Analysing environmental acoustic data through collaboration and automation

Monitoring environmental health is becoming increasingly important as human activity and climate change place greater pressure on global biodiversity. Acoustic sensors provide the ability to collect data passively, objectively and continuously across large areas for extended periods. While these factors make acoustic sensors attractive as autonomous data collectors, there are significant issues associated with large-scale data manipulation and analysis. We present our current research into techniques for analysing large volumes of acoustic data efficiently. We provide an overview of a novel online acoustic environmental workbench and discuss a number of approaches to scaling analysis of acoustic data; online collaboration, manual, automatic and human-in-the loop analysis.

Vertical particle concentration profiles around urban office buildings

Despite its role in determining both indoor and outdoor human exposure to anthropogenic particles, there is limited information describing vertical profiles of particle concentrations in urban environments, especially for ultrafine particles. Furthermore, the results of the few studies performed have been inconsistent. As such, this study aimed to assess the influence of vehicle emissions and nucleation formation on particle characteristics (particle number size distribution-PNSD and PM 2.5 concentration) at different heights around three urban office buildings located next to busy roads in Brisbane, Australia, and place these results in the broader context of the existing literature. Two sets of instruments were used to simultaneously measure PNSD, particle number (PN) and PM 2.5 concentrations, respectively, for up to three weeks at each building. The results showed that both PNSD and PM 2.5 concentration around building envelopes were influenced by vehicle emissions and new particle formation, and that they exhibited variability across the three different office buildings. During nucleation events, PN concentration in size range of <30 nm and total PN concentration increased (7-65% and 5-46%, respectively), while PM 2.5 concentration decreased (36-52%) with height. This study has shown an under acknowledged role for nucleation in producing particles that can affect large numbers of people, due to the high density and occupancy of urban office buildings and the fact that the vast majority of people's time is spent indoors. These findings highlight important new information related to the previously overlooked role of particle formation in the urban atmosphere and its potential effects on selection of air intake locations and appropriate filter types when designing or upgrading mechanical ventilation systems in urban office buildings. The results also serve to better define particle behaviour and variability around building envelopes, which has implications for studies of both human exposure and particle dynamics. © 2012 Author(s).

The future of sustainable building assessment tools : a case study in Australia

Sustainability issues in built environment have attracted an increasingly level of attention from both the general public and the industry. As a result, a number of green building assessment tools have been developed such as the Leadership in Energy and Environmental Design (LEED) and the BRE Environmental Assessment Method (BREEAM), etc. This paper critically reviewed the assessment tools developed in Australian context, i.e. the Green Star rating tools developed by the Green Building Council of Australia. A particular focus is given to the recent developments of these assessment tools. The results showed that the office buildings take the biggest share of Green Star rated buildings. Similarly, sustainable building assessments seem to be more performance oriented which focuses on the operation stage of buildings. In addition, stakeholder engagement during the decision making process is encouraged. These findings provide useful references to the development of next generation of sustainable building assessment tools.

Influence of filtration on I/O particle concentration ratios at urban office buildings

