The outcome of the project is to have the capability to obtain relevant data analytics from fixed cameras & have the capability to run those analytics themselves.
Dr Ali Ardeshiri is an urban economist/choice modeller at the University of South Australia. Here we find out more about his research, career path, and more.
The major findings from our Recalibrating Adelaide’s strategic transport model project, plus download a copy of the final report.
Change brings tension and stress, but also opportunities for improvement. And so it is with our new Federal Government and matters of transport.
This new iMOVE report distils all the work we’re doing in the area of Working from Home, along with our policy considerations and recommendations.
Watch the recording of our ‘Digitisation of transport and freight: How are we tracking in Australia, and where are the opportunities?’ webinar.
Download the final report from iMOVE’s ‘Digitisation in transport and freight: Lessons for Australia’ project.
This project’s evidence-based approach will allow Main Roads Western Australia’s improvement of roundabout modelling practice and guidelines.
This project investigates the use of an integrated package of IoT, computer vision and machine learning to support smart bridge health monitoring and prediction.
This project will develop a framework/tool for forecasting future scenarios of urban freight in informing planning and regulation (transport and land use).
This PhD project will analyse archived GTFS data to identify significant inefficient road designs and exemplary designs for optimising performance
iMOVE’s most-read articles of 2021, counted down from 10 to number 1.
The newly-announced National Location Registry will perform a pivotal role in providing more accurate and reliable Australian location data.
Development/delivery of a low-cost IoT-based system for live tracking & condition monitoring of freight consignments across multiple carriers & transport modes.
Despite many of our partners being significantly impacted by COVID restrictions, iMOVE is still delivering $10 million of project activity annually.
This project will develop data fusion and machine learning models to estimate service use for Melbourne trams and make real-time prediction of tram loads.