Intelligent CRM through Conjoint Data Mining of Heterogeneous Sources. This project aims to investigate and develop techniques to improve customer relationship management (CRM) for public and private organisations. It aims to develop an intelligent framework to assist in adaptive marketing and management of customers. The framework is designed to manage multiple information resources for information sharing, and to synthesise knowledge through visualisation. Intended outcomes are standardised XM ....Intelligent CRM through Conjoint Data Mining of Heterogeneous Sources. This project aims to investigate and develop techniques to improve customer relationship management (CRM) for public and private organisations. It aims to develop an intelligent framework to assist in adaptive marketing and management of customers. The framework is designed to manage multiple information resources for information sharing, and to synthesise knowledge through visualisation. Intended outcomes are standardised XML profiles for the different data sets and business processes, novel techniques for conjoint mining of structured and semi-structured data, and adaptive business intelligence techniques. The results will be validated using large real-world data sets provided by the partner organisation.Read moreRead less
Predictive analytics from at home telemonitoring of vital signs. Predictive analytics from at home telemonitoring of vital signs. This project aims to reduce unscheduled admissions to hospital, by developing statistical models of people’s health using longitudinal measurements of vital signs and questionnaires. Hospital costs are becoming unsustainable and will overwhelm state budgets within thirty years. Telehealth monitoring to manage chronic disease is becoming increasingly routine internatio ....Predictive analytics from at home telemonitoring of vital signs. Predictive analytics from at home telemonitoring of vital signs. This project aims to reduce unscheduled admissions to hospital, by developing statistical models of people’s health using longitudinal measurements of vital signs and questionnaires. Hospital costs are becoming unsustainable and will overwhelm state budgets within thirty years. Telehealth monitoring to manage chronic disease is becoming increasingly routine internationally and should reduce unnecessary hospital admissions and health service costs. To scale up telehealth services nationally, automated means of assessing changes in an individual health status are needed. This project’s automated risk assessment models are expected to identify exacerbations and orchestrate an optimal response from health services to reduce unscheduled admissions to hospital.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE190100431
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Optimising the use of geophysical data for modelling the Australian crust. This project aims to determine the optimal use of geophysical methods to model the Australian crust in four dimensions. These models provide an understanding of the tectonic history of a region and thus its mineral potential. Mineral resources are mostly being found undercover, requiring geophysical data to locate them. This project will combine recent developments in modelling geological uncertainty with data acquired fo ....Optimising the use of geophysical data for modelling the Australian crust. This project aims to determine the optimal use of geophysical methods to model the Australian crust in four dimensions. These models provide an understanding of the tectonic history of a region and thus its mineral potential. Mineral resources are mostly being found undercover, requiring geophysical data to locate them. This project will combine recent developments in modelling geological uncertainty with data acquired for locating zones of mineralisation. The outcomes will help guide Australian government policy to draw on publicly-available datasets that provide a basis for mineral exploration performed by companies, and supported by research institutions.Read moreRead less
Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provi ....Data-driven water quality treatment management decision support system. Data-driven water quality treatment management decision support system. This project aims to develop a robust decision support system to predict manganese and the character and concentration of dissolved organic matter in drinking water reservoirs, using intelligent algorithms and data collected through remote autonomous instrumentation. These predicted water quality parameters could be used as model input variables to provide real-time decisions for plant operators on the required treatment regime for incoming raw water, and advise them on the optimal reservoir offtake depth. This will potentially minimise treatment costs and health risks for consumers. The ultimate goal is to significantly enhance current water supply management practices.Read moreRead less
Next generation Customer Relationship Management (CRM) framework through intelligence and relationships from multiple information sources. In the current competitive times, organisations need to improve their service delivery and customer care processes and provide customised service to customers. This project develops a Customer Relationship Management (CRM) framework that can extract intelligence and relationships from multiple data sources to improve customer management and satisfaction in pu ....Next generation Customer Relationship Management (CRM) framework through intelligence and relationships from multiple information sources. In the current competitive times, organisations need to improve their service delivery and customer care processes and provide customised service to customers. This project develops a Customer Relationship Management (CRM) framework that can extract intelligence and relationships from multiple data sources to improve customer management and satisfaction in public and private organisations.Read moreRead less