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Articles 1 - 9 of 9
Full-Text Articles in Physical Sciences and Mathematics
Towards Agent-Based Traffic Simulation Using Live Data From Sensors For Smart Cities, Johan Barthelemy, Yan Qian, Pascal Perez
Towards Agent-Based Traffic Simulation Using Live Data From Sensors For Smart Cities, Johan Barthelemy, Yan Qian, Pascal Perez
SMART Infrastructure Facility - Papers
The Smart City and Internet-of-Things revolutions enable the collection of various types of data in real-time through sensors. This data can be used to improve the decision tools and simulations used by city planners. This paper presents a new framework for real-time traffic simulation integrating an agent-based methodology with live CCTV and other sensor data while respecting the privacy regulations. The framework simulates traffic flows of pedestrians, vehicles and bicycles and their interactions. The approach has been applied in Liverpool (NSW, Australia) showing promising preliminary results and can easily ingest additional sensor data, e.g. air quality.
Estimating Travellers’ Trip Purposes Using Public Transport Data And Land Use Information, Bo Du
Estimating Travellers’ Trip Purposes Using Public Transport Data And Land Use Information, Bo Du
SMART Infrastructure Facility - Papers
In public transport system, the equipped automated fare collection (AFC) system records travellers’ spatial and temporal information and generates a mass of data daily with more than ever attraction of interest and attention from both academics and practitioners. Advances in data availability and data mining techniques provide great opportunity to investigate various researches in an efficient and effective manner. A comprehensive literature review on the application of public transport smart card data before 2011 can be referred to [1]. As some relevant studies in recent years, [2] proposed a data fusion method to infer passengers’ behavioral attributes of the trips …
Data Mining In Educational Technology Classroom Research: Can It Make A Contribution?, Charoula Angeli, Sarah Katherine Howard, Jun Ma, Jie Yang, Paul A. Kirschner
Data Mining In Educational Technology Classroom Research: Can It Make A Contribution?, Charoula Angeli, Sarah Katherine Howard, Jun Ma, Jie Yang, Paul A. Kirschner
SMART Infrastructure Facility - Papers
The paper addresses and explains some of the key questions about the use of data mining in educational technology classroom research. Two examples of use of data mining techniques, namely, association rules mining and fuzzy representations are presented, from a study conducted in Europe and another in Australia. Both of these studies examine student learning, behaviors, and experiences within computer-supported classroom activities. In the first study, the technique of association rules mining was used to understand better how learners with different cognitive types interacted with a simulation to solve a problem. Association rules mining was found to be a useful …
Investigating The Accuracy Of Georeferenced Social Media Data For Flood Mapping: The Petajakarta.Org Case Study, Robert Ighodaro Ogie, Hugh I. Forehead
Investigating The Accuracy Of Georeferenced Social Media Data For Flood Mapping: The Petajakarta.Org Case Study, Robert Ighodaro Ogie, Hugh I. Forehead
SMART Infrastructure Facility - Papers
Georeferenced social media data are gaining increased application in creating near real-time flood maps needed to improve situational awareness in data-starved regions. However, there is growing concern that the georeferenced locations of flood-related social media contents do not always correspond to the actual locations of the flooding event. But to what extent is this true? Without this knowledge, it is difficult to ascertain the accuracy of flood maps created using georeferenced social media contents. This study aims to improve understanding of the extent to which georeferenced locations of social media flood reports deviate from the actual locations of floods. The …
Big Data, Big Theory: Moving Beyond New Empiricism To Generate Powerful Explanations, Sarah Katherine Howard, Karl A. Maton, Ellie Rennie, Jun Ma, Jie Yang, Julian Thomas, Matthew Ciao, Rangan Srikhanta
Big Data, Big Theory: Moving Beyond New Empiricism To Generate Powerful Explanations, Sarah Katherine Howard, Karl A. Maton, Ellie Rennie, Jun Ma, Jie Yang, Julian Thomas, Matthew Ciao, Rangan Srikhanta
SMART Infrastructure Facility - Papers
Abstract presented at the 3rd ISA Forum of Sociology, 10-14 July 2016, Vienna, Austria
Mining A System: The Use Of Data Mining And System Dynamics To Explore Technology Integration, Sarah Katherine Howard, Jun Ma, Jie Yang, Kate Thompson
Mining A System: The Use Of Data Mining And System Dynamics To Explore Technology Integration, Sarah Katherine Howard, Jun Ma, Jie Yang, Kate Thompson
SMART Infrastructure Facility - Papers
Abstract presented at the 16th Biennial EARLI Conference for Research on Learning and Instruction, 25-29 August 2015, Limassol, Cyprus
Modelling And Data Frameworks For Understanding Infrastructure Systems Throuh A Systems-Of-Systems Lens, Matthew J. Berryman, Rohan Wickramasuriya, Vu Lam Cao, Pascal Perez
Modelling And Data Frameworks For Understanding Infrastructure Systems Throuh A Systems-Of-Systems Lens, Matthew J. Berryman, Rohan Wickramasuriya, Vu Lam Cao, Pascal Perez
SMART Infrastructure Facility - Papers
Modelling and analysis of large systems of infrastructure systems carries with it a number of challenges, in particular around the volume of data and the requisite complexity (and thus computing resources required) of models. In this paper we present an integrated land use–transportation model of a region in Sydney, and detail how we integrated an agent-based model of location and transport choice with a traffic micro-simulator. We also discuss both some novel architectures for scalability of modelling as well as for fusion and relevant visualisation of large data sets. We have a particular focus on geospatial infrastructure data visualisation.
Data-Driven Modeling And Analysis Of Household Travel Mode Choice, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya Denagamage, Nam N. Huynh
Data-Driven Modeling And Analysis Of Household Travel Mode Choice, Nagesh Shukla, Jun Ma, Rohan Wickramasuriya Denagamage, Nam N. Huynh
SMART Infrastructure Facility - Papers
One of the important problems studied in the area of travel behavior analysis is travel mode choice which is one of the four crucial steps in transportation demand estimation for urban planning. State of the art models in travel demand modelling can be classified as trip based; tour based; and activity based. In trip based approach, each individual trips is modelled as independent and isolated trips i.e. no connections between different trips. In tour based approach, trips that start and end from the same location (home, work, etc) and trips within a tour are dependent on each other. In past …
The Smart Way To Manage Research Data, Craig Napier, Despina Clancy, Tim Davies, Katie Elcombe
The Smart Way To Manage Research Data, Craig Napier, Despina Clancy, Tim Davies, Katie Elcombe
SMART Infrastructure Facility - Papers
The University of Wollongongs' $62 million SMART (Simulation, Modelling, Analysis, Research, Teaching) Infrastructure Facility will become a research and development powerhouse with an unprecedented level of impact within the broader infrastructure sector nationally and overseas [1]. With a vision to be a world class intellectual leader and educator in 'integrated' infrastructure planning and management and the capacity to host 200 PhD students, comprising 30 integrated research laboratories, data demands and volume are increasing exponetially.