Nordic Semiconductor and Seeed Studio Launch Ultra-Compact IoT Development Board…Integrated Wireless and Power Management Based on nRF54LM20A
Published2026.10.01 10:44
Ultra-Compact 21×17.8mm Form Factor with Bluetooth LE and Matter Support
Nordic Semiconductor and Seeed Studio have unveiled two ultra-compact wireless development boards for battery-based IoT application development.
Seeed Studio announced the launch of XIAO nRF54LM20A and XIAO nRF54LM20A Sense on the 1st.
The new products are characterized by incorporating Nordic's wireless system-on-chip (SoC) nRF54LM20A and power management IC (PMIC) nPM1300. They are designed as a development platform for battery-based devices such as wearables, smart home, industrial IoT, and smart sensing.
In particular, the XIAO nRF54LM20A Sense model features an embedded 6-axis IMU and digital microphone to support development of voice, audio, motion, and gesture recognition applications.
Enhanced Wireless Connectivity and Power Efficiency
The nRF54LM20A integrates a 128MHz Arm Cortex-M33 processor, 512KB RAM, and 2MB non-volatile memory.
It also supports Bluetooth LE, Bluetooth Mesh, Bluetooth Channel Sounding, Thread, Zigbee, Matter, and proprietary 2.4GHz wireless protocol with speeds up to 4Mbps.
The integrated nPM1300 PMIC consolidates battery charging, voltage regulation, power management, and fuel gauging functions to support the design of IoT devices requiring extended battery operation.
Security and Development Environment Support
The development board provides 28 GPIO pins, USB Type-C, 8MB external flash, NFC, and external antenna interface.
It also supports various security features including secure boot, secure firmware update, secure storage, Arm TrustZone-based execution environment, and tamper detection.
The software development environment supports nRF Connect SDK, Zephyr RTOS, and PlatformIO, enhancing embedded development convenience.
Seeed Studio announced plans to additionally launch the XIAO nRF54LM20B model in the future to address demand for next-generation low-power edge AI applications.
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