Automated 3D Structure Inference of Civil Infrastructure Using a Stereo Camera Set

The commercial far-range (>10m) infrastructure spatial data collection methods are not completely automated. They need significant amount of manual post-processing work and in some cases, the equipment costs are significant. This paper presents a method that is the first step of a stereo videogrammetric framework and holds the promise to address these issues. Under this method, video streams are initially collected from a calibrated set of two video cameras. For each pair of simultaneous video frames, visual feature points are detected and their spatial coordinates are then computed. The result, in the form of a sparse 3D point cloud, is the basis for the next steps in the framework (i.e., camera motion estimation and dense 3D reconstruction). A set of data, collected from an ongoing infrastructure project, is used to show the merits of the method. Comparison with existing tools is also shown, to indicate the performance differences of the proposed method in the level of automation and the accuracy of results.

Risk-based approaches to sustainability in civil engineering

Infrastructure project sustainability assessment typically entails the use of specialised assessment tools to measure and rate project performance against a set of criteria. This paper looks beyond the prevailing approaches to sustainability assessments and explores sustainability principles in terms of project risks and opportunities. Taking a risk management approach to applying sustainability concepts to projects has the potential to reconceptualise decision structures for sustainability from bespoke assessments to becoming a standard part of the project decisionmaking process. By integrating issues of sustainability into project risk management for project planning, design and construction, sustainability is considered within a more traditional business and engineering language. Currently, there is no widely practised approach for objectively considering the environmental and social context of projects alongside the more traditional project risk assessments of time, cost and quality. A risk-based approach would not solve all the issues associated with existing sustainability assessments but it would place sustainability concerns alongside other key risks and opportunities, integrating sustainability with other project decisions.

Designing for resilience: Using a Delphi study to identify resilience issues for hospital designs in a changing climate

Hospitals are facing a triple challenge - meeting mandatory climate change targets and refurbishing aging infrastructure while simultaneously providing quality of care. With the potential of more frequent disruptive weather events, a UK government-funded project was launched in 2009 to investigate practical strategies for the National Health Service to increase its resilience to climate change. This paper presents the process of defining resilience by using the Delphi method and demonstrates its applicability within healthcare design. A Delphi survey is nearing completion which has determined the significant resilience issues and temperature ranges for ideal and critical conditions. Our preliminary findings identified six priorities that lead towards increasing resilience. Using the Delphi method can be a useful tool in clarifying the focus for healthcare design considerations. Copyright © 2002-2012 The Design Society. All rights reserved.

Development of modelling method selection tool for health services management: From problem structuring methods to modelling and simulation methods

Background: There is an increasing recognition that modelling and simulation can assist in the process of designing health care policies, strategies and operations. However, the current use is limited and answers to questions such as what methods to use and when remain somewhat underdeveloped. Aim. The aim of this study is to provide a mechanism for decision makers in health services planning and management to compare a broad range of modelling and simulation methods so that they can better select and use them or better commission relevant modelling and simulation work. Methods. This paper proposes a modelling and simulation method comparison and selection tool developed from a comprehensive literature review, the research team's extensive expertise and inputs from potential users. Twenty-eight different methods were identified, characterised by their relevance to different application areas, project life cycle stages, types of output and levels of insight, and four input resources required (time, money, knowledge and data). Results: The characterisation is presented in matrix forms to allow quick comparison and selection. This paper also highlights significant knowledge gaps in the existing literature when assessing the applicability of particular approaches to health services management, where modelling and simulation skills are scarce let alone money and time. Conclusions: A modelling and simulation method comparison and selection tool is developed to assist with the selection of methods appropriate to supporting specific decision making processes. In particular it addresses the issue of which method is most appropriate to which specific health services management problem, what the user might expect to be obtained from the method, and what is required to use the method. In summary, we believe the tool adds value to the scarce existing literature on methods comparison and selection. © 2011 Jun et al.

