SparkFun
SparkFun Thing Plus-Artemis Machine Learning Development Board
Unlock the power of machine learning with the SparkFun Thing Plus-Artemis development board. This compact board is built around the Artemis module, a groundbreaking open-source, US-manufactured BLE solution. It boasts 1MB of Flash and 384KB of RAM, capable of running complex machine learning models and sketches at up to 96MHz. With 21 interrupt-capable GPIO pins, 8 analog inputs, and multiple serial interfaces, it offers extensive connectivity. The integrated LiPo charger and USB-C port simplify power management, while exposed JTAG pins cater to advanced debugging needs. It's designed for compatibility with the Feather Footprint and Arduino IDE.
$25.95
Owner Satisfaction
4.4
/ 5
Category Rank
931
/ 1543
#931 in Development Boards
Price vs Category Average
-70%
Below average
Processor Clock Speed
4896
/ MHz ( MHz Turbo)
Who it's for
- Integrated ML Sensor Suite
- Ultra-Low Power Consumption
- Thing Plus (Feather) Compatibility
Who should skip it
- Steep ML Learning Curve
- Limited RAM for Complex Models
- Bluetooth 5.0 Setup Overhead
Key Specs
Processor Clock Speed
48 MHz (96 MHz Turbo)
Onboard Flash Memory
1 MB
SRAM
384 KB
GPIO Pins
21 total, all interrupt capable
Analog Inputs
8 channels (14-bit precision)
Serial Interfaces
2 I2C buses, 1 SPI bus
Connectivity
Bluetooth 4.0 (BLE supported)
Power Connector
USB-C
Features
- Run TensorFlow machine learning models.
- World's first open-source BLE module.
- Ample memory for complex projects.
- Built-in Bluetooth low energy radio.
- 21 interrupt-capable GPIO pins.
- Exposed JTAG for professional debugging.
- Feather Footprint compatible.
- Onboard LiPo charger for easy power.
What customers say
Developers highly value this board for its exceptional power efficiency, enabling sophisticated machine learning models to run effectively on battery power for IoT applications. Its compatibility with the standard Thing Plus form factor streamlines project integration. While the platform is powerful and compact for low-power AI, users note a steep learning curve. Novice developers often find the initial setup, toolchain configuration, and model deployment complex. The board is indispensable for serious developers comfortable navigating specialized SDKs and technical specifications, though it is not recommended for absolute beginners entering embedded machine learning.
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