The Infineon Technologies KITPSE84AITOBO1 evaluation kit, available from Mouser, enables rapid prototyping, development, and evaluation of Infineon's machine learning platform, DEEPCRAFT™ Studio, as well as the deployment of embedded systems, machine learning models, and other software products, leveraging the versatile PSOC Edge E84 microcontroller (MCU).
The PSOC MCU is designed for responsive computing and control tasks, with hardware-accelerated machine learning that delivers refined end-user interaction and application awareness, making it suitable for always-on applications in the IoT and industrial sectors. The PSOC Edge E84 microcontroller features 512 Mbit of QSPI flash memory, 128 Mbit of octal RAM, and a SIP-based wireless interface powered by a combination of Infineon Technologies' AIROC™ CYW55513 Wi-Fi® and Bluetooth®. The Infineon Technologies AIROC CYW55513 is a low-power, tri-band, 1x1 single-stream Wi-Fi 6/6E compatible device that is IEEE 802.11ax compliant and Bluetooth 5.4 compatible.
The PSOC™ Edge E84 AI evaluation kit also includes an integrated programmer/debugger (KitProg3), an SWD debug head, a MIPI-DSI connector, a speaker interface, USB host and device interfaces, I/O expansion heads, an IMU sensor, a magnetometer, a barometric pressure sensor, two analog microphones (PDM interface), an image sensor, and an BGT60LTR11x XENSIV™ . The BGT60LTR11x is a fully integrated, size-optimized microwave motion sensor that includes antennas in package (AIP) and built-in motion and direction detectors.
The KITPSE84AITOBO1 evaluation kit was featured in a recent episode of Mouser's "Engineering Bench Talk" where it was shown how it helps accelerate time to market by enabling machine learning (ML) and AI-driven application designs with a robust ecosystem, including the ModusToolbox™ operating system, Zephyr®, and full use of Infineon's DEEPCRAFT AI suite.
In addition to accelerating the development of edge AI applications, the PSOC™ Edge E84 AI evaluation kit provides a complete hardware and software ecosystem to reduce time to market for new devices. The platform integrates the PSOC™ Edge E84 microcontroller, based on Arm Cortex-M55 and Cortex-M33 cores, and incorporates hardware acceleration for machine learning algorithms, enabling the execution of AI models with low power consumption—an essential feature for battery-powered IoT devices. Key
hardware features include 16 MB of Flash memory, 16 MB of PSRAM, 1 Gbit QSPI NOR memory, Wi-Fi 6/6E and Bluetooth 5.4 wireless connectivity via the AIROC™ CYW55513 chip, and a comprehensive suite of sensors including a 60 GHz XENSIV™ radar, analog and digital microphones, a barometric sensor, an IMU, a magnetometer, and a DVP camera included with the kit. This combination allows the development of presence detection, gesture recognition, embedded vision, and environmental monitoring applications without the need for additional hardware.
The kit is also compatible with the ModusToolbox™ and Zephyr OS development environments, as well as the DEEPCRAFT™ Studio platform, which facilitates the training, optimization, and deployment of machine learning models directly on the microcontroller. This allows developers to create AI solutions for smart homes, robotics, industrial automation, wearable devices, and human-machine interfaces (HMIs), leveraging an open and extensively documented platform.
According to Mouser and Infineon, the goal of the KITPSE84AITOBO1 is to provide a reference platform that allows for the rapid validation of new Machine Learning and Edge AI designs, reducing development time and facilitating the transition from prototype to commercial product.
