XIAOML Kit: ESP32-S3 with camera, microphone and IMU for studying TinyML
Embarcados introduces the XIAOML Kit from Seeed Studio, made to follow the hands-on labs of the book «Machine Learning Systems» by Professor Vijay Janapa Reddi of Harvard. The labs were developed together with Professor Marcelo Rovai of UNIFEI in Itajubá, within the tinyML4D group.
The kit brings a XIAO ESP32-S3 Sense with an OV3660 camera, a digital microphone and an SD card reader, plus an expansion board with a 6-axis IMU and a 0.42-inch OLED display. That covers the three kinds of data the book works with: images, sound and motion. It also includes a 2.4 GHz FPC antenna, two heat sinks and a 32 GB microSD card with adapter.
The SoC is the ESP32-S3R8, a dual-core Xtensa LX7 at 240 MHz with 512 KB of SRAM, 8 MB of PSRAM and 8 MB of flash. The IMU is the LSM6DS3TR-C, and the OLED uses an SSD1315 controller, which the libraries treat as an SSD1306 with 72 x 40 pixels. The assembled unit measures 21 x 17.8 x 30 mm and weighs 10.6 g. A practical detail the author points out is that the IMU and the OLED share the same I2C bus at addresses 0x6A and 0x3C, so anyone adding another I2C sensor has to avoid those two. The IMU board also has a JST connector for a 3.7 V lithium battery, which is handy for wearable projects.
What I liked most is the mix of a reference book with cheap, compact hardware: you can move from theory to running inference on a real microcontroller. The OLED only fits two or three readable lines, of course, but that is enough to show the inferred class or a confidence percentage.
Source: Embarcados
The kit brings a XIAO ESP32-S3 Sense with an OV3660 camera, a digital microphone and an SD card reader, plus an expansion board with a 6-axis IMU and a 0.42-inch OLED display. That covers the three kinds of data the book works with: images, sound and motion. It also includes a 2.4 GHz FPC antenna, two heat sinks and a 32 GB microSD card with adapter.
The SoC is the ESP32-S3R8, a dual-core Xtensa LX7 at 240 MHz with 512 KB of SRAM, 8 MB of PSRAM and 8 MB of flash. The IMU is the LSM6DS3TR-C, and the OLED uses an SSD1315 controller, which the libraries treat as an SSD1306 with 72 x 40 pixels. The assembled unit measures 21 x 17.8 x 30 mm and weighs 10.6 g. A practical detail the author points out is that the IMU and the OLED share the same I2C bus at addresses 0x6A and 0x3C, so anyone adding another I2C sensor has to avoid those two. The IMU board also has a JST connector for a 3.7 V lithium battery, which is handy for wearable projects.
What I liked most is the mix of a reference book with cheap, compact hardware: you can move from theory to running inference on a real microcontroller. The OLED only fits two or three readable lines, of course, but that is enough to show the inferred class or a confidence percentage.
Source: Embarcados
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