Infineon — ModusToolbox™ Software & IMAGIMOB Studio

 

Rapid AI/Machine Learning Development for Edge Applications

ModusToolbox™ and IMAGIMOB Studio with Infineon PSoC™ 62 MCUs

Supporting a wide range of Infineon MCU‘s, ModusToolbox™ offers a single, all-in-one place for machine learning (ML) at the edge where developers can collect, create, train, optimize and deploy with speed.

With the recent IMAGIMOB acquisition and integration of IMAGIMOB Studio and ModusToolbox™ software, it is now possible for even the newest edge ML application developers to quickly build production grade ML applications. With a complete ML workflow for embedded devices, IMAGIMOB Studio enables developers to build intelligence for the edge for audio classification, gesture recognition, signal classification, fall detection, material detection, and more.
 

IMAGIMOB Studio

IMAGIMOB Studio is a leading platform for Machine Learning (ML) solutions for edge devices, providing an end-to-end machine learning toolchain that is highly flexible and easy to use with a strong focus on delivering production-grade ML-models for a wide range of use cases building on Infineon’s advanced sensors and comprehensive IoT solutions. Learn more about IMAGIMOB Studio integration into ModusToolbox here.

ModusToolbox™

ModusToolbox™ Machine Learning (ML) enables you to rapidly evaluate and deploy Machine Learning models on Infineon MCUs. ModusToolbox™ ML is designed to work seamlessly with the ModusToolbox™ ecosystem and can be added into existing projects to enable inferencing on low-power edge devices.

ModusToolbox™ Software is a comprehensive suite of development tools and embedded run-time assets that provide a flexible and efficient development environment. ModusToolbox™ Software provides specific tools and capabilities that support a seamless transition from the initial getting started setup, through the edit-compile-debug cycle of prototyping, and finally the retargeting of the embedded application to final hardware. ModusToolbox™ also supports packs for expansion of additional tools, device support, and capabilities.
 

Machine Learning Applications for:

• Predictive maintenance - Recognize machine state, detect machine anomalies and act in milliseconds, on device.
• Audio applications - Classify sound events, spot keywords, and recognize your sound environment.
• Gesture recognition - Detect hand gestures using low-power radars, capacitive touch sensors or accelerometers.
• Signal classification - Recognize repeatable signal patterns from any sensor.
• Fall detection - Fall detection using IMUs or a single accelerometer.
• Material detection - Real time material detection using low-power radars.

 

IMAGIMOB Studio Edge AI Development Platform

Summary of Features Collect and annotate high quality data ML-assisted labeling to automatically label new data Manage, analyze and process your data Build great models without being an ML expert Evaluate, verify and select the best models Package your models and quickly deploy on your target hardware

Benefits Move AI out of the cloud and into your embedded devices where edge AI allows for real time operations, reduced power consumption, reduced costs. Own your own data without data storage in the Infineon cloud Edge ML development for machine learning on Infineon-based microcontrollers brings a number of advantages, including: low latency, low power consumption, low bandwidth, and privacy IMAGIMOB Studio and AI models can be leveraged on Infineon’s advanced PSoC™ and XMC™ microcontrollers. Collect real data from real products for high-quality model creation

 

Featured Hardware: Infineon PSoC™ 62S2 Wi-Fi BT Pioneer Kit (Cy8CKIT-062S2-43012)

Feature-rich hardware evaluation platform

Infineon offers the PSoC™ 62S2 Wi-Fi BT Pioneer Kit (CY8CKIT-062S2-43012), a feature rich hardware evaluation platform that enables development of applications based on the PSoC™ 62 series MCU. The kit also includes a wireless module based on the AIROC™ CYW43012 combo device to develop cloud connected IoT applications including Matter over Wi-Fi applications.

Kit Contents PSoC® 62S2 Wi-Fi BT Pioneer Board USB Type-A to Micro-B cable Quick Start Guide Jumper wires

 

Featured Hardware: Infineon IoT Sense Expansion Kit (CY8CKIT-028-SENSE)

The IoT sense expansion kit is a low-cost Arduino™ UNO compatible shield board that can be used to easily interface a variety of sensors with the PSoC™ 6 MCU platform. The kit targets two main applications:

Kit Contents Audio applications: Two PDM microphones and one analog microphone are included, as well as an audio codec with an audio jack socket connector. Machine Learning (ML) applications: Multiple sensors are included to generate input data to feed ML algorithms, such as a 6-axis motion sensor, a pressure and temperature sensor, and the microphones. This kit guide provides details on the kit contents, hardware, schematics, and BOM