MATLAB and Simulink for IoT Applications

MATLAB® and Simulink® can help you design, prototype, and deploy IoT applications such as predictive maintenance, operations optimization, supervisory control, and more.

  • Access and preprocess streaming and archived data using built-in interfaces to cloud storage, relational and nonrelational databases, and protocols such as REST, MQTT, and OPC UA.

  • Design custom IoT analytics and algorithms quickly from thousands of proven, prebuilt functions for topics such as data cleaning, machine and deep learning, computer vision, controls, and optimization. Use existing functions, customize them, or create your own.

  • Develop data-driven and physics-based models to understand, control, and optimize your connected things and create digital twins.

  • Deploy MATLAB analytics and Simulink models to your choice of asset, edge, or cloud by automatically generating C/C++, HDL, PLC, GPU, .NET, or Java® based software components.

  • Use ThingSpeak™, a ready-to-run IoT platform with MATLAB analytics, to prototype and operationalize smaller-scale systems.

Use MATLAB and Simulink for Internet of Things

Access Streaming and Archived Data

Use MATLAB with big data to develop your algorithms. MATLAB supports time-stamped and unstructured data from many sources including cloud storage services (e.g., AWS S3, Azure Blob), OPC UA, RESTful web services, and databases. Work with live data from connected assets by integrating MATLAB with message brokers like MQTT and streaming protocols such as Kafka.

You can easily perform data munging and cleaning using built-in features to replace missing or erroneous values, smooth data, and align data sets that use different timestamp formats.

Develop Analytics, Control, and Optimization Algorithms

MATLAB provides thousands of functions for IoT application development, including for predictive maintenance, signal and image processing, feedback and supervisory control, optimization, and machine learning.

Develop algorithms much faster with MATLAB than with traditional programming languages by using existing functions, customizing them, or creating your own. The same algorithm can operate across many common IoT scenarios, including streaming or big data.

Build Data-Driven and Physics-Based Digital Twins

With MATLAB, you can define a model using data from your industrial smart machine. You can also use Simulink to create a physics-based model using multi-domain modeling tools. Both data-driven and physics-based models can be tuned with data from the operating asset to act as a digital twin. These digital twins can be used for prediction, what-if simulations, anomaly detection, fault isolation, and more.

Have Questions About Using MATLAB and Simulink for Predictive Maintenance

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