The new version of NanoEdge AI Studio comes as the shift of AI capabilities from the cloud to the edge offers manufacturers phenomenal potential to fundamentally improve processes, and deliver innovative functions in equipment that can sense, process data, and act locally to improve latency and information security. Applications include connected devices, household appliances, and industrial automation.
NanoEdge AI Studio simplifies the creation of machine learning, anomaly learning, detection and classification on any STM32 microcontroller. This new release also includes prediction capabilities such as regression and outliers libraries. The tool makes it easier for users to integrate such cutting-edge machine-learning capabilities quickly, easily, and cost-effectively into their equipment. No data-science expertise is needed.
Adding native support for all STM32 development boards, ST has also eliminated the need to write code for its industrial-grade sensors with new high-speed data acquisition and management capabilities. NanoEdge AI Studio software enhances security by using local data storage and processing, instead of transferring to, and processing data in, the cloud.
“We had the opportunity to use NanoEdge AI Studio with one of our major aerospace customers. For machine drilling during the manufacture of expensive parts, where a worn drill-bit or the slightest anomaly can have significant consequences, Alten used NanoEdge AI Studio to integrate Machine-Learning algorithms into the drilling equipment. The solution tested on a production line was so effective that Alten has launched a practice around this technology to support its customers and to industrialize these first results to deploy a disruptive solution of drilling tools prescriptive maintenance in their factories,” states Steve Peguet, Scientific Director, Innovation Department of Alten Group, an international technology consulting and engineering company.
“To protect our loved ones so that they can have a healthy and fulfilling life, NanoEdge AI is empowering us to reduce the Machine-Learning development time for our next-generation personal-safety devices. AI running at the edge on our devices will allow us to make informed decisions promptly with higher accuracy and reduced false-positives,” says Deepak Arora, President & CEO of Wearable Technologies.
Key features of the new NanoEdge AI Studio V3 software includes a completely redesigned user interface to make it even easier for non-experts to develop state-of-the-art machine-learning libraries, including new high-speed data acquisition and management support on the STWIN development board, making all industrial-grade sensors easily manageable without having to write a single line of code.
NanoEdge AI Studio V3 also offers many new learning features focusing on visual inspection, production control and predictive maintenance, with improved native support of all STM32 development boards, no configuration required.
Before the advent of NanoEdge AI Studio, engineers had to contact software vendors, go over their hardware configuration, and the behavior to monitor. Today, the tool enables developers to customize, generate, and validate their machine learning library. The utility first asks users to select their Cortex-M architecture and the sensor in the system. They then import a file with values describing the equipment’s typical behavior. It can be data from an accelerometer on a fan or the electrical information of an equipment. Then, NanoEdge AI Studio automatically tests, optimizes, and sorts the best algorithmic combination among hundreds of millions of possible combinations and produces a customized library that developers can validate using the embedded emulator.
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