XIAO ESP32S3 Sense Board – Wi-Fi, BLE, Camera & ML Ready

Seeed Studio XIAO ESP32S3 Sense – Wi-Fi, BLE & AI Camera Board

If you want a small but powerful development board, pick the Seeed Studio XIAO ESP32S3 Sense. It is ideal for IoT and embedded machine-learning projects.

This seeed studio ESP32 board has a powerful Xtensa processor ESP32-S3R8 SoC that provides dependable 2.4GHz Wi-Fi and Bluetooth BLE 5.0. 

It has an OV3660 smart camera sensor board for crisp 1600*1200 quality photos and a built-in digital microphone for voice detection and audio recognition.

You'll love the 8MB PSRAM and 8MB FLASH, plus an SD card slot for up to 32GB of extra storage. It supports battery charging, making it great for portable projects, and it’s versatile with its wide range of interfaces.

The XIAO ESP32S3 Sense also offers pre-trained AI models and no-code deployment through SenseCraft AI. Despite its powerful features, it maintains the classic thumb-sized form factor of the XIAO family. This board is a fantastic choice for your next project!

Features:

• Features a powerful ESP32S3 32-bit dual-core processor.
  
• It supports Arduino and MicroPython.
  
• Includes a detachable OV3660 camera for 1600*1200 resolution.
  
• Includes an integrated digital microphone.
  
• Measuring just 21 x 17.5mm.
  
• Has 8MB PSRAM, 8MB FLASH, and an SD card slot for up to 32GB of memory.
  
• Supports 2.4GHz Wi-Fi and BLE with a 100m+ range using a U.FL antenna.
  
• Provides pre-trained AI models from SenseCraft AI for no-code deployment.

Camera & ML Demo: Sample Projects

• DIY Face Detection Camera: Use the XIAO ESP32S3 Sense built-in camera and on-board ML support to detect faces, capture snapshots, and send alerts over WiFi.
• Smart Door Entry Monitor: Combine the camera with a PIR sensor to capture entry events, log timestamps, and stream snapshots to a dashboard.
• Voice and Camera Surveillance: Use the digital microphone and camera together to detect sound and motion, then record short clips or trigger notifications.
• Object Classification Station: Run small image classification models on the S3 Sense to identify objects on a workbench or conveyor belt and log results to local storage or the cloud.
• Portable Field Camera Node: Deploy the board with battery power and SD storage to capture and store images in remote locations for later analysis.

Comparison: C3 vs S3 Sense

Related Products & Modules

• XIAO Series Collection
• IoT Sensors Collection

Tutorial : Build a DIY Face Detection Camera

Use the XIAO ESP32S3 Sense, attach power and optional microSD card, flash a sample face detection sketch using Arduino or MicroPython, and configure WiFi to stream or upload detection events to your dashboard. For best results use lightweight models optimized for the S3 Sense and test in varied lighting conditions.

Suggested steps:

• Prepare hardware: XIAO ESP32S3 Sense, power source, optional microSD, and a PIR sensor if needed.
• Install toolchain: Arduino IDE or MicroPython firmware and required libraries for camera and ML inference.
• Load sample code: run a face detection example, adjust model thresholds and frame size for performance.
• Configure output: save snapshots to microSD or push events to a dashboard via MQTT or HTTP.
• Test and tune: iterate on model size, resolution, and detection thresholds for reliable results.

Application:

• Speech recognition
  
• Video monitoring
  
• Wearable devices
  
• Image processing
  
• Smart homes
  
• Low-power (LP) networking
  
• Rapid prototyping
  
• Health monitoring
  
• Education