Epidemiological research has consistently shown an association between fine and ultrafine particle concentrations, and increases in both respiratory and cardiovascular morbidity and mortality. These particles, often found in vehicle emissions outside buildings, can penetrate inside via their envelopes and mechanically ventilated systems. Indoor activities such as printing, cooking and cleaning, as well as the movement of building occupants are also an additional source of these particles. In this context, the filtration systems of mechanically ventilated buildings can reduce indoor particle concentrations. Several studies have quantified the efficiency of dry-media and electrostatic filters, but they mainly focused on the particle size range > 300 nm. Some others studied ultrafine particles but their investigations were conducted in laboratories. At this point, there is still only limited information on in situ filter efficiency and an incomplete understanding of filtration influence on I/O ratios of particle concentrations. To help address these gaps in knowledge and provide new information for the selection of appropriate filter types in office building HVAC systems, we aimed to: (1) measure particle concentrations at up and down stream flows of filter devices, as well as outdoor and indoor office buildings; (2) quantify efficiency of different filter types at different buildings; and (3) assess the impact of these filters on I/O ratios at different indoor and outdoor source operation scenarios.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular, and time-varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper evaluates a number of matching techniques for possible use in a stereo vision sensor for mining automation applications. Area-based techniques have been investigated because they have the potential to yield dense maps, are amenable to fast hardware implementation, and are suited to textured scenes. In addition, two nonparametric transforms, namely, rank and census, have been investigated. Matching algorithms using these transforms were found to have a number of clear advantages, including reliability in the presence of radiometric distortion, low computational complexity, and amenability to hardware implementation.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. The objective is to produce a stereo vision sensor suited to close-range scenes consisting primarily of rocks. This sensor should be able to produce a dense depth map within real-time constraints. Speed and robustness are of foremost importance for this investigation. A number of area based matching metrics have been implemented, including the SAD, SSD, NCC, and their zero-meaned versions. The NCC and the zero meaned SAD and SSD were found to produce the disparity maps with the highest proportion of valid matches. The plain SAD and SSD were the least computationally expensive, due to all their operations taking place in integer arithmetic, however, they were extremely sensitive to radiometric distortion. Non-parametric techniques for matching, in particular, the rank and the census transform, have also been investigated. The rank and census transforms were found to be robust with respect to radiometric distortion, as well as being able to produce disparity maps with a high proportion of valid matches. An additional advantage of both the rank and the census transform is their amenability to fast hardware implementation.

Suitability of non-parametric stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper assesses the suitability of a number of matching techniques for use in a stereo vision sensor for close range scenes consisting primarily of rocks. These include traditional area-based matching metrics, and non-parametric transforms, in particular, the rank and census transforms. Experimental results show that the rank and census transforms exhibit a number of clear advantages over area-based matching metrics, including their low computational complexity, and robustness to certain types of distortion.

Fast and robust stereo matching algorithms for mining automation

The mining environment, being complex, irregular and time varying, presents a challenging prospect for stereo vision. For this application, speed, reliability, and the ability to produce a dense depth map are of foremost importance. This paper evaluates a number of matching techniques for possible use in a stereo vision sensor for mining automation applications. Area-based techniques have been investigated because they have the potential to yield dense maps, are amenable to fast hardware implementation, and are suited to textured scenes. In addition, two non-parametric transforms, namely, the rank and census, have been investigated. Matching algorithms using these transforms were found to have a number of clear advantages, including reliability in the presence of radiometric distortion, low computational complexity, and amenability to hardware implementation.

A waste management system for small and medium enterprises engaged in office building retrofit projects

Waste management and minimisation is considered to be an important issue for achieving sustainability in the construction industry. Retrofit projects generate less waste than demolitions and new builds, but they possess unique features and require waste management approaches that are different to traditional new builds. With the increasing demand for more energy efficient and environmentally sustainable office spaces, the office building retrofit market is growing in capital cities around Australia with a high level of refurbishment needed for existing aging properties. Restricted site space and uncertain delivery process in these projects make it a major challenge to manage waste effectively. The labour-intensive nature of retrofit projects creates the need for the involvement of small and medium enterprises (SMEs) as subcontractors in on-site works. SMEs are familiar with on-site waste generation but are not as actively motivated and engaged in waste management activities as the stakeholders in other construction projects in the industry. SMEs’ responsibilities for waste management in office building retrofit projects need to be identified and adapted to the work delivery processes and the waste management system supported by project stakeholders. The existing literature provides an understanding of how to manage construction waste that is already generated and how to increase the waste recovery rate for office building retrofit projects. However, previous research has not developed theories or practical solutions that can guide project stakeholders to understand the specific waste generation process and effectively plan for and manage waste in ongoing project works. No appropriate method has been established for the potential role and capability of SMEs to manage and minimise waste from their subcontracting works. This research probes into the characteristics of office building retrofit project delivery with the aim to develop specific tools to manage waste and incorporate SMEs in this process in an appropriate and effective way. Based on an extensive literature review, the research firstly developed a questionnaire survey to identify the critical factors of on-site waste generation in office building retrofit projects. Semi-structured interviews were then utilised to validate the critical waste factors and establish the interrelationships between the factors. The interviews served another important function of identifying the current problems of waste management in the industry and the performance of SMEs in this area. Interviewees’ opinions on remedies to the problems were also collected. On the foundation of the findings from the questionnaire survey and semi-structured interviews, two waste planning and management strategies were identified for the dismantling phase and fit-out phase of office building retrofit projects, respectively. Two models were then established to organize SMEs’ waste management activities, including a work process-based integrated waste planning model for the dismantling phase and a system dynamics model for the fit-out phase. In order to apply the models in real practice, procedures were developed to guide SMEs’ work flow in on-site waste planning and management. In addition, a collaboration framework was established for SMEs and other project stakeholders for effective waste planning and management. Furthermore, an organisational engagement strategy was developed to improve SME waste management practices. Three case studies were conducted to validate and finalise the research deliverables. This research extends the current literature that mostly covers waste management plans in new build projects, by presenting the knowledge and understanding of addressing waste problems in retrofit projects. It provides practical tools and guidance for industry practitioners to effectively manage the waste generation processes in office building retrofit projects. It can also promote industry-level recognition of the role of SMEs and their performance in on-site waste management.

