System architecture

Data collection and system supervision

 Ultron is powered by NVIDIA Jetson Linux4Tegra (L4T), a Linux-based embedded operating system developed by NVIDIA for all Jetson platforms and supported by NVIDIA Jetpack SDK, a comprehensive set of libraries for acceleration of GPU computing, multimedia, graphics, and computer vision. Benefits of using Linux as a platform include background logging of critical operations and support for open communication standards such as SSH for secure communications.  

A centralized supervisory software that monitors and controls the entire platform sits on top of the Jetson-based PLC hardware. The software processes collected data from inputs and sends commands to control output processes. Because the device's software is cloud-native, the containerized app can be easily managed and deployed at scale.

GPU-accelerated computing with Ultron

The collected data is useful for AI model training and for developing seamless streaming pipelines to extract meaningful real-time insights. The NVIDIA DeepStream SDK is a comprehensive analytics toolkit for AI-based multi-sensor processing. The toolkit is based on the GStreamer multimedia framework and includes a GPU-accelerated plug-in pipeline for building end-to-end AI-powered applications that analyze video and sensor data from connected inputs.. By leveraging Jetson’s high computing power and the unified SDK, , DeepStream and GStreamer elements can be easily integrated into the automation system and shorten the time required to build and deploy real-time Intelligent Video Analytics (IVA) applications. For example, engineers can build end-to-end DeepStream pipelines to quickly convert raw video input data into insightful annotated video output.

AI Inference at the edge

Aside from increased computation capability, real-time inference at the edge reduces latency significantly. This is vital when connectivity is unavailable, such as with remote devices, or when the latency to send data to and from a data center is too long. Edge AI minimizes data transfer between edge devices and their data centers. There is also more privacy and security by storing the data locally.

Visualize and derive insights from models’ output

A human-machine interface (HMI) is an interface that enables humans to monitor and control a device. An HMI is required in a control system and is usually connected to a single PLC or process to enable operators to change the flow set point and enable alarm conditions in the event of a loss of flow, high temperature, or anomalies, and the condition is displayed and recorded. The following figure shows a customized HMI connected to Ultron that streams the AI model’s output, visualizes important device metrics, and includes interactive elements for I/O controls