Discovery Early Career Researcher Award - Grant ID: DE230100049
Funder
Australian Research Council
Funding Amount
$459,030.00
Summary
Towards automated Australian Sign Language translation. This project aims to address the computational modelling of Auslan. The project expects to generate knowledge by creating the largest Auslan dataset, enabling further advancements in this research area. The dataset will also play an essential role in other research fields, e.g., sign linguistics. Expected outcomes include the invention of the first Auslan recogniser and generator capable of distinguishing and synthesising 1000+ signs, repre ....Towards automated Australian Sign Language translation. This project aims to address the computational modelling of Auslan. The project expects to generate knowledge by creating the largest Auslan dataset, enabling further advancements in this research area. The dataset will also play an essential role in other research fields, e.g., sign linguistics. Expected outcomes include the invention of the first Auslan recogniser and generator capable of distinguishing and synthesising 1000+ signs, representing a substantial advancement towards fully automated Auslan translation. This should provide significant benefits for the Australian Deaf community, such as high-quality digital systems for education and communication, resulting in increased quality of life and inclusion in the Australian society.Read moreRead less
Scalable Stream Processing in Hybrid Edge-Cloud Infrastructures. This project aims to develop a new computational paradigm to ensure low-latency services for streaming applications across heterogeneous Edge devices while satisfying high-throughput and scalability requirements. This project is of high significance for generating new knowledge in the area of real-time streaming using innovative algorithms that overcome the limitations of remote Cloud and distributed Edge computing. Expected outcom ....Scalable Stream Processing in Hybrid Edge-Cloud Infrastructures. This project aims to develop a new computational paradigm to ensure low-latency services for streaming applications across heterogeneous Edge devices while satisfying high-throughput and scalability requirements. This project is of high significance for generating new knowledge in the area of real-time streaming using innovative algorithms that overcome the limitations of remote Cloud and distributed Edge computing. Expected outcomes include novel programming abstractions, performance models, and control mechanisms to address complex problems for incremental and iterative computations in hybrid Edge-Cloud infrastructures. This should provide significant benefits, one of which is the optimised utilisation of limited computing resources.Read moreRead less
Adaptive and Ubiquitous Trust Framework for Internet of Things interactions. The aim of the project is to address the Trust challenges in Internet of Things (IoT) environments, thus enabling the wide deployment of potentially billions of IoT devices. This project will generate new knowledge in the area of IoT Trust by developing novel techniques to establish trust in highly dynamic crowdsourcing IoT environments. The project's main outcomes include the development of a ubiquitous and adaptive mu ....Adaptive and Ubiquitous Trust Framework for Internet of Things interactions. The aim of the project is to address the Trust challenges in Internet of Things (IoT) environments, thus enabling the wide deployment of potentially billions of IoT devices. This project will generate new knowledge in the area of IoT Trust by developing novel techniques to establish trust in highly dynamic crowdsourcing IoT environments. The project's main outcomes include the development of a ubiquitous and adaptive multi-component trust framework reflecting trust perspectives. The developed solutions will allow the establishment of trusted interactions among crowdsourced IoT devices and wider deployment of convenient and just-in-time services, thus enabling the development of novel applications, such as the crowdsourcing of green energy.Read moreRead less
Multi-resolution situation recognition for urban-aware smart assistant. This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, ....Multi-resolution situation recognition for urban-aware smart assistant. This project aims to develop a situation recognition framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions in an urban environment. The project will address a significant knowledge gap by capturing and modelling unpredictability in human mobility and work routines. The outcome will be a situation recognition framework that can be applied at the individual, social group, and urban level, and at multiple locations and time scales. This should provide users with timely notifications and recommendations to resume their activities and routines. The expected benefits will be far-ranging and adaptable to many domains, from personal smart assistants to trip planning and emergency services.Read moreRead less
Explainable machine learning for electrification of everything. The energy sector is the largest contributor to greenhouse gas emissions. "Electrification of Everything" combined with electricity generation from renewables is a key solution to decarbonise the energy and transport sectors. This project aims to develop an explainable machine learning based data-driven technology to accurately predict the impact of electrification on consumers energy consumption and cost. The expected outcome of th ....Explainable machine learning for electrification of everything. The energy sector is the largest contributor to greenhouse gas emissions. "Electrification of Everything" combined with electricity generation from renewables is a key solution to decarbonise the energy and transport sectors. This project aims to develop an explainable machine learning based data-driven technology to accurately predict the impact of electrification on consumers energy consumption and cost. The expected outcome of this project includes a data-informed decision support technology to help consumers choose the best electrification technologies and solutions. This should provide significant benefits, such as increasing community engagement with electrification, and thus reducing their carbon footprint.Read moreRead less
