{"links":{"self":"http://dataportal.arc.gov.au/NCGP/API/grants/FT250100844"},"data":{"type":"grant-details","id":"FT250100844","attributes":{"code":"FT250100844","administering-organisation":"The University of New South Wales","announcement-administering-organisation":"The University of New South Wales","scheme-name":"ARC Future Fellowships","grant-status":"Active","funding-commencement-year":2025,"years-funded":4,"project-start-date":"2026-04-06","anticipated-end-date":"2030-04-05","grant-summary":"An Intelligent Spatial Data Management System for Smart Query Processing. Spatial data and its effective management are essential across various domains, including public health, transportation, urban planning, cybersecurity, logistics, and emergency management. It provides critical insights and enables better decision-making and analysis. Spatial data often involves high-dimensional, non-linear patterns that traditional methods struggle to capture. This project aims to develop an intelligent spatial database system for smart query processing using novel machine-learning techniques and large language models to handle such complexity effectively. The success of this project will open up new research directions to enrich frontier technologies and establish our leadership in the global geospatial analytics market.","funding-current":1115563.00,"funding-at-announcement":1091272,"investigators-current":[{"title":"Dr","firstName":"Xin","familyName":"Cao","roleName":"Future Fellowship","roleCode":"FT","isFellowship":true,"orcidIdentifier":null}],"investigators-at-announcement":[{"title":"Dr","firstName":"Xin","familyName":"Cao","roleName":"Future Fellowship","roleCode":"FT","isFellowship":true,"orcidIdentifier":null}],"organisations-current":[{"organisationName":"The University of New South Wales","roleName":"Administering Organisation","state":"NSW"}],"organisations-at-announcement":[{"organisationName":"The University of New South Wales","roleName":"Administering Organisation","state":"NSW"}],"field-of-research":[{"isPrimary":true,"code":"4605","name":"Data Management and Data Science","type":"FOR20"},{"isPrimary":false,"code":"460505","name":"Database Systems","type":"FOR20"}],"socio-economic-objective":[{"code":"220302","name":"Electronic Information Storage and Retrieval Services","type":"SEO20"},{"code":"220408","name":"Information Systems","type":"SEO20"}],"international-collaboration":["Denmark","Hong Kong (SAR of China)","Singapore"],"lief-register":[],"achievement-summary":null,"national-interest-test-statement":"Spatial data is being generated at an unprecedented rate from mobile and internet-connected devices, and it has become a vital tool for people who need information on land, the environment, transport, communications, utility services, and demographics. For example, in the NSW Spatial Digital Twin program, a digital version of a city, enhanced with real-time data from sensors and 5G networks, will allow identifying flood-prone zones and fire-risk areas to improve emergency planning and response. Traditional spatial data management methods struggle to capture the data complexity including high-dimensions and non-linear patterns. This project will develop effective spatial indices and efficient query-processing algorithms powered by novel machine-learning techniques and large language models. The outcomes will enhance Australia's capacity to address challenges such as urban congestion, disaster response, and environmental sustainability. The system will also contribute to the digital transformation agenda by enabling seamless spatial data integration into smart technologies, such as Internet of Things (IoT) networks and autonomous systems. The research promotes innovation in spatial data management and strengthens Australia’s position in the global technology landscape. The solutions developed through this project can be applied across various sectors, including agriculture, transport, energy, and public health, ensuring broad economic and societal impact."}}}