Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing ....Developing key vision technology for automation of aquaculture factory. This project aims to investigate structural, coloured textural, and hyperspectral analysis approaches to achieve automated lobster molt-cycle staging and classification to the level required for commercial production. High labour cost, water contamination, and disease transmission are major barriers in Australian bay lobster aquaculture inhibiting its large scale production. Automation of the production process and reducing the human contact with animals are of high priority in the development of this Australian-led emerging industry. The project aims to develop technology to bring this world- first aquaculture factory to large scale production, and create new export opportunities for lobsters and production systems.Read moreRead less
Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it i ....Robust, valid and interpretable deep learning for quantitative imaging. One of the biggest challenges in employing artificial intelligence is the “black-box” nature of the models used. This project aims to improve the effectiveness and trustworthiness of deep learning within quantitative magnetic resonance imaging. Deep learning has great promise in speeding-up complex image processing tasks, but currently suffers from variable data inputs, predictions are not guaranteed to be plausible and it is not clear to the end user how reliable the results are. The outcomes intend to deliver advanced knowledge and capability in artificial intelligence and machine learning that Australia urgently needs to capitalise on bringing deep learning into practical applications delivering economic, commercial and social impact.Read moreRead less
Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning proc ....Multi-Modal Dictionary Learning for Smart City Operation and Management. This Project aims to provide new digital asset management tools for city councils to improve city services by utilising new sensing and automated learning technologies for recognising, tracking and auditing of assets. Currently, there are no digital tools available to handle these services. This project proposes new multi-modal sensing and mapping of city asset techniques by building new multi-modal dictionary learning procedures. The new framework will recognise different conditions of city assets in real-time to make decisions. Expected outcomes of this Project include integration and easy access of assets with unique digital identities to help city councils, governments, and navigation services for real-time asset monitoring.Read moreRead less
Open Standards design for improved road network information exchange. Open Standards design for improved road network information exchange. This project aims to design a draft digital open source performance-based construction contract specification for delivering road construction information to operational network asset management. This will be a common information exchange specification for all road agencies to standardise exchange of their assets data. Road network construction and maintenan ....Open Standards design for improved road network information exchange. Open Standards design for improved road network information exchange. This project aims to design a draft digital open source performance-based construction contract specification for delivering road construction information to operational network asset management. This will be a common information exchange specification for all road agencies to standardise exchange of their assets data. Road network construction and maintenance costs $21 billion annually, but the outcome of this project is expected to save $65 to $130 million annually through data harmonisation. This project is at the leading edge of information management for roads and is expected to change several international standards.Read moreRead less
A Socially Conscious Smart IoT Platform for Water Quality Monitoring. This project will develop an intelligent remote water quality monitoring platform based on a new sensor network architectural paradigm. Expected outcomes include an artificially intelligent water quality monitoring system that is produced via a unique social enterprise business model. This approach will facilitate widespread remote water quality monitoring, leading to an enhanced understanding of the environment, whilst provid ....A Socially Conscious Smart IoT Platform for Water Quality Monitoring. This project will develop an intelligent remote water quality monitoring platform based on a new sensor network architectural paradigm. Expected outcomes include an artificially intelligent water quality monitoring system that is produced via a unique social enterprise business model. This approach will facilitate widespread remote water quality monitoring, leading to an enhanced understanding of the environment, whilst providing valuable training/education for the community stakeholders involved in the production of the system. The research outcome will be globally significant, enabling end users to meet key water quality objectives over time, and considerably increase productivity in the Australian agriculture/aquaculture industries.Read moreRead less