Infrastructure Maintenance Research Articles

Factors Affecting the Performance of the Community-Based Water Supply Organisations (CBWSOs) in Katavi Districts, Tanzania

This study assessed the factors affecting the Performance of Community-Based Water Supply Organisations (CBWSOs) in managing water supply schemes in Katavi rural areas. An inductive approach and exploratory design were employed in this study. The study population comprised 48 respondents, comprising the region's management team and supervisory board members of selected CBWSOs. Data was collected through one on one In-depth interviews, field observation and literature reviews. The findings revealed firstly, financial management was identified as a critical aspect, emphasising the importance of community participation in the collection of funds. Secondly, Regular infrastructure maintenance is essential for water supply reliability. Thirdly Positive political influence involves securing funding and resources, creating a supportive regulatory environment, promoting community engagement, and advocating for the interests of CBWSOs. In contrast, negative political influence hinders decision-making processes and neglects the responsibilities of supporting and overseeing CBWSOs. Lastly, community awareness was identified as a significant factor. Community participation in the collection of funds fosters financial sustainability, a sense of ownership, responsible resource utilisation, and transparency. Based on these findings, some of the recommendations and policy implications proposed include supporting financial sustainability, establishing a regulatory framework for infrastructure maintenance, minimising negative political interference, promoting community awareness and participation, providing capacity building and implementing a monitoring and evaluation framework.

Stability prediction of muddy submarine channel slope based on sub-bottom profile acoustic images and transfer learning

This research addresses the challenging task of predicting the stability of muddy submarine channel slopes, crucial for ensuring safe port operations. Traditional methods falter due to the submerged nature of these channels, impacting navigation and infrastructure maintenance. The proposed approach integrates sub-bottom profile acoustic images and transfer learning to predict slope stability in Lianyungang Port. The study classifies slope stability into four categories: stable, creep, expansion, and unstable based on oscillation amplitude and sound intensity. Utilizing a sub-bottom profiler, acoustic imagery is collected, which is then enhanced through Gabor filtering. This process generates source data to pre-train Visual Geometry Group (VGG)16 neural network. This research further refines the model using targeted data, achieving a 97.92% prediction accuracy. When benchmarked against other models and methods, including VGG19, Inception-v3, Densenet201, Decision Tree (DT), Naive Bayes (NB), Support Vector Machine (SVM), and an unmodified VGG16, this approach exhibits superior accuracy. This model proves highly effective for real-time analysis of submarine channel slope dynamics, offering a significant advancement in marine safety and operational efficiency.

Infrastructural insecurity: Geopolitics in the standardization of telecommunications networks

This article argues that the production and maintenance of “infrastructural insecurity” is an inherent part of the process of the standardization of telecommunication networks. Infrastructural insecurity is the outcome of intentional practices during the production, standardization, and maintenance of communication infrastructures that leave end-users vulnerable to attacks that benefit particular actors. We ground this analysis in the qualitative and quantitative exploration of the responses to the disclosure of three fundamental security vulnerabilities in telecommunications networks. To research the shaping of communication and infrastructure architectures in the face of insecurities, we develop a novel approach to the study of Internet governance and standard-setting processes that leverages web scraping and computer-assisted document set discovery software tools combined with document analysis. This is an important contribution because it problematizes the process of standardization and asks fundamental questions about the adequacy and legitimacy of the process and procedures of standardization, its participants, and its institutions.

An Integrated Data-Driven System for Digital Bridge Management

Relational databases are established and widespread tools for storing and managing information. The efficient collection of information in a database appears to be a promising solution for bridge management (BM), thus facilitating the digital transition. The Italian regulatory framework on infrastructure operation and maintenance (O&M) is complex and is constantly being updated. The current plan for implementing its guidelines envisages that infrastructure managers, also on a regional scale, equip themselves with their own digital database for BM. Within this context, this research proposes an integrated methodology that collects information derived from project documentation, in situ inspections, digital surveys, and monitoring and field tests in a queryable database for digitalising, georeferencing, and creating models of many bridges. Structured query language (SQL) statements are used to efficiently export specific shared information, enabling network cross-analysis. Furthermore, the database represents the source of a geographic information system (GIS) catalogue and the basis for deriving models for building information modelling (BIM). The methodology focuses on the infrastructural context of the Lazio region, Italy, the first beneficiary of the research.

TunGPR: Enhancing data-driven maintenance for tunnel linings through synthetic datasets, deep learning and BIM

Non-destructive Testing (NDT) techniques and data-driven technologies are increasingly applied in underground infrastructure maintenance, which can facilitate predictive monitoring for informed decision-making. Ground Penetrating Radar (GPR) is extensively utilised in rapid condition assessment of tunnel linings, particularly for detecting defects that lead to unforeseen changes of dielectric properties of materials. In this paper, a prototyped framework is proposed, namely TunGPR, for GPR-based tunnel lining assessment by incorporating Building Information Modelling (BIM), synthetic database and deep learning-enabled interpretation. The first module integrates laser-scanned point clouds and GPR Scan-to-BIM of tunnel lining with geological model. Subsequently, interoperability is achieved between the geo-integrated BIM and GPR simulation software. From the dielectric model retrieved from the BIM model, a database is established, considering a variety of condition combinations (i.e., voids, cavities, delamination, and water intrusion) leveraging domain randomisation and Finite-Difference Time-Domain (FDTD) modelling, as well as monitored field data. The dataset is then fed into the diagnostic module underpinned by a dual-rotational Convolutional Neural Network (CNN) that is customised to enhance accuracy and automation of hyperbola detection. Lastly, a preliminary risk assessment matrix is implemented into the BIM model for data management and action prioritisation. These efforts serve as an initial step to validate the feasibility and effectiveness of the GPR-enabled data-driven maintenance for tunnel linings in a BIM-centred framework.

