Arduino Nicla Sense ME - image 1
Arduino·module

Arduino Nicla Sense ME

Compact 22.86mm sensor module with nRF52840 BLE 5.0 and four Bosch sensors — 9-axis IMU with AI, barometric pressure, temperature/humidity, and gas/CO2 detection. Edge AI-powered environmental and motion sensing in a coin-sized package.

Starting from

$50.00

Compatible Firmware

Specifications

ArchitectureARM Cortex-M4F
CPU Cores1
Clock Speed64MHz
Flash1MB
GPIO Level3.3V
BluetoothBLE 5.0
StorageNo
Dimensions22.86 × 22.86mm
Weight2g

Components

Nordic nRF52840 at 64MHz handling BLE communication and application logic.

Bosch BHI260AP self-learning AI smart sensor with 6-axis IMU and programmable neural network accelerator.

Bosch BME688 measuring temperature, humidity, barometric pressure, and gas resistance for air quality and CO2 estimation.

Bosch BMP390 barometric pressure sensor with ±0.3hPa accuracy for altitude tracking.

Bus Interfaces

SPI
notes: Via castellated pads
I2C
notes: Via castellated pads

GPIO Map

GPIO0
Digital I/O
digital-inputdigital-output
GPIO1
Digital I/O
digital-inputdigital-output
GPIO2
Digital I/O
digital-inputdigital-output

Overview

The Arduino Nicla Sense ME is a tiny (22.86×22.86mm) multi-sensor module designed for environmental and motion intelligence at the edge. It integrates four Bosch Sensortec sensors: the BHI260AP smart IMU with built-in AI for motion classification, BMM150 magnetometer, BMP390 barometric pressure sensor, and BME688 4-in-1 gas sensor measuring temperature, humidity, air quality, and CO2 levels.

Powered by the nRF52840 ARM Cortex-M4F with BLE 5.0 connectivity, the Nicla Sense ME runs sensor fusion algorithms directly on the Bosch BHI260AP's neural network accelerator, offloading motion classification from the main MCU. This architecture enables always-on activity recognition, compass heading, altitude tracking, and air quality monitoring at minimal power consumption.

Compatible with the Nicla, Portenta, and MKR ecosystems, it operates standalone on battery power or plugs into carrier boards. Ideal for wearable health monitors, environmental tracking, indoor air quality stations, and predictive maintenance sensors.

Use Cases

3

Resources

Where to Buy

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