ESP32S3_DEV_Minimal_LowPower

This project implements a minimal low-power development board based on the ESP32-S3.
The design focuses on reducing component count, board complexity, and idle power consumption, while still exposing the full capabilities of the ESP32-S3 for advanced development.

Unlike traditional development boards, this design does not include a USB-to-UART bridge. Instead, it leverages the native USB interface of the ESP32-S3 for programming and communication, resulting in a simpler and more efficient design.

🔑 Features

• ESP32-S3 MCU with external QSPI Flash memory.

• Native USB 2.0 interface used for flashing and serial communication.

• MCP1826S LDO regulator:

  • Low quiescent current (IQ) for low-power operation.

  • Stable supply for ESP32-S3 core.

• 4-layer PCB:

  • Designed and manufactured at NextPCB (PCBA service).

  • Optimized for low EMI/EMC compliance.

• Castellated edges for easy integration into other projects.

• Full pinout exposure:

  • All ESP32-S3 GPIOs available, including those not accessible on standard WROOM modules.

  • Enables advanced use cases and maximum flexibility.

• On-board PCB antenna (MIFA type):

  • Designed with uSimmics EM simulation.

  • Verified radiation characteristics, dispersion parameters, and stack-up effects.

📂 Repository structure

• /schematic/ → Circuit schematic files.

• /pcb/ → PCB layout and Gerber files.

• /doc/ → Antenna simulation results and design notes.

• /firmware/ → Demo applications and example projects.

• /img/ → PCB renders and prototype photos.

🧪 Demo Application

Included with this project is a human presence detection demo based on Wi-Fi spectral footprint analysis:

• Scans available Wi-Fi networks, collecting SSID and RSSI values.

• Applies a probability-based algorithm using normal distribution to estimate environmental changes.

• Detects human presence based on variations in the Wi-Fi spectrum.

• Displays results on a color IPS display.

This demonstrates the potential of the ESP32-S3 in low-cost sensing and AIoT applications without requiring dedicated motion sensors.

🔧 Typical applications

• Low-power IoT node development.

• Integration into custom PCBs via castellated module design.

• Edge-AI and machine learning applications.

• Antenna research and RF prototyping.

📑 References

• ESP32-S3 Technical Reference Manual (Espressif)

• MCP1826S LDO Datasheet (Microchip)

• uSimmics EM Simulation Software

📸 Project preview

(Insert here PCB renders, antenna simulation plots, and prototype photos)

⚖️ License

This project is released under the MIT License.
You are free to use, modify, and distribute it, provided that proper credit is given.