New digital deep-time exploration tools for a low-emissions economy. Demand for critical minerals will soar as renewable energy generation increases, but exploration companies currently cannot take full advantage of available exploration data in an Earth evolution context. This project will generate new knowledge in big and complex geodata analysis using an innovative data mining approach. It will enable Lithodat, a small enterprise, to perform cloud-based plate tectonic reconstruction, visualis ....New digital deep-time exploration tools for a low-emissions economy. Demand for critical minerals will soar as renewable energy generation increases, but exploration companies currently cannot take full advantage of available exploration data in an Earth evolution context. This project will generate new knowledge in big and complex geodata analysis using an innovative data mining approach. It will enable Lithodat, a small enterprise, to perform cloud-based plate tectonic reconstruction, visualisation and spatio-temporal analysis of geodata for resource exploration. The outcomes include an enhanced capacity to generate ore prospectivity maps and an improved understanding of their tectonic, geochemical, and geophysical signatures, benefiting Lithodat and their clients in the search for new mineral deposits.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