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This work aims to develop a web platform for inspecting roof structures for technical assistance supported by drones and artificial intelligence. The tools used were HTML, CSS and JavaScript languages; Firebase software for infrastructure; and Custom Vision for image processing.

This study adopted the design science research approach, and the main stages for the development of the web platform include (1) creation and validation of the roof inspection checklist, (2) validation of the use of Custom Vision as an image recognition tool, and (3) development of the web platform.

The results of automatic recognition showed a percentage of 77.08% accuracy in identifying pathologies in roof images obtained by drones for technical assistance.

This study contributed to developing a drone-integrated roof platform for visual data collection and artificial intelligence for automatic recognition of pathologies, enabling greater efficiency and agility in the collection, processing and analysis of results to guarantee the durability of the building.

Regular inspection and maintenance is recommended to preserve and sustain built cultural heritage. Systematising inspection processes and knowledge on defects, and providing pictorial guides for evaluating defects is an approach that may facilitate their condition survey. Generating pictorial guides for preliminary visual inspection of Modern Heritage buildings with rendered-painted facade concerning two defects (i.e. crack and efflorescence) is aimed in this study. These guides are thought as aids in determining the defect levels and deciding the necessity of advanced examination and/or maintenance. Analysing briefly the evolution of crack over time in the inspected buildings under environmental conditions of Istanbul (Turkey) is also aimed.

Preliminary guide generation was based mainly on literature survey on defects, and visual data collection from eight Modern Movement examples in Istanbul. The guides were then refined through systematic visual inspection of three buildings among them. Evolution of crack over time was analysed through a second inspection performed after 2.5 years.

Visual inspections showed that crack is the commonest defect occurring mostly on projecting structural members, while efflorescence is less in number. Comparison of cracks' visuals taken in the first and second inspections showed that deterioration process is slow.

Modern heritage buildings usually have some characteristic features, which may sometimes lead to accumulation of defects at certain locations or may lead to formation of certain defects. Generating visual guides as a start for an initiative for a comprehensive defects catalogue particular for Modern Movement buildings in line with associated cultural heritage standards may contribute to their preservation by easing the condition surveys.

This paper highlights a crucial public safety issue due to falling objects from tall residential buildings in Singapore. A systematic façade inspection regime and a system of evaluation of severity for the detection and assessment of potential falling objects from tall buildings are presented.

The research uses qualitative case study approach with 450 tall residential buildings sampled for the study. The common materials, elements, components with high risk of falling objects, the nature and type of the falling, the critical factors affecting the falling, the respective level of severity, and the effectiveness of various diagnostic techniques and protocols, are summarised.

Façade for tall residential buildings in Singapore comprises mainly cementitious materials cast in situ or precast, with fixtures and architectural features, all of which have potential of falling. The common anomalies arising from each material and fixture/features are identified, the causes evaluated and their implications to future design, construction and maintenance analysed.

This study provides original and significant information to a crucial public safety issue, setting design and construction criteria that will serve as a benchmark for new and existing facades, applicable to all cities dominated by tall buildings. The paper presents original figures, checklists and guides as a basis for readers' consideration to use according to their respective unique conditions.

Defects in concrete surfaces are inevitably recurring during construction, which needs to be checked and accepted during construction and completion. Traditional manual inspection of surface defects requires inspectors to judge, evaluate and make decisions, which requires sufficient experience and is time-consuming and labor-intensive, and the expertise cannot be effectively preserved and transferred. In addition, the evaluation standards of different inspectors are not identical, which may lead to cause discrepancies in inspection results. Although computer vision can achieve defect recognition, there is a gap between the low-level semantics acquired by computer vision and the high-level semantics that humans understand from images. Therefore, computer vision and ontology are combined to achieve intelligent evaluation and decision-making and to bridge the above gap.

Combining ontology and computer vision, this paper establishes an evaluation and decision-making framework for concrete surface quality. By establishing concrete surface quality ontology model and defect identification quantification model, ontology reasoning technology is used to realize concrete surface quality evaluation and decision-making.

Computer vision can identify and quantify defects, obtain low-level image semantics, and ontology can structurally express expert knowledge in the field of defects. This proposed framework can automatically identify and quantify defects, and infer the causes, responsibility, severity and repair methods of defects. Through case analysis of various scenarios, the proposed evaluation and decision-making framework is feasible.

This paper establishes an evaluation and decision-making framework for concrete surface quality, so as to improve the standardization and intelligence of surface defect inspection and potentially provide reusable knowledge for inspecting concrete surface quality. The research results in this paper can be used to detect the concrete surface quality, reduce the subjectivity of evaluation and improve the inspection efficiency. In addition, the proposed framework enriches the application scenarios of ontology and computer vision, and to a certain extent bridges the gap between the image features extracted by computer vision and the information that people obtain from images.

