This research aims to develop a framework to recognise and anticipate unforeseen emerging situations, such as schedule changes, incidents, and disruptions. 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. - ARC Discovery Project DP190101485
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CIDDA’s ADM+S Projects, funded by ARC Centre of Excellence in Automated Decision Making and Society
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RMIT is host of the Centre of Excellence for Automated Decision-Making and Society.
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Behaviour Recognition: more complex
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Cortana Intelligence Institute (CII) is driving the next-generation of capabilities for Microsoft’s digital assistant, Cortana. Focused on researching work-related tasks and using sensors in mobile phones, the CII team builds a complex multidimensional data set, used to model and predict user’s work-related tasks.
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Funded by the Centre for New Energy Technology (C4Net), GWMWater, Gippsland Water
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Funded by the Centre for New Energy Technology (C4Net) and CSIRO
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Using Transfer Learning for ML-based model, transferrable to multiple cities
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A live (deployed) project in collaboration with Mornington Peninsula Shire (MPS) Reducing traffic congestion & emissions
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Reducing traffic congestion & vehicle air pollution
Show More© 2021 Flora Salim - CRUISE Research Group.