The next agricultural revolution will be driven by the use of digital technologies, informatics & cybernetics. Future Farming brings together elements of technology, society, and biology and enables the use of information, extracted from purposefully collected data, to manage agricultural production systems: optimise yield and quality and increase efficiency whilst ensuring sustainability.
Over the next ten years, we expect to see better use of information within each component of the agri-food production system and perhaps the start of a transition to a single integrated agri-food system, in which thinking and decision making is based on information about the state of all key system components. The ultimate result will be a truly optimised and robust food production system from paddock to plate and fibres from the paddock to the user. To achieve this, we must thoroughly understand all processes involved in the reverse order: from the consumer to paddock.
Visit QUT’s Future Farming site for more information.
Funded by Queensland Department of Agriculture and Fisheries
Meet AgBot II, a new generation tool for robotic site-specific crop and weed management.
Plant Biosecurity CRC (2014 - 2018)
This project investigates the sensitivities and capacity of emerging unmanned aerial systems (UASs) and imaging technologies for biosecurity surveillance in viticulture, horticultural and grain industries.
Use of UAS and Hyperspectral Remote Sensing for Early detection of Phylloxera Infestation in Vineyards
The aim of this project is to use predictive models combined with high-resolution detection technologies to increase sampling efficiency and improve first detection rates.
The goal of this project is to research and develop a fully autonomous robotic crop management system for protected cropping systems
This project aims to develop a robotic crop management system for the growth of nutrient-dense crops within Vertical Farming Systems
QUT has developed a prototype robotic capsicum (sweet pepper) harvester nicknamed ‘Harvey’, combining robotic vision and automation expertise to benefit agricultural producers.
This project is investigating smarter ways for robots to see around all the clutter in order to better monitor crops in agricultural environments.
Commonwealth Grant CRCPIX000099 (Cooperative Research Centre Project); Agent Oriented Software (Lead Partner)
The project aims to develop a robot to autonomously find and identify individual noxious weeds, spraying or using an alternative method to eliminate them. It will produce a series of operational prototypes ("Kelpie"), based upon a commercially available agricultural chassis.