Adaptive context caching for fast concurrent access in Internet of Things. Context-awareness in Internet of Things (IoT) applications has profound impact on smartness, relevance, adaptability, dependability, performance and flexibility of such applications. This project will address the significant knowledge gap by investigating, proposing and validating a novel adaptive context caching scheme for fast near real-time access in multiple concurrent context queries coming from multiple and diverse ....Adaptive context caching for fast concurrent access in Internet of Things. Context-awareness in Internet of Things (IoT) applications has profound impact on smartness, relevance, adaptability, dependability, performance and flexibility of such applications. This project will address the significant knowledge gap by investigating, proposing and validating a novel adaptive context caching scheme for fast near real-time access in multiple concurrent context queries coming from multiple and diverse IoT applications. The outcome will be a critical component of the IoT context management platform called Context-as-a-Service which is currently under development. The expected benefits will be far ranging and applicable to many domains including intelligent transportation, industrial internet and smart cities..Read moreRead less
Efficient and fair context-aware resource allocation in networks. This project aims to develop a flexible mathematical framework for internet resource allocation among competing demands by exploiting application context to allocate resources more efficiently. The project will extend an existing framework which allocates resources independently at each time period, by considering benefits over periods of time relevant to users. The expected outcome of this project is a systematic method for desig ....Efficient and fair context-aware resource allocation in networks. This project aims to develop a flexible mathematical framework for internet resource allocation among competing demands by exploiting application context to allocate resources more efficiently. The project will extend an existing framework which allocates resources independently at each time period, by considering benefits over periods of time relevant to users. The expected outcome of this project is a systematic method for designing next-generation congestion-avoidance protocols that anticipate and accommodate different types of demand. This project will provide significant benefits including better provision of internet services and new ways to help combat traffic congestion, bringing benefits to both the environment and society.Read moreRead less
Stability Analysis of Power System with Massive Power Electronic Devices. The decarbonization of Australia's power systems is to integrate massive renewable energy sources which are interfaced with many power electronic devices (PEDs). The fast and complex dynamics of PEDs have significantly changed the nature of the power system, which limits the applicability of existing tools and methods to assess its stability. The goal of this project is to gain a comprehensive insight into the stability of ....Stability Analysis of Power System with Massive Power Electronic Devices. The decarbonization of Australia's power systems is to integrate massive renewable energy sources which are interfaced with many power electronic devices (PEDs). The fast and complex dynamics of PEDs have significantly changed the nature of the power system, which limits the applicability of existing tools and methods to assess its stability. The goal of this project is to gain a comprehensive insight into the stability of a futuristic power system with high penetration of PEDs. The intended outcomes will be a model and data jointly driven methodology for high-efficient and real-time stability assessment. The methodology developed in this project will support Australia's transition to a stable, secure, and low-carbon power grid.Read moreRead less
Resilient design of energy pile foundations toward zero carbon buildings. This project aims to investigate the complex thermo-hydro mechanical interactions affecting the effectiveness of energy pile foundations for improved energy efficiency of new buildings. Using cutting-edge micro to field-scale methods, this project expects to underpin the development of experimentally validated predictions of the geotechnical performance of energy piles. Expected outcomes of this project are the establishme ....Resilient design of energy pile foundations toward zero carbon buildings. This project aims to investigate the complex thermo-hydro mechanical interactions affecting the effectiveness of energy pile foundations for improved energy efficiency of new buildings. Using cutting-edge micro to field-scale methods, this project expects to underpin the development of experimentally validated predictions of the geotechnical performance of energy piles. Expected outcomes of this project are the establishment of new approaches to improve the resilient design of energy pile foundations, provision of new recommendations for their design and increased integration for zero carbon buildings. These outcomes will contribute significantly toward strategies to decarbonise energy systems in buildings to meet carbon neutrality goals.Read moreRead less