Towards persistent indoor appearance-based localization, mapping and navigation using CAT-Graph

The challenge of persistent appearance-based navigation and mapping is to develop an autonomous robotic vision system that can simultaneously localize, map and navigate over the lifetime of the robot. However, the computation time and memory requirements of current appearance-based methods typically scale not only with the size of the environment but also with the operation time of the platform; also, repeated revisits to locations will develop multiple competing representations which reduce recall performance. In this paper we present a solution to the persistent localization, mapping and global path planning problem in the context of a delivery robot in an office environment over a one-week period. Using a graphical appearance-based SLAM algorithm, CAT-Graph, we demonstrate constant time and memory loop closure detection with minimal degradation during repeated revisits to locations, along with topological path planning that improves over time without using a global metric representation. We compare the localization performance of CAT-Graph to openFABMAP, an appearance-only SLAM algorithm, and the path planning performance to occupancy-grid based metric SLAM. We discuss the limitations of the algorithm with regard to environment change over time and illustrate how the topological graph representation can be coupled with local movement behaviors for persistent autonomous robot navigation.

Green office interiors in Australia : lessons learnt

In 2003, the Green Building Council of Australia (GBCA) launched their Green Star rating tools for various types of buildings in order to promote green building practice in Australia. Of these, the Green Star-Office Interior rating tool is designed for building owners, tenants and interior designers to assess the environmental impact of an interior fitout. It covers a number of categories, including Management, Indoor Environment Quality, Energy, Transport, Water, Materials, Land Use and Ecology, Emissions, and Innovation. This paper reviews the usage of the Green Star system in Australian office tenancy fitouts and the potential challenges associated with Green Star-Office Interior implementation. This involves the analysis of score sheets of 66 office interior projects across Australia that achieved Green Star certification. The percentage of green star points obtained within each category and sub-categories (credits) for each project are investigated to illustrate the achievement of credits. The results show that Emission-related credits and Innovation related credits are the easiest and most difficult respectively to obtain. It is also found that 6 Green Star office interior projects perform especially better in the categories of Energy and Ecology than 4 and 5 Star projects. The investigation of point frequency in each category provides prospective Green Star applicants with insights into credit achievement for future projects.

Assessment of precision timing and real-time data networks for digital substation automation

This project researched the performance of emerging digital technology for high voltage electricity substations that significantly improves safety for staff and reduces the potential impact on the environment of equipment failure. The experimental evaluation used a scale model of a substation control system that incorporated real substation control and networking equipment with real-time simulation of the power system. The outcomes confirm that it is possible to implement Ethernet networks in high voltage substations that meet the needs of utilities; however component-level testing of devices is necessary to achieve this. The assessment results have been used to further develop international standards for substation communication and precision timing.