Efficient farm management relies on timely and accurate information, yet many agricultural monitoring activities remain labour-intensive, fragmented, or difficult to scale across large farming operations.
Charles Sturt University’s (CSU) Global Digital Farm (GDF) faces challenges in detecting early-stage weed infestations, monitoring seasonal crop and pasture performance, and tracking livestock health and welfare during critical periods such as lambing and calving.
While monitoring technologies exist, they often fail to deliver the frequency, resolution, and integrated decision support required for practical farm management.
As a result, many monitoring workflows remain disconnected from on-farm decision-making, limiting the ability to translate data into timely action.
This project will establish a unified UAV-based intelligence platform across CSU's GDF network, providing a validated and scalable approach to monitoring crops, pastures, and livestock.
The platform will integrate fixed-wing VTOL drone technology with artificial intelligence, thermal sensing, and ground-truth validation to deliver actionable farm intelligence through dashboards, APIs, and farm management workflows.
This is a newly launched project. Updates will appear here in due course.