Visual pattern recognition models for remote sensing of civil infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Visual Pattern Recognition Models for Remote Sensing of Civil Infrastructure

As-built models have been proven useful in many project-related applications, such as progress monitoring and quality control. However, they are not widely produced in most projects because a lot of effort is still necessary to manually convert remote sensing data from photogrammetry or laser scanning to an as-built model. In order to automate the generation of as-built models, the first and fundamental step is to automatically recognize infrastructure-related elements from the remote sensing data. This paper outlines a framework for creating visual pattern recognition models that can automate the recognition of infrastructure-related elements based on their visual features. The framework starts with identifying the visual characteristics of infrastructure element types and numerically representing them using image analysis tools. The derived representations, along with their relative topology, are then used to form element visual pattern recognition (VPR) models. So far, the VPR models of four infrastructure-related elements have been created using the framework. The high recognition performance of these models validates the effectiveness of the framework in recognizing infrastructure-related elements.

Micro-measurement and monitoring system for ageing underground infrastructure (Underground M3)

Advances in the development of computer vision, miniature Micro-Electro-Mechanical Systems (MEMS) and Wireless Sensor Network (WSN) offer intriguing possibilities that can radically alter the paradigms underlying existing methods of condition assessment and monitoring of ageing civil engineering infrastructure. This paper describes some of the outcomes of the European Science Foundation project "Micro-Measurement and Monitoring System for Ageing Underground Infrastructures (Underground M3)". The main aim of the project was to develop a system that uses a tiered approach to monitor the degree and rate of tunnel deterioration. The system comprises of (1) Tier 1: Micro-detection using advances in computer vision and (2) Tier 2: Micro-monitoring and communication using advances in MEMS and WSN. These potentially low-cost technologies will be able to reduce costs associated with end-of-life structures, which is essential to the viability of rehabilitation, repair and reuse. The paper describes the actual deployment and testing of these innovative monitoring tools in tunnels of London Underground, Prague Metro and Barcelona Metro. © 2012 Taylor & Francis Group.

The role of infrastructure in improving human settlements

This paper considers how the provision of integrated household-level infrastructure – particularly water and environmental sanitation (including water supply, sewerage, roads, storm drainage and solid waste management) –can play a leading role in improving the conditions in slum settlements. Around 700 socio-economic interviews were carried out in India and South Africa to investigate an innovative approach called slum networking, which sees the strong correlation between slum locations and drainage paths as an opportunity for improving the wider urban environment. This recognition allows resources to be mobilised locally, thereby removing the need for external aid funding. The evidence from the 700 families shows that communities perceive water and sanitation inputs to be their top priority and are willing to contribute to the costs. If slum upgrading is led with access to integrated water and environmental sanitation at household level with community contributions to the cost of infrastructure, then slum communities subsequently invest considerably greater sums in improved housing and education, with longer term contributions to poverty alleviation, improvements in health and literacy and an increase in disposable incomes.

Analysis of structural health monitoring data from hammersmith flyover

There has recently been considerable research published on the applicability of monitoring systems for improving civil infrastructure management decisions. Less research has been published on the challenges in interpreting the collected data to provide useful information for engineering decision makers. This paper describes some installed monitoring systems on the Hammersmith Flyover, a major bridge located in central London (United Kingdom). The original goals of the deployments were to evaluate the performance of systems for monitoring prestressing tendon wire breaks and to assess the performance of the bearings supporting the bridge piers because visual inspections had indicated evidence of deterioration in both. This paper aims to show that value can be derived from detailed analysis of measurements from a number of different sensors, including acoustic emission monitors, strain, temperature and displacement gauges. Two structural monitoring systems are described, a wired system installed by a commercial contractor on behalf of the client and a research wireless deployment installed by the University of Cambridge. Careful interpretation of the displacement and temperature gauge data enabled bearings that were not functioning as designed to be identified. The acoustic emission monitoring indicated locations at which rapid deterioration was likely to be occurring; however, it was not possible to verify these results using any of the other sensors installed and hence the only method for confirming these results was by visual inspection. Recommendations for future bridge monitoring projects are made in light of the lessons learned from this monitoring case study. © 2014 This work is made available under the terms of the Creative Commons Attribution 4.0 International license,.