), Amazon S3 (simple
storage service), Amazon Machine Learning, Amazon DynamoDB, and many more.
NI provides a free toolkit through the LabVIEW Tools Network to connect your
LabVIEW applications to AWS S3, SNS, SQS, and IoT services directly to enable
cloud storage, push notifications, and more.
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IBM WATSON IOT FOR BLUEMIX
Bluemix, IBM’s cloud development platform, is a PaaS. With Bluemix, you can
access IBM software for services like “big data” analytics, storage, databases,
security, IoT, cognitive applications, and more.
Watson IoT for Bluemix lets an application communicate with the connected
devices and consumes data received from those devices and device gateways. MQTT
is used to communicate with the devices and gateways. Devices can securely
connect to Watson IoT using MQTT over TLS.
The device needs to be registered with IBM Bluemix before an MQTT connection can
be established with the Watson IoT MQTT broker. Rules and logic to handle the
data can be defined in any of the languages that IBM Bluemix supports, such as
node.js (Node-RED), Java, Python, and more.
The LabVIEW Tools Network contains an example to connect CompactRIO and a
detailed description for IBM Watson IoT for Bluemix.
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PTC THINGWORX
ThingWorx is a model-based IoT application development platform that provides a
complete application design, run time, and environment. ThingWorx provides
components for connectivity, analytics, collaboration, and visualization
including augmented reality. The core development features of the platform are:
* Composer—An application modeling environment to model the “things,” logic,
visualization, data storage, and security
* Mashup builder—A web page is called a mashup with ThingWorx, and
visualization of web pages can be created using the mashup builder tool
* SQUEAL—A search feature that allows searching through all data in a model
* Execution engine and storage—Event-driven platform for execution and storage
to store, relate, and expose big data to make it valuable and actionable
ThingWorx supports device connectivity in several ways: direct network
connections, MQTT and AMQP, third-party device clouds, and OPC-UA connectivity
through PTC Kepware software.
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MICROSOFT AZURE IOT SUITE
The Azure IoT Suite allows data collection from devices and provides a set of
services like data analysis, data storage, real-time and historical data
visualization, and integration with back-office systems. The Azure IoT hub
receives the data from IoT devices. The device data can then be stored or passed
on for further processing, analytics, and management. Devices can communicate
with the IoT hub over HTTP, MQTT, or AMQP protocols. Microsoft offers a set of
Azure IoT device SDKs through GitHub.
Other cloud platforms are available, such as Google Cloud Platform, GE Predix,
and many more. For more information, see the vendor’s specific product pages.
NEXT STEPS
* Watch a webinar on connecting LabVIEW to the Industrial IoT
* Explore the importance of testbeds for the Industrial Internet of Things
(IIoT)
* Learn about using LabVIEW to communicate with industrial IOT equipment
APPENDIX A: OVERVIEW OF 4 MAJOR IOT CLOUD PLATFORMS
AWS IoT
IBM Watson IoT for Bluemix
PTC ThingWorx
Microsoft Azure IoT
Free Evaluation
1-year free trial
30-day trial, then free Lite version
30-day trial
IoT Hub free trial for unlimited time
Pricing
Usage basis, no minimum fees
Pay per device, data exchanged, data stored
Subscription, then pay depending on usage
Usage based (No. of IoT Hub messages)
Deployment Options
Public cloud
Public or private
Private or hybrid
Public, private, or hybrid
Getting Started Materials (Tutorials, White Papers, and Videos)
Yes
Yes
Yes
Yes
Platform Access Options
GUI, CLI
GUI, CLI
GUI
GUI, CLI
MQTT Support
Yes
Yes
Yes
Yes
MQTT WebSockets
Yes
Yes
Not Specified
Yes
AMQP
Use SQS instead or 3rd party
Through 3rd party
Yes
Yes
AMQP WebSockets
–
Through 3rd party
Not Specified
Yes
Data Format
JSON
JSON
JSON
JSON
Storage
S3 (files), DynamoDB (NoSQL database), Redshift (database), and others
Cloudant (NoSQL database), Mongodb, and others
Data tables, streams, and value streams
SQL storage, DocumentDB (NoSQL), blob storage (files), and table storage
LabVIEW Connectivity
Yes, LabVIEW Cloud Toolkit for AWS; MQTT
Yes, MQTT
Yes, MQTT/AMQP
Yes, MQTT/AMQP
Device SDKs Available
Yes
Yes
Yes
Yes
Rules Engine
Yes, rules engine acts on the data and routes onto other services
Yes, that is, node.js application
Yes, Expression Widget
Yes, Azure Stream Analytics
Visualization of Data
QuickSight or custom development
Yes, Watson IoT Real-Time Insight
Yes, ThingWorx SQUEAL, widgets, Vuforia, and Mashup
Via Azure web apps, power BI, and notifications
Platform Real-Time Streaming Analytics
Amazon Kinesis
IoT Real-Time Insights, IBM Streaming Analytics
Yes
Stream Analytics
Platform Machine Learning
Amazon Machine Learning
IBM Predictive Analytics
Predictive Analytics
Azure ML
Security
TLS/SSL
TLS
TLS
TLS/SSL
The table features out-of-the-box capabilities. Often features can be added by
installing additional services.
APPENDIX B: SOURCES
AWS https://aws.amazon.com
IBM http://www.ibm.com
Intel http://www.intel.com
PTC
http://www.ptc.com/internet-of-things/technology-platform-thingworx
NI
http://www.ni.com/nl-nl/innovations/industrial-internet-of-things.html
Electronic Design—Understanding the protocols behind the internet of things
http://www.electronicdesign.com/iot/understanding-protocols-behind-internet-things
Internet of Things (IoT) Development Platforms—A case of IBM Bluemix, P Kumar,
Univ. of Koblenz-Landau
https://kola.opus.hbz-nrw.de/frontdoor/index/index/docId/1373
IoT Standards and Protocols
https://www.postscapes.com/internet-of-things-protocols/
Industrial Internet of Things Platform Comparison
https://www.mandsconsulting.com/industrial-iot-platform-comparison
Books:
Internet of Things, W. Vermeend, J.W. Timmer, 2016, ISBN 97890821993-4-5
Enterprise IoT, Naveen Balani, 2016, ISBN 9781535505642
The registered trademark Linux® is used pursuant to a sublicense from LMI, the
exclusive licensee of Linus Torvalds, owner of the mark on a worldwide basis.
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