Stavros Vougioukas

This project aims to develop AgML, an open-source Python library to accelerate agricultural AI by providing access to ML datasets, benchmarks, pre-trained models, workflows, and synthetic data generators. It builds on the successes of the Year 3 AIFS proposal, "AgML: Open-Source Infrastructure to Accelerate Scaling of Agricultural AI Technologies."

The project aims to build infrastructure for the rapid scaling of agricultural AI technologies by creating an open-source Python library, AgML, providing access to agricultural-specific machine learning datasets, benchmarks, pre-trained models, workflows, and synthetic data generators, building on successes from the Year 2 AIFS proposal.

The project involves collaboration on open-source infrastructure development, optimized sensor-driven precision agriculture, and inexpensive soil nitrate sensors, with the potential to accelerate agricultural AI technologies through AgML Python library and to develop tools for autonomous vehicles and soil nitrate measurement.