Development Board

unPhone 9

by University of Sheffield

Xtensa LX7 with 8512 KB SRAM and vector SIMD instructions provides good ML inference performance

Board Specifications

Clock Speed	240 MHz
SRAM	8512 KB
Flash	7.9375 MB
Connectivity	bluetooth, wifi
Supported Frameworks	arduino, espidf
MCU Family	ESP32-S3 (Espressif)
Platform	espressif32

Data synced from PlatformIO registry on 2026-04-01 View source on GitHub ↗

Hardware Guides for ESP32-S3

ESP32-S3 Anomaly Detection with Edge Impulse

Excellent

ESP32-S3 Anomaly Detection with TFLite Micro

Excellent

ESP32-S3 Fall Detection with Edge Impulse

Excellent

ESP32-S3 Fall Detection with TFLite Micro

Excellent

ESP32-S3 Gesture Recognition with Edge Impulse

Excellent

ESP32-S3 Gesture Recognition with TFLite Micro

Excellent

Explore More

All ESP32-S3 guides All resources MCU Compatibility Checker

Orchestrate unPhone 9 Edge AI with ForestHub

The unPhone 9 runs inference on-device. ForestHub on your Linux edge gateway ingests its results over MQTT, orchestrates the sense-reason-act loop as a deterministic, auditable graph, and acts on the line.

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