The TDK InvenSense QCIoT-ICM42688P Pmod™ Evaluation Board is a MEMS sensor breakout board featuring the ICM-42688-P 6-axis IMU. Developed in partnership with Renesas, this board integrates with the Renesas QuickConnect platform, allowing for rapid prototyping and development of systems using TDK sensors and Renesas RAxx MCUs. QuickConnect provides a cloud-based environment for graphical firmware development. 

The ICM-42688-P combines a 3-axis gyroscope and a 3-axis accelerometer, offering a configurable host interface supporting I3C, I²C, and SPI communication. It includes a 2 kB FIFO buffer and two programmable interrupts with wake-on-motion functionality for power management. The board features user-programmable digital filters for gyroscope, acceleration, and temperature sensors. Typical applications include AR/VR controllers, head-mounted displays, wearables, sports, robotics, and IoT devices.

Features of QCIoT-ICM42688P Pmod^TM Evaluation Board

QCIoT-ICM42688P board facilitates the integration of TDK sensors with Renesas MCUs for Industrial and IoT applications, with pre-integrated MEMS sensor drivers available within the QuickConnect platform. Let’s explore some of its salient features:

High-Precision Motion Tracking

The TDK InvenSense QCIoT-ICM42688P Pmod^TM Evaluation Board integrates the ICM-42688-P, a 6-axis MEMS MotionTracking® device combining a 3-axis gyroscope and a 3-axis accelerometer. The sensor has 2.8 mdps/√Hz gyroscope noise and 70 µg/√Hz accelerometer noise for low-noise performance. It supports user-selectable full-scale ranges, with gyroscope settings from ±15.6 dps to ±2000 dps. The accelerometer offers sensitivity settings between ±2g and ±16g, making it adaptable for different applications.

Advanced Motion Detection and Filtering

The ICM-42688-P MEMS device features user-programmable digital filters for gyroscopes, accelerometers, and temperature sensors. The board includes APEX motion functions like a pedometer, tilt detection, and tap detection. Additional features include wake-on motion, raise to wake/sleep, and significant motion detection. These functions enhance wearables, AR/VR controllers, sports tracking, and robotics. The low-power operation allows event-based activation while reducing energy consumption.

Seamless Integration with Renesas QuickConnect

The QCIoT-ICM42688P board integrates easily with Renesas RA MCU boards via the QuickConnect platform, eliminating the need for manual driver conversion. The QuickConnect cloud-based system enables graphical design, rapid prototyping, and production-ready firmware generation. It supports EK-RAxxx evaluation kits, ensuring smooth integration of MEMS sensors with Renesas microcontrollers. This setup accelerates the development of industrial and IoT applications.

Standardized Connectivity and Low Power Operation

The board offers standard Pmod Type 6A (expanded I²C) and Type 2A (expanded SPI) connections, ensuring easy interfacing with various development platforms. Its low-noise mode consumes just 0.88mA, making it efficient for battery-operated devices. By combining compact design, low power usage, and configurable sensor settings, the QCIoT-ICM42688P board is optimized for motion sensing applications. These features make it ideal for rapid prototyping, industrial automation, and battery-powered devices.

Applications

The TDK InvenSense QCIoT-ICM42688P Pmod^TM Evaluation Board is suited for motion-sensing applications across industrial, IoT, and consumer technologies. In asset tracking, it enhances real-time location monitoring using precise motion detection. Predictive maintenance benefits from its low-noise gyroscope and accelerometer, detecting irregular vibrations in Industrial 5.0 systems. 

Smart home and building automation leverage its motion functions for energy-efficient control. The board supports AR/VR controllers, head-mounted displays, and wearables, improving motion accuracy. In sports and robotics, it enables real-time tracking and movement analysis. For IoT devices, its low-power wake-on-motion feature optimizes battery life in wireless sensor networks.