Infrastructure Engineering - Research Publications

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    Parking Occupancy Detection and Slot Delineation Using Deep Learning: A Tutorial
    Khoshelham, K ; Acharya, D ; Winter, S ; Goel, S (TU Wien Academic Press, 2021)
    This chapter describes a simple method for parking occupancy detection and an automatic parking slot delineation method using CCTV images. These methods will be presented in the form of MATLAB tutorials with code snippets to allow the interested reader to implement the method and obtain results on a sample dataset. The first tutorial will involve fine-tuning a pre-trained deep neural network for vehicle detection in a sequence of CCTV camera images to determine the occupancy of the parking spaces. In the second tutorial, we perform spatio-temporal analysis of the detections made by a state-of-the-art deep learning object detector (Faster-RCNN) for automatic parking slot delineation.
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    Computer Vision Techniques for Urban Mobility
    Khoshelham, K ; Winter, S ; Goel, S (TU Wien Academic Press, 2021)
    This chapter provides an overview of computer vision techniques with applications in urban mobility and transport systems. Focusing on imagery and Light Detection and Ranging (LiDAR) point clouds as the main data modalities, the chapter reviews relevant computer vision tasks, including classification, segmentation, object detection and tracking. Example applications of these techniques to data captured by stationary sensors installed in the environment as well as mobile sensors onboard vehicles will then be discussed.
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    Sensors for Parking Occupancy Detection
    Khoshelham, K ; Winter, S ; Goel, S (TU Wien Academic Press, 2021)
    This chapter provides an overview of sensor technologies and methodologies for determining the occupancy of parking spaces. It covers a range of sensors including active and passive sensors that can be installed overhead, in or on the ground in both indoor and outdoor environments. The chapter also provides a comparison of sensors, and Discusses considerations for sensor selection and open challenges in parking occupancy detection.
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    Structural Health Monitoring of Bridges Using Advanced Non-destructive Testing Technique
    Maizuar, M ; Zhang, L ; Miramini, S ; Mendis, P ; Duffield, C ; Wang, CM ; Ho, JCM ; Kitipornchai, S (Springer, Singapore, 2020-01-01)
    This paper presents an integrated framework for structural health monitoring of bridges by using advanced non-destructive testing (NDT) technique in conjunction with computational modelling. First, the structural characteristics of the Eltham Trestle Bridge under train loading were monitored using the combination of the 3D optical measurement system and IBIS-S. The results demonstrate that, in conjunction with computational modelling, the NDT can capture the structural health conditions of the bridge by analysing the natural frequencies and deformation profiles of the critical members of the bridges. Then, the developed framework also takes into account the impact of extreme events (e.g. truck impacts and earthquakes) by using a reliability-based model. Finally, using the Montague Street Bridge as a case study, it shows that proposed framework has the capability of predicting the residual life of a bridge subject to both progressive deterioration and extreme events throughout its service life.
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    Automation in structural health monitoring of transport infrastructure
    Zhang, L ; Herath, N ; Raja, BNK ; Chen, S ; Miramini, S ; Duffield, C (Springer Singapore, 2021-01-01)
    Roads are among the most important assets in the world. Road structure improvements make a crucial contribution to economic development and growth and bring important social benefits. Automation in structural health monitoring allow the accurate prediction of ongoing damage caused by long-term traffic loading. This permits optimal road structure management and ensures the longevity and safety of road structures. This chapter discusses a variety of advanced automation techniques in structural health monitoring of road structures, such as data acquisition, data processing, and life-cycle assessment. It demonstrates that the implementation of automation in road asset management can increase the productivity and extend the service life of road structures, and enhance the durability of crucial road structures and increase transport infrastructure sustainability.
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    Urban Analytics Data Infrastructure: Critical SDI for Measuring and Monitoring The National and Local Progress of SDGs
    Rajabifard, A ; Sabri, S ; Chen, Y ; Agunbiade, M ; Kalantari, M ; Rajabifard, A (CRC Press - Taylor & Francis Group, 2020-01-01)
    This chapter describes an innovative Spatial Data Infrastructure to support urban analytics and urban research capabilities focused on Australian cities, called Urban Analytics Data Infrastructure (UADI). The UADI provides opportunity for multi-disciplinary, and cross-jurisdictional analytics. The chapter highlights the UADI capabilities to be adopted for deriving the SDG indicators as a response to the UN-GGIM strategic framework 2017 { 2021 technical requirements.
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    Construction Project Managers Graduate Agile Competencies Required to Meet Industry Needs
    Vaz-Serra, P ; Hui, F ; Aye, L ; Dissanayake, R ; Mendis, P ; Weerasekera, K ; De Silva, S ; Shiromal, F (Springer, Singapore, 2021-01-01)
    The construction industry is embracing new management challenges to deal with the ever-increasing needs for collaboration, environmental and social responsibilities. Improvements in construction project management competencies are essential to helping the construction sector to embrace the new challenges. Building engineering management capabilities through the correct training are therefore essential. In research involving the twenty-four largest contractors in Australia ‘Lean construction’ was identified as an important skill to be included in academic programs that has not yet fully been embraced. Contractors are not yet seeing ‘lean’ and ‘agile’ methods as important approaches to improve communication within the teams and between projects. This research highlighted that although contractors identified communication as one of themain skills needed to achieve a good performance in project construction management they do not yet recognise that training in lean and agile methodologies will help them to improve communication not only between professionals but between projects and organisations involved in each project in improving business goals.
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    What’s next? New forms of city diplomacy and emerging global urban governance
    Kosovac, A ; Pejic, D ; Fernández de Losada, A ; Galceran-Vercher, M (CIDOB, 2021-02-05)
    Everyday urban governance is taking on increasingly global dimensions, leading city governments to expand their alignment with international frameworks and engagement with global processes. While these activities are often driven or coordinated by dedicated international teams within city governments, the global dimensions of urban governance are expanding to include policy teams across local authorities and artners working outside government, such as academic institutions, businesses and philanthropies. This “glocalisation” may be producing new forms of global urban governance operating both within and outside the traditional multilateral system. Drawing on survey data from 47 cities from around the world and a case study on the city of Amsterdam, this chapter explores how new forms of city diplomacy interact with evolving conceptions of multistakeholderism and the impact this may have on the governance of global challenges.
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    Infrared Thermography for Detecting Subsurface Defects of Concrete Structures
    Khan Raja, BN ; Miramini, S ; Duffield, C ; Zhang, L ; Wang, CM ; Ming, C ; Kitipornchai, S (Springer Singapore, 2020-12-23)
    Delamination is one of the serious types of deterioration in reinforced concrete structures. It could cause concrete spalling, exposed steel bars, and ultimately affects the structural integrity of concrete structures. Infrared thermography (IRT) is a non-destructive technique which could potentially detect the delamination by capturing thermal contrast (∆T) on concrete surface caused by the heat flow disruption within the concrete due to subsurface anomalies. However, the optimum time and environmental conditions for IRT data collection are still unclear. In this study, an experimentally validated numerical model was developed to investigate the effect of a range of environmental conditions and defect characteristics on the IRT inspection outcomes. The results show that, under direct solar irradiation, the total heat flux input plays an important role in the development of thermal contrast ∆T instead of flux rate. Furthermore, delamination depth and size are two critical parameters that affect IRT results.