# Seeed Studio XIAOML Kit - tinyML Kit for Vision, Sound and Motion

**Type:** Product page · **SKU:** SSE2025080501 · **Brand:** [Seeed Studio](https://core-electronics.com.au/brands/seeed-studio-australia)
**Page:** https://core-electronics.com.au/seeed-studio-xiaoml-kit-tinyml-kit-for-vision-sound-and-motion.html ([markdown](https://core-electronics.com.au/seeed-studio-xiaoml-kit-tinyml-kit-for-vision-sound-and-motion.html.md))

Train and run machine learning models on vision, sound and motion data - a complete tinyML lab that fits in your hand.

## Pricing

- **Price:** $64.26 (inc GST) — $58.42 AUD, exc GST

## Availability & dispatch

- Available with a lead time — expect dispatch between Oct 05 and Oct 06.

## Description

Everything you need to learn embedded machine learning, from capturing your own data to deploying trained models on a thumbnail-sized microcontroller.

This kit is built to accompany Professor Vijay Janapa Reddi's [Machine Learning Systems](https://mlsysbook.ai/) textbook from Harvard University, with hands-on tinyML® lab sessions developed with Marcelo Rovai (UNIFEI). Each lab builds a practical skill with documentation and example code, so learners pair the theory with real results on real hardware.

At its heart is the Seeed Studio XIAO ESP32-S3 Sense, with an onboard OV3660 camera, digital microphone, Wi-Fi and Bluetooth LE. An IMU expansion board clips on to add a 6-axis LSM6DS3TR-C motion sensor and a 0.42" OLED display, and a 32 GB SanDisk microSD card kit handles dataset logging - covering vision, audio and motion projects with one compact setup.

Program it from the Arduino IDE, train and deploy models without code using SenseCraft AI, or build your own pipelines with TensorFlow Lite (LiteRT).

### Features

- Learn with a structured, university-aligned path - lab sessions follow the Machine Learning Systems curriculum from Harvard's tinyML4D group
- Build image classification and object detection projects using the onboard OV3660 camera
- Create keyword spotting and voice command projects with the built-in digital microphone
- Recognise gestures and analyse movement with the precise 6-axis IMU
- See inference results on-device, no PC required, thanks to the 0.42" OLED display
- Collect large training datasets in the field by logging straight to microSD
- Program and power over a single USB-C cable, or go portable with a 3.7 V LiPo on the JST connector
- Official Seeed Studio hardware, designed to work together out of the box

### Specifications

| Property | Specification |
|---|---|
| Microcontroller board | Seeed Studio XIAO ESP32-S3 Sense |
| Camera | OV3660 |
| Microphone | Digital microphone |
| Wireless | Wi-Fi, Bluetooth LE |
| Display | 0.42" OLED (SSD1315 driver) |
| IMU | LSM6DS3TR-C, 6DoF |
| Storage | microSD card slot (32 GB card included) |
| Button | Reset |
| Battery connector | JST 1.0 mm, 2-pin |
| Power supply | USB-C or 3.7 V battery |
| Dimensions | 21 × 17.8 × 30 mm |
| Weight | 10.6 g |

### Resources

- [Overview and Getting Started](https://mlsysbook.ai/kits/contents/seeed/xiao_esp32s3/xiao_esp32s3.html)

### What's Included

- 1x Seeed Studio XIAO ESP32-S3 Sense (pre-soldered, with OV3660 camera, digital microphone and microSD card slot)
- 1x IMU expansion board for XIAO ESP32-S3 (6-axis IMU and 0.42" OLED)
- 1x 2.4 GHz FPC antenna
- 2x heatsinks
- 1x SanDisk 32 GB microSD card
- 1x USB-C to USB-A adapter
- 1x 20 cm USB-A to USB-C cable

## Images

- [Product image 1](https://core-electronics.com.au/media/catalog/product/S/S/SSE2025080501_ecommerce_1790304785220.jpg)