Machine Assisted, Multi-scale Spatial and Temporal Observation and Modeling of Marine Benthic Habitats. The Integrated Marine Observing System (IMOS) science plans include sampling campaigns reliant on Autonomous Underwater Vehicle (AUV) Facility data and designed to address the issues of marine biodiversity quantification and assurance. The proposed research will directly enhance the effectiveness of these programs by speeding labour-intensive analyses, aggregating the results, and searching f ....Machine Assisted, Multi-scale Spatial and Temporal Observation and Modeling of Marine Benthic Habitats. The Integrated Marine Observing System (IMOS) science plans include sampling campaigns reliant on Autonomous Underwater Vehicle (AUV) Facility data and designed to address the issues of marine biodiversity quantification and assurance. The proposed research will directly enhance the effectiveness of these programs by speeding labour-intensive analyses, aggregating the results, and searching for ecological patterns on a national scale that would be difficult to identify using traditional approaches tuned to process-scale studies. Australian society stands to benefit by virtue of improved large-scale models of ecosystem function and reduced cost for conducting marine ecosystem investigations.Read moreRead less
The endangered swift parrot as a model for managing small migratory birds. Endangered swift parrots use variable locations while breeding in eastern Tasmania and over winter on the Australian mainland. This project aims to develop effective conservation strategies for swift parrots and other migrants using new and long term data and innovative technological solutions to tracking small birds across vast landscapes.
Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data ar ....Visual analytics for massive multivariate networks. Visual analytics for massive multivariate networks. This project aims to create methods to visually analyse massive multivariate networks. The amount of network data available has exploded in recent years: software systems, social networks and biological systems have millions of nodes and billions of edges with multivariate attributes. Their size and complexity makes these data sets hard to exploit. More efficient ways to understand the data are needed. This project will design, implement and evaluate visualisation methods for massive multivariate network data sets. This research is expected to be used by Australian software development, biotechnology and security companies to exploit their data.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
Industrial Transformation Training Centres - Grant ID: IC190100033
Funder
Australian Research Council
Funding Amount
$3,852,568.00
Summary
ARC Training Centre for Transformation of Australia's Biosolids Resource. This Centre aims to bring together Australia’s leading biosolids researchers and key industry and government stakeholders to advance the management, transformation and reuse of biosolids in agriculture. The focus is: 1) capability and knowledge building, 2) research development, extension and training, 3) sustainable strategic partnerships. The expected outcomes of the Centre are to develop a group of new, highly-trained i ....ARC Training Centre for Transformation of Australia's Biosolids Resource. This Centre aims to bring together Australia’s leading biosolids researchers and key industry and government stakeholders to advance the management, transformation and reuse of biosolids in agriculture. The focus is: 1) capability and knowledge building, 2) research development, extension and training, 3) sustainable strategic partnerships. The expected outcomes of the Centre are to develop a group of new, highly-trained industry-ready researchers as well as advanced solutions in three major themes: improved technologies, enhanced products and sustainability. This will provide significant benefits in the economic value of new applications and market opportunities as well as deliver cost-savings – all in an environmentally friendly manner.Read moreRead less
Clothes, fibres and filters that reduce pollution by micro and nano debris. This project aims to provide scientifically verified methods to avoid, intercept and redesign products that cause the most abundant type of marine plastic pollution – clothing fibres - which has increased by over 450% in 60 years. It will determine how natural and plastic fibres, clothing brands and washing machine filters, alter fibre emissions and ecological impacts. This will enable protocols to improve products and t ....Clothes, fibres and filters that reduce pollution by micro and nano debris. This project aims to provide scientifically verified methods to avoid, intercept and redesign products that cause the most abundant type of marine plastic pollution – clothing fibres - which has increased by over 450% in 60 years. It will determine how natural and plastic fibres, clothing brands and washing machine filters, alter fibre emissions and ecological impacts. This will enable protocols to improve products and the environment, and reduce health risks that will benefit the public, government regulation and companies in designing "eco-friendly" products.Read moreRead less
Keystone effects of Australia's top predators: dingoes, devils and biodiversity. This project will study the interactions of Australia's two largest predators, the dingo and Tasmanian devil, with other species. The project will help develop an understanding of the value of these predators in maintaining ecosystem processes and diversity, and guide their management in the future.
Modelling and control of mosquito-borne diseases in Darwin using long-term monitoring. Management of mosquito populations is a high public health priority because these insects can spread diseases such as malaria, dengue, Ross River virus, Barmah Forest virus, Murray Valley encephalitis, Japanese encephalitis and Kunjin/West Nile virus. Our research into the effectiveness of mosquito control programs in Darwin is of immediate national relevance and priority given the need to Safeguard Australia ....Modelling and control of mosquito-borne diseases in Darwin using long-term monitoring. Management of mosquito populations is a high public health priority because these insects can spread diseases such as malaria, dengue, Ross River virus, Barmah Forest virus, Murray Valley encephalitis, Japanese encephalitis and Kunjin/West Nile virus. Our research into the effectiveness of mosquito control programs in Darwin is of immediate national relevance and priority given the need to Safeguard Australia from invasive diseases. There is an urgency to undertake our research because global environmental change and increasing movements of people (particularly military personnel) from overseas regions where these diseases are endemic is increasing the vulnerability of northern Australia to the (re)establishment of mosquito borne diseases.Read moreRead less
Anthropogenic influences on the source, transformation and fate of carbon and nitrogen in coastal waters: a case study of the Derwent Estuary. Ninety five percent of Australia's population live in the coastal zone on the shores of our major bays and estuaries. These water bodies are valuable resources for recreation, boating, fishing, marine transport and industry, but some activities, particularly the release of nitrogen, impose an environmental and economic cost. This project will significant ....Anthropogenic influences on the source, transformation and fate of carbon and nitrogen in coastal waters: a case study of the Derwent Estuary. Ninety five percent of Australia's population live in the coastal zone on the shores of our major bays and estuaries. These water bodies are valuable resources for recreation, boating, fishing, marine transport and industry, but some activities, particularly the release of nitrogen, impose an environmental and economic cost. This project will significantly advance our understanding of the natural processes that control the transformation and fate of nitrogen in coastal waters. As such the outcomes of this study will provide key information for managers on the environmental outcomes of nutrient management strategies.Read moreRead less
Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire ....Physics-aware machine learning for data-driven fire risk prediction. The 2019/20 Australian fire season was unprecedented in its extent, impact, and the response of fire agencies. In this project, we aim to answer the question: was the scale of these fires driven by known drivers of fire (drought, weather, fuels and ignitions), or were fundamentally new undescribed processes and phenomena involved? We will accomplish this by developing an innovative, physics-aware machine learning model of fire risk and spread, trained and validated on a two-decade satellite fire record. The predictive ability of the model will be tested on the 2019/20 fire season to determine if novel drivers of fire can be identified, and the model itself will be operationalised into a novel short-to-mid term fire risk prediction tool. Read moreRead less