Enhancing the content and experience of Interactive Childrens Television. Interactive television (iTV) as a participatory, on-demand communication provides a unique opportunity to significantly engage, entertain and educate preschool children. Through considerable industry partner collaboration and participation, this project will evaluate three distinct interactive options produced from selected children's television programs with proven success in Australia. Usability studies employing a vari ....Enhancing the content and experience of Interactive Childrens Television. Interactive television (iTV) as a participatory, on-demand communication provides a unique opportunity to significantly engage, entertain and educate preschool children. Through considerable industry partner collaboration and participation, this project will evaluate three distinct interactive options produced from selected children's television programs with proven success in Australia. Usability studies employing a variety of surveillance techniques will evaluate content design and user response. Children's viewing habits will be evaluated within a social context (the home) and a mobile lab setting using qualitative and quantitative assessment. The results will identify effective ways to produce meaningful interactivity and will encourage future industry based research.Read moreRead less
A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons fo ....A Machine Learning Framework for Concrete Workability Estimation . Concrete is the most used construction material in Australia. The project aims to develop a system to measure the workability of concrete in transit in agitator trucks using advanced machine vision and machine learning, and provide a reliable alternative to the current practice of visually testing concrete workability by certified testers. Concrete that fails to meet workability requirements is one of the most frequent reasons for rejection at construction sites, resulting in significant costs, waste, and delays. Multimodal data sources will be used to provide a reliable workability estimate in real time, enabling construction teams to identify and rectify workability issues in transit while continuously monitoring the adjustments effects.Read moreRead less