Specifications
Product
EWatch
Type
Programmable open ESP32-S3 smartwatch
Author
Ewan Wills
MCU
ESP32-S3 with Wi-Fi and Bluetooth Low Energy
Display
1.69-inch colour touchscreen
Battery
350 mAh
Feedback
Vibration motor
Connectivity
USB-C
Main PCB
34 x 28 mm, two-layer ENIG-finished design
Peripheral I/O
I2C and UART
Strap
Standard 20 mm replaceable strap on the complete watch
Toolchains
Arduino IDE, PlatformIO, ESP-IDF
Languages
C, C++, Python, Rust
Drivers
Open-source drivers for display, touch, IMU, Bluetooth LE, charging and sleep modes
Variants
Bare PCB, self-assembly kit, or complete assembled watch
Development History
More than five years of development
Overview
EWatch is a programmable smartwatch design by Ewan Wills built around the ESP32-S3, with a 1.69-inch colour touchscreen, a 350mAh battery, vibration feedback and USB-C connectivity. It is offered at three levels of finish - bare PCB, self-assembly kit, or a complete assembled watch - which makes it usable both as a wearable and as a straight dev board.
The main PCB measures 34 x 28 mm and uses a two-layer ENIG finish, exposing I2C and UART for peripherals. Because it is an ESP32-S3 design, firmware can be built with Arduino IDE, PlatformIO or ESP-IDF, and the project lists C, C++, Python and Rust support. Open-source drivers cover the display, touch interface, IMU, Bluetooth LE, charging system and sleep modes, so developers can work at the API level or drop to registers where they need more control.
The finished watch adds the 350mAh cell, vibration motor, enclosure and a standard 20mm replaceable strap. Wills also positions the hardware as a testbed for AI-assisted firmware development, demonstrating in the project video how an LLM with the drivers and project context can generate additional watch functionality - a use case that follows directly from keeping the driver layer fully open.
Key Benefits
ESP32-S3 with Wi-Fi and BLE, fully open drivers for display, touch, IMU and charging, three build levels from bare PCB to finished watch, and standard toolchains (Arduino, PlatformIO, ESP-IDF).
Applications
Wearable prototyping, HMI research, open-hardware education, sensor-fusion experiments, and an AI-assisted firmware development testbed.
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