Most residential building owners often report problems associated with the plumbing systems. If identified at the early stages, plumbing-related defects can be easily repaired. However, if unnoticed for a long period of time, they could lead to major damages and incur a significant cost to repair. Despite the problems, studies investigating plumbing anomalies and their root causes in residential buildings are limited. This study aims to explore plumbing defects and their potential causes, diagnosis methods and repair techniques in residential buildings.

This research used data collected through an extensive survey of both academic and grey literature. Through the content analysis, plumbing defects and the associated causes have been identified and presented in tabular format.

The study investigated the anomalies and causes in the residential plumbing system under five key sub-systems: water supply system; sanitary plumbing system; roof drainage system; heating, ventilation, air conditioning and gas system; and swimming pool. Accordingly, some of the identified plumbing defects include leakages, corrosion, water penetration, slow drainage and cracks. Damaged pipes, faulty equipment and installations are some of the common causes of the anomalies. Visual inspection, hydrostatic pressure test, thermography, high-tech pipe cameras, infrared cameras, leak noise correlators and leak loggers are techniques used for diagnosing anomalies. Reactive, preventive, predictive and reliability-centred maintenance strategies are identified to control or prevent anomalies.

The findings of this research can be used as a useful tool or guideline for contractors, plumbers, facilities managers and building surveyors to identify and rectify plumbing system-related defects in residential buildings.

This research proposes the study of the pathology in floor finishes, focussing on proactive maintenance strategies to promote the durability of these elements. A model to assess the floorings' performance levels was designed to support decision-making regarding maintenance activities to be carried out, in order to prevent the defects and extend the floors' service life.

The model to measure the floorings' level of performance was developed based on the literature and applied in fieldwork, focussed on visual inspections of floor finishes. Photographs were taken and standardized inspection forms were used to collect the data about the defects in the floors.

This study provides a simple classification model to assess floorings' performance levels, capable to define priorities and help decision-makers in adopting maintenance activities. The model was validated through a case study, which showed that occasionally the choice of the floor finishes is incorrectly made only based on aesthetic criteria and not taking into account the main criteria, i.e. the use of space.

This work contributes to a development of methodologies to assess floorings' performance levels, to study the behavior of different floor finishes, to propose maintenance strategies to improve their performance in service and adopt better solutions in the buildings' design phase.

Building defects are becoming recurrent phenomena in most high-rise buildings. However, little research exists on the analysis of defects in high-rise buildings based on data from real-life projects. This study aims to develop dashboards and models for revealing the most common locations of defects, understanding associations among defects and predicting the rectification periods.

In total, 15,484 defect reports comprising qualitative and quantitative data were obtained from a company that provides consulting services for the construction industry in Victoria, Australia. Data mining methods were applied using a wide range of Python libraries including NumPy, Pandas, Natural Language Toolkit, SpaCy and Regular Expression, alongside association rule mining (ARM) and simulations.

Findings reveal that defects in multi-storey buildings often occur on lower levels, rather than on higher levels. Joinery defects were found to be the most recurrent problem on ground floors. The ARM outcomes show that the occurrence of one type of defect can be taken as an indication for the existence of other types of defects. For instance, in laundry, the chance of occurrence of plumbing and joinery defects, where paint defects are observed, is 88%. The stochastic model built for door defects showed that there is a 60% chance that defects on doors can be rectified within 60 days.

The dashboards provide original insight and novel ideas regarding the frequency of defects in various positions in multi-storey buildings. The stochastic models can provide a reliable point of reference for property managers, occupants and sub-contractors for taking measures to avoid reoccurring defects; so too, findings provide estimations of possible rectification periods for various types of defects.

Construction defects in residential buildings are causing significant impacts both on consumers and the industry. As a consequence, several countries have established new home warranty schemes. However, designing a public policy for domestic building warranties can become a difficult task. In fact, many of these programs in the past have failed, collapsed or gone bankrupt. Therefore, the purpose of the current research is to provide a systematic comparative representation of various active programs internationally.

The methodology relied on a multiple-case study research design. The case selection covered a total of nine jurisdictions with compulsory home warranty programs. Those included Japan, France, United Kingdom, three provinces in Canada (Ontario, British Columbia and Alberta), and three states in Australia (New South Wales, Victoria and Queensland). The study applied a data collection protocol to gather all the evidence in a replicable manner for each individual case. Subsequently, a cross-case analysis was conducted to identify similarities and variations between programs.

The findings unveiled institutional practices that aimed to resolve, compensate, or rectify defects in residential constructions within these countries. The review mostly suggested that every home warranty program presents certain unique characteristics. At the end, this paper proposed an analytical illustration representing the diversification of components adopted by each jurisdiction.

Nowadays, there is still not a consensus within the academic community on what is an optimal solution when conceiving a new home warranty program. Hence, the current study aims to fill this knowledge gap by presenting the plurality of methods employed by several countries. This paper seeks to help policy makers and industry leaders to improve their home warranty scheme based on awareness derived from observations and analyses of what has been accomplished elsewhere in the world.

