SparkFun QuickLogic Thing Plus – EOS S3 | FPGA-Enabled ARM Cortex-M4F Machine Learning Board
Description
The (SPIDER Automation) SparkFun QuickLogic Thing Plus – EOS S3 is a compact, high-performance system designed to fuel the next generation of ultra-low-power machine learning (ML) and Internet of Things (IoT) devices. Built around QuickLogic’s EOS S3—the world’s first FPGA-enabled ARM Cortex-M4F MCU—this board breaks away from proprietary hardware limitations by offering 100% open-source hardware (Feather-compatible) and robust open-source software toolchain support.
Between its integrated LiPo battery management circuitry, wake-on-sound PDM microphone, low-power 3-axis accelerometer, and Qwiic connector, this board is perfectly tailored for voice-controlled wearables, gesture-sensing gadgets, and edge-AI monitoring. Sensor data can easily be routed straight into the embedded FPGA, allowing developers to train and run custom machine learning models using TensorFlow Lite, SensiML, and SymbiFlow tools.
Key Features
- EOS S3 SoC Architecture: Powered by an ARM Cortex-M4F core with an 80 MHz max clock frequency, 512 KB SRAM, and embedded FPGA (eFPGA) logic.
- 100% Open-Source Ecosystem: Fully supported by open software tools including FreeRTOS, Zephyr RTOS, Minden, Docker, and SymbiFlow.
- Feather Footprint Compatibility: Standardized pinout matching Adafruit Feather boards for seamless shield and accessory integration.
- Onboard Wake-on-Sound Microphone: Features a built-in PDM microphone ideal for voice activation and audio-based AI prototyping.
- Low-Power 3-Axis Accelerometer: Detects motion, gestures, and orientation changes with minimal power consumption.
- Plug-and-Play Qwiic Connector: Integrated I2C Qwiic port allows rapid connection to over 150+ sensors, displays, and relays without soldering.
Benefits
- Ultra-Low Power Edge ML: Process neural networks and machine learning algorithms locally on the device without needing cloud connectivity.
- Rechargeable Battery Support: Built-in Microchip MCP73831/2 charging circuitry and standard JST connector for single-cell LiPo batteries.
- Developer Friendly: Eliminates vendor lock-in with transparent, community-driven open-source hardware designs and firmware stacks.
- Flexible Debugging & Programming: Features a dedicated SWD programming connector for use with USB-TTL converters.
- Compact & Lightweight: Measuring only 70 x 24 mm and weighing just 8 grams, it fits effortlessly into wearable prototypes and small enclosures.
Applications
- Voice-Activated Smart Devices: Wake-on-sound applications, smart home voice triggers, and localized audio command processing.
- Wearable Fitness & Gesture Trackers: Motion-activated wearables using the onboard 3-axis accelerometer.
- Edge Machine Learning & AI Nodes: Training and deploying TensorFlow Lite or SensiML models for anomaly detection and pattern recognition.
- IoT Prototyping & Sensor Hubs: Connecting environmental, optical, and motion sensors via the Qwiic ecosystem.
- Educational & Research Platforms: Teaching embedded systems, FPGA programming, and real-time operating systems (RTOS).
Package Includes
- 1 x SparkFun QuickLogic Thing Plus – EOS S3 Development Board
Technical Specifications
| Parameter | Specification |
|---|---|
| Item Type | AI & Machine Learning Development Board |
| Brand | SPIDER Automation |
| Manufacturer / Model | SparkFun QuickLogic Thing Plus – EOS S3 |
| Microcontroller | ARM® Cortex®-M4F with Embedded FPGA (eFPGA) |
| Max Clock Frequency | 80 MHz |
| SRAM Capacity | 512 KB |
| Operating / Input Voltage | 3.3 V |
| USB Interface | USB Type-C (Data signals tied to eFPGA programmable logic) |
| Battery Support | Single-Cell LiPo (JST Connector with MCP73831/2 Charger) |
| Onboard Sensors | Wake-on-Sound PDM Microphone & 3-Axis Accelerometer |
| Expansion Interface | I2C Qwiic Connector & UART via I/O Headers |
| Software & OS Support | Zephyr RTOS, FreeRTOS, TensorFlow Lite, SensiML, SymbiFlow |
| Board Dimensions (L × W × H) | 70 mm × 24 mm × 7 mm |
| Net Product Weight | 8 g |
| Gross Shipping Weight | 0.01 kg |
| Package Shipping Dimensions | 9.5 cm × 6 cm × 1 cm |