The ESP32-S3 DataLogger is a purpose-built SoC system we are deploying on our ocean rowing boat during our expedition from Australia to Africa. It was developed in close collaboration with researchers from the University of Western Australia, especially PhD candidate Rick de Kreij and Professor Phil Watson, as well as commercial partners who provided technical guidance and support.

The project began as a shared idea between our team and the UWA researchers. Together, we wanted to build a robust and reliable system that could gather high-quality data throughout the expedition — data that would not only help us understand our own performance and safety in the open ocean, but also contribute to long-term scientific research in oceanography, weather modelling, and endurance under extreme conditions.

Our UNTAMED Data Logger will record:

- Wind speed and direction;
- GPS position and heading;
- Inertial Measurement Unit (IMU) data;

IMU data includes pitch, roll, tilt, and vibration — allowing researchers to study how the vessel moves in response to wind, waves, and rowing effort.

We are also planning optionally to record environmental data like air temperature, humidity, and barometric pressure.

The system will operate continuously throughout the journey, storing data locally on SD card storage in a custom RobinLog format. Logging frequencies are optimized per sensor, ranging from 1 to 10 Hz depending on the data type. The system is modular and built to run on solar power, with low energy consumption and rugged waterproof casing designed for life at sea.

The DataLogger is built on the ESP32-S3 microcontroller platform. Final integration and hardware testing are being completed by HardwareX in Nicosia, Cyprus. Initial proof of concept which was done by Evgeniy Sudyr, who is leading this effort from our side was supported by Paul Price of SmartBee Designs (USA).

This project represents the collaboration between academic research, hands-on engineering, and open data. Our full dataset will be made available to the research team at the University of Western Australia, where it will support studies in Indian Ocean dynamics, surface drift modeling, and understanding how physical effort is impacted by weather and ocean conditions during human-powered travel.

We believe this will be one of the most detailed datasets ever recorded from a rowing expedition in the Indian Ocean. It has the potential to help calibrate ocean models, inform future expedition planning, and offer real-world insights into the connection between endurance performance and environmental variability.