Improving water quality modelling by better understanding solute transport. Poor stream water quality is a critical problem in Australia and globally. Stream water quality depends directly on pathways and time taken for water to transport pollutants through catchments. Predicting these pathways is highly challenging and currently requires specialised data. This project aims to better model the movement of water from rainfall to streams, enable greatly improved use of water quality data routinely ....Improving water quality modelling by better understanding solute transport. Poor stream water quality is a critical problem in Australia and globally. Stream water quality depends directly on pathways and time taken for water to transport pollutants through catchments. Predicting these pathways is highly challenging and currently requires specialised data. This project aims to better model the movement of water from rainfall to streams, enable greatly improved use of water quality data routinely collected in Australia's catchments and thereby better predict water quality behaviour. Proposed field studies aim to support this development. The outcomes sought are improved planning and management of water quality in our rivers, lakes and estuaries, improved health of these water bodies and improved water supplies.Read moreRead less
Airborne ultrafine particles in Australian cities. There is an acute deficiency of knowledge in Australia on urban airborne ultrafine particles, originating from transport and other anthropogenic sources, which pose significant health and environmental risks. The aim of this project is to address this deficiency by an extensive multi-city, cross-disciplinary study using state of the art instrumentation and data analytic techniques. The outcome will be an in depth, quantitative insight into the c ....Airborne ultrafine particles in Australian cities. There is an acute deficiency of knowledge in Australia on urban airborne ultrafine particles, originating from transport and other anthropogenic sources, which pose significant health and environmental risks. The aim of this project is to address this deficiency by an extensive multi-city, cross-disciplinary study using state of the art instrumentation and data analytic techniques. The outcome will be an in depth, quantitative insight into the characteristics of the particles, their sources and spatial and temporal variation across different urban areas and time scales. Further, the impacts of changing fuels, vehicle technologies, and climate on future trends of the particles will be elucidated.Read moreRead less
Industrial Transformation Training Centres - Grant ID: IC170100030
Funder
Australian Research Council
Funding Amount
$4,133,659.00
Summary
ARC Training Centre in Cognitive Computing for Medical Technologies. The ARC Training Centre in Cognitive Computing for Medical Technologies aims to create a workforce that is expert in developing, applying and interrogating cognitive computing technologies in data-intensive medical contexts. This will facilitate the next generation of data-driven and machine learning-based medical technologies. The Centre will provide a world-class industry-driven research training environment for PhD students ....ARC Training Centre in Cognitive Computing for Medical Technologies. The ARC Training Centre in Cognitive Computing for Medical Technologies aims to create a workforce that is expert in developing, applying and interrogating cognitive computing technologies in data-intensive medical contexts. This will facilitate the next generation of data-driven and machine learning-based medical technologies. The Centre will provide a world-class industry-driven research training environment for PhD students and postdoctoral researchers. These researchers will lead the medical technology industry into a new era of data-driven personalised and precision medical devices and applications. The Centre will result in the development of capabilities in the core technologies of machine learning and the practical application of cognitive computing in the area of health.Read moreRead less
ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies th ....ARC Centre of Excellence for Robotic Vision. Robots are vital to Australia's future prosperity in the face of high relative wages, low or decreasing productivity, and impending labour shortages. However the work and workplaces of our most important industries are unstructured and changeable and current robots are challenged by their inability to quickly, safely and reliably "see" and "understand" what is around them. The Centre's research will create the fundamental science and technologies that will allow robots to see as we do, and overcome the last barrier to the ubiquitous deployment of robots into society for the benefit of all.Read moreRead less
Industrial Transformation Research Hubs - Grant ID: IH180100002
Funder
Australian Research Council
Funding Amount
$5,000,000.00
Summary
ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. Thes ....ARC Research Hub for Driving Farming Productivity and Disease Prevention. The ARC Research Hub for Driving Farming Productivity and Disease Prevention aims to increase farm production and disease prevention through advancing and transferring new artificial intelligence technologies into industrial deployment. The Hub will combine machine vision, machine learning, software quality control, engineering, biology, and farming industries to develop technologies to build more intelligent systems. These dynamic systems will help determine what goal to achieve and the most efficient plan to achieve it. This Hub is expected to contribute to higher farming efficiency, lower production costs and fewer disease risks, giving the Australian industry new business opportunities and an international competitive advantage.Read moreRead less