Getting started
To enable wider adoption of ML Technology, STMicroelectronics have released a demonstration version of the NanoEdge AI Studio which is available completely free for three months for developers to experiment with. The PC-based push-button development studio is compatible with Windows or Linux Ubuntu operating systems and supports several STM32 Nucleo boards and Discovery Kits such as the STEVAL-STWINKT1B SensorTile wireless industrial node development kit, this kit also supports the datalogging feature embedded in the NanoEdge AI Studio. The software can be downloaded for free by registering on the STMicroelectronics website, click or scan the QR code to register and download now.
Fig.1 – Adding more value
the type of fault detected reducing diagnosis and repair time. And finally, the Regression (E) algorithm can be used to extrapolate data and predict future data patterns. In this instance the developer imports reference signals and target values in the desktop Studio tool and in a few steps can generate a smart library to, for example, improve energy management or to forecast the remaining lifetime of equipment.
These ML libraries are powerful tools in their own right and can also be combined and chained: anomaly or outlier detection to detect a problem on the equipment, classification to identify the source of the problem, and regression to extrapolate information and provide real insight to the maintenance team. Typically designs will start with one library and then move onto using more libraries adding more value and capability on subsequent versions, see figure 1. All this learning and inference are done directly inside the microcontroller by means of the NanoEdge AI self-learning library, which streamlines the AI process and significantly
reduces development effort, cost and time to market. For a typical use case example in industrial equipment, ML can provide the key to avoiding breakdowns by helping to predict when and where a failure might occur. It allows preventative maintenance and service schedules to be optimised so they can be conducted when convenient and targeted correctly at the equipment or subsystem which is most in need.
Making sense of sensors
Of course, to implement ML in an application, the equipment will need appropriate sensors to detect the required environmental conditions. These input sensor signals can range from vibration to pressure, sound, magnetic and time of flight just to name a few. By utilising STMicroelectronics’ wide range of MEMS and sensor technologies, which includes smart sensors with integrated ML, developers can cover a full spectrum of applications from low-power devices for IoT and battery-operated applications to high-end devices for accurate navigation and positioning, Industry 4.0, augmented virtual reality components and consumer devices. The NanoEdge AI Studio provides developers with maximum flexibility by allowing multiple sensor inputs to be combined, either in a single library, or using multiple libraries concurrently.
Once initial investigation using the demonstration version of NanoEdge AI Studio has been completed users then have the option to purchase an annual Single user development license or Team development license which works with all STM32 microcontrollers. To help build prototypes or proofs of concept faster, with limited risk and investment and maximum chance of success, developers are also able to purchase an Edge AI Sprint Package, this is a bundle that includes training sessions, a NanoEdge AI Studio license, and technical support. The libraries generated with NanoEdge AI Studio production licenses can run on any STM32 microcontrollers during development and are subject to licensed conditions for production.
Design support
Anglia offers support for customer designs with free evaluation kits, demonstration boards and samples of STMicroelectronics products via the EZYsample service which is available to all registered Anglia Live account customers.
Anglia’s engineering team are also on hand to support designers with their extensive experience of ML and AI commonly being used in Condition based Monitoring (CbM) and Predictive Maintenance (PdM) based designs and can offer advice and support at component, software and system level. This expertise is available to assist customers with all aspects of their product design, providing hands on support and access to additional comprehensive STMicroelectronics resources including tutorial videos, technical application notes and reference designs.
Visit
www.anglia-live.com to see the full range of STMicroelectronics products available from Anglia.
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Components in Electronics
May 2022 9
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