The existing concept in the building rating scheme especially in developing countries was more focused on the environment, economic, social and culture. The new approach of the classroom condition index (CCI) assessment scheme has its uniqueness in environmental and social aspects because of high building performance in secondary school buildings. The requirements set by the Ministry of Education Malaysia include providing a conducive learning environment, especially for students who are considered as the main users of classrooms in school buildings. Currently, the school administration needs to manually record the condition of the classroom to increase its comfort level. The lack of a structured scheme for classroom assessment makes it difficult for school administration to focus on the overall classroom condition (physical environmental aspect) in the school building. The purpose of this study is to develop a framework for classroom conditions by proposing a CCI assessment scheme for a secondary school building in Malaysia.

Mixed methods were used to carry out the study. The first stage of this study concentrates on developing a system for CCI that relates to physical elements in the classroom. This is done by reviewing the literature on the classroom physical performance, as well as a comparison between several building rating systems locally and abroad. The structure of the proposed CCI scheme is grouped into four main themes, namely, space management quality (SMQ), building condition (BC), indoor environmental quality (IEQ) and teaching and learning quality (TLQ). In addition, there are 12 categories and 23 indicators listed under this theme. The second stage focuses on formulating assessment categories with their relevant performance indicators. This phase undergoes a validation process by conducting a survey (questionnaire) toward the classroom’s main users, which are students and teachers. This is to ensure the accuracy of classroom conditions in the school building. A semi-structured interview was also conducted among building experts. They are building surveyors, building engineers, building designers and building performance experts to support the main findings in the second stage. Relative importance (RI) index approach has been applied to show the indicators weighting and ranking are used as data collections method by using Statistical Package of Social Science software to examine the RI of each category and indicator, respectively.

The findings show that prominent RI and balanced weights are formed from these four main themes. They are SMQ (19.9%), BC (26.6%), IEQ (33.2%) and TLQ (20.3%). The outcome of this study will contribute to a detailed assessment scheme for CCI at the secondary school building. The contribution of the CCI Assessment Scheme is more comprehensive and holistic than the conventional assessment process for BCs. It focuses specifically on classroom space as it is the most important area to achieve a high level of comfort comparing to other spaces in the school building. This holistic approach encompasses all types of classrooms. The concept of one tool fits all is seen as no longer a relevant adaptation in this context. This proposed tool is to be used only for the classroom (as the name CCI implies) and it cannot be used for the other types of spaces, for instance, teacher room, library, meeting room, toilet, canteen and, etc. This is because different spaces represent different physical indicators to be classified. This, in turn, contributes to a conducive learning environment for students in the school.

This paper provides the current information, knowledge and findings related to the classroom physical indicators in developing the assessment scheme for the classroom environment. It will assist both technical and non-technical experts to clarify the current condition of classroom physical performance that ideally may affect the students’ learning environment. The novelty of CCI development is not only on the adopted method but it also includes the ideas on next generation model of rating system that ideally need specific indicators and weighting to be generated into an intelligent computerized system.

The purpose of this study is to explore the suggestions that construction processes could be considerably improved by integrating building information modelling (BIM) with 3D laser scanning technologies. This case study integrated 3D laser point cloud scans with BIM to explore the effects of BIM adoption on ongoing construction project, whilst evaluating the utility of 3D laser scanning technology for producing structural 3D models by converting point cloud data (PCD) into BIM.

The primary data acquisition adopted the use of Trimble X7 laser scanning process, which is a set of data points in the scanned space that represent the scanned structure. The implementation of BIM with the 3D PCD to explore the precision and effectiveness of the construction processes as well as the as-built condition of a structure was precisely captured using the 3D laser scanning technology to recreate accurate and exact 3D models capable of being used to find and fix problems during construction.

The findings indicate that the integration of BIM and 3D laser scanning technology has the tendency to mitigate issues such as building rework, improved project completion times, reduced project cost, enhanced interdisciplinary communication, cooperation and collaboration amongst the project duty holders, which ultimately enhances the overall efficiency of the construction project.

The acquisition of data using 3D laser scanner is usually conducted from the ground. Therefore, certain aspects of the building could potentially disturb data acquisition; for example, the gable and sections of eaves (fascia and soffit) could be left in a blind spot. Data acquisition using 3D laser scanner technology takes time, and the processing of the vast amount of data acquired is laborious, and if not carefully analysed, could result in errors in generated models. Furthermore, because this was an ongoing construction project, material stockpiling and planned construction works obstructed and delayed the seamless capture of scanned data points.

These findings highlight the significance of integrating BIM and 3D laser scanning technology in the construction process and emphasise the value of advanced data collection methods for effectively managing construction projects and streamlined workflows.