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

XIAO ESP32S3 Sense Use Cases for Developers

The XIAO ESP32S3 Sense is purpose-built for developers building real applications at the edge — not just blinking LEDs. Here's how makers and engineers are using it for serious projects.

XIAO ESP32S3 Sense for TinyML

The ESP32-S3 dual-core processor running at 240 MHz with 8MB PSRAM makes the XIAO ESP32S3 Sense one of the most capable TinyML boards available at this price point. It supports deployment of quantized neural network models directly on-device no cloud required.

Developers use it for:

• On-device image classification using lightweight CNN models (MobileNetV2, EfficientNet-Lite)
• Keyword spotting and wake-word detection using the built-in PDM digital microphone
• Anomaly detection on sensor streams with no-latency inference loops
• No-code model deployment via SenseCraft AI lo; ad pre-trained models without writing inference code

The board's PSRAM headroom lets you load larger models than typical ESP32 variants, making it the go-to choice when you need inference speed without upgrading to a full Raspberry Pi or Jetson.

XIAO ESP32S3 Sense Face Detection Project

The detachable OV3660 camera (1600×1200 resolution) combined with the ESP32-S3's hardware acceleration makes the XIAO ESP32S3 Sense a natural fit for face detection projects. Unlike raw ESP32-CAM modules, this board gives you PSRAM, BLE 5.0, and a microphone all on one thumb-sized footprint.

Common face detection project configurations:

• Smart Door Monitor: Detect faces at a doorway, capture a snapshot, and push an alert over Wi-Fi to a Telegram bot or MQTT broker
• Attendance Logger: Run lightweight face detection on-device, log timestamps to a microSD card (supports up to 32GB), and sync records over Wi-Fi
• Occupancy Detector: Count detected faces in a frame to estimate room occupancy, useful for labs, libraries, and co-working spaces
• Webcam Streaming with Detection Overlay: Stream live camera feed over Wi-Fi with detection bounding boxes using the built-in WebServer library

The board supports both Arduino IDE and MicroPython for face detection workflows. For fastest time-to-demo, use the SenseCraft AI platform to flash a pretrained face detection model with zero configuration.

XIAO ESP32S3 Sense Audio Recognition

The integrated PDM digital microphone makes the XIAO ESP32S3 Sense one of the few thumb-sized boards that can handle on-device audio recognition without an external mic module. This unlocks a whole class of voice and sound-based applications.

Audio recognition use cases developers build with this board:

• Wake-word detection: Train a keyword spotting model (e.g., "Hey Device") using Edge Impulse and flash directly to the S3 Sense runs entirely offline
• Sound classification: Detect specific audio events glass breaking, alarms, coughs, machinery faults and trigger actions or alerts via BLE or Wi-Fi
• Voice command interface: Build a small set of voice commands (4–8 words) to control connected peripherals using MFE spectrograms and a neural classifier
• Audio logging: Record audio clips to microSD on trigger events (sound above a threshold, camera motion detection) for later analysis

The I2S interface also supports external microphones if you need higher sensitivity or directional audio pickup.

Why Developers Choose the XIAO ESP32S3 Sense for Edge AI Projects

• All-in-one sensing: Camera + mic + Wi-Fi + BLE on a 21×17.5mm board no shield stack required
• Battery-native: Built-in LiPo charging means your project is portable from day one
• Flexible toolchains: Arduino, MicroPython, ESP-IDF, and SenseCraft AI are all supported
• Maker-tested in India: Used in college capstone projects, ATL labs, IoT workshops, and hackathons across India

Need help choosing between the XIAO ESP32S3 Sense and other edge AI boards? Browse our AI Hardware collection or explore our full XIAO Series lineup including camera add-ons and expansion boards.

XIAO ESP32S3 Sense vs Standard – Which XIAO Should You Buy?

The XIAO ESP32-S3 family has three variants that look nearly identical but serve very different projects. If you're not sure which one to order, this table settles it.

Choose the XIAO ESP32S3 Sense if you need:

• A camera for face detection, object classification, or image capture
• A microphone for wake-word detection, sound classification, or audio logging
• On-device TinyML inference via SenseCraft AI or Edge Impulse
• Local storage via microSD for offline data logging

Choose the XIAO ESP32-S3 Standard if you need:

• A smaller price point for a pure IoT or BLE project
• Ultra-low deep-sleep current (14μA) for battery-critical applications
• A clean base board to pair with your own sensors and modules
• Wearable or compact embedded work where camera bulk isn't wanted

Not sure yet? The Sense's camera and mic are detachable — you get full flexibility. Most developers building anything with vision or voice should default to the Sense. View the XIAO ESP32-S3 Standard board →