A data-driven prioritisation framework to mitigate maintenance impact on passengers during metro line operation

The application of artificial intelligence (AI) techniques may lead to significant improvements in different aspects of rail sector. Considering asset management and maintenance, AI can improve data analysis and asset status forecasting and decision-making processes, fostering predictive and prescriptive maintenance strategies. A prescriptive approach should be able to predict future scenarios as well as to suggest a course of actions. Nevertheless, the decision-making in rail asset management is often based on the classical asset-oriented approach, concentrating on the function of the asset itself as a main key performance indicator (KPI), whereas a user-oriented approach could lead to improved performance in terms of level of service. This paper is aimed at integrating the passengers’ perspective in the decision-making process for asset management to mitigate the impact that service interruptions may have on the final users. A data-driven prioritisation framework is developed to prioritise maintenance interventions taking into account asset status and criticality. In particular, a three-step approach is proposed, which focuses on the analysis of passenger data to evaluate the failure impact on the service, the analysis of alarms and anomalies to evaluate the asset status, and the suggestion of maintenance interventions. The proposed approach is applied to the maintenance of the metro line M5 in the Italian city of Milan. Results show the usefulness of the proposed approach to support infrastructure managers and maintenance operators in making decisions regarding the priority of maintenance activities, reducing the risk of critical failures and service interruptions.

The mediating role of technological vigilance between IT infrastructure and AIS efficiency

This study aimed to examine the mediating role of technological vigilance within commercial banks in Jordan in supporting the relationship between information technology (IT) infrastructure (hardware, software, network, security, maintenance, information quality, and interoperability) and Accounting Information Systems (AIS) efficiency. AMOS and Statistical Package of Social Science (SPSS) were used in order to screen and analyze the data collected from 161 financial and accounting managers within commercial banks in Jordan. The results indicated that technological vigilance mediates the relationship between IT infrastructure and AIS efficiency; it is based on the idea that the use of IT infrastructure, such as networks, hardware, and software to support business processes has a direct impact on the efficiency of AIS. Accordingly, this study recommends focusing on the role of IT infrastructure and the mediating role of technological vigilance in achieving AIS efficiency in Jordanian commercial banks. The originality of the study lies in its ability to address the role of IT infrastructure in increasing AIS efficiency, as well as its focus on the mediating role that technological vigilance. The study also has a novel contribution to the field by exploring the interconnectedness between technology, operational efficiency, and watchfulness. Through an in-depth analysis of empirical case studies, a deeper understanding of the interplay between these three variables was presented.

Digital curation and long-term digital preservation in libraries

For over twenty years public institutions and foundations committed in cultural heritage curation and preservation worked up methodologies, strategies and techniques for long-term digital preservation of digital resources. Thanks to a relevant number of initiatives and services carried on by international institutions and specialized agencies, public and private libraries reached a high level of awareness in this field which requires continuous adaptation due to the constant evolution of publishing industry and the rapid emergence of Open Science. After a quick review of digital preservation milestones, this article looks at some emerging trends and issues which characterize the constant transformation of digital preservation landscape. Dynamic generated digital contents and Open Science to fulfil findability, accessibility, interoperability and reuse (FAIR) of digital assets are engaging new challenges for existing digital preservation services. Digital curation and digital preservation are deeply merged and proceed in parallel to assure long-term usage of digital resources and data. How to select and deploy digital preservation platforms is another complex area where Cloud services can offer the opportunity to reduce the costs of technical infrastructures maintenance and management. Policy and decision making institutional levels need more awareness to draw up digital preservation strategies and to activate services to assure digital contents and data long-term access and reuse. Finally the paper suggests to promote “digital preservation by design” as a new base rule to be applied since the conception of every project and initiative in the cultural heritage, scientific and academic contexts.

Povandeninio roboto taikymas vandens transporto ir infrastruktūros povandeninės dalies techninės apžiūros duomenų bazės sukūrimui

This paper examines the application of the CHASING M2 PRO MAX underwater robot for the creation of databases for the technical inspection of the underwater components of water transport vehicles and their infrastructure. The paper defines and analyzes specific areas of application for the underwater robot, detailing the characteristics of its control systems that are essential for efficiently and accurately collecting data on water transport vehicles and underwater port infrastructure. Special attention is given to the operations of the technical inspection process of watercraft and port infrastructure. The study analyzes how this robot can improve the data collection process and inspection efficiency. Finally, the underwater inspection process is modeled, demonstrating how the CHASING M2 PRO MAX can be integrated into existing procedures to optimize data collection and analysis. This research opens new possibilities in the field of water transport safety and infrastructure maintenance, providing valuable insights into the application of underwater robot technologies. Keywords: CHASING M2 PRO MAX, ROV, technical inspection of ships and port infrastructure, remotely operated underwater drone, technical inspection, hull inspection, IMO, SQL.

Perancangan Aplikasi Layanan Pengaduan Kerusakan Jalan Berbasis Android

The android-based road damage complaint service application is a technological innovation that aims to improve the reporting and management of road damage. In the era of digitalization, people expect a lot from public services, especially infrastructure. However, the reporting process is still often done manually, causing weaknesses such as data loss, slow response and ineffectiveness. This application is an effective solution to overcome these problems. Users can easily report road damage through their Android devices. The benefit of this application is the ability to know the level of road damage in each report, making it easier for the authorities to determine the priority of handling. In addition, the app allows users to provide a detailed description of the damage, upload photos as evidence, and add additional relevant information. The app provides a complete and easy-to-fill form, making the reporting process more efficient.Once the report is submitted, users will receive a confirmation of report receipt to track the status of the report. The relevant agencies will utilize the app as a tool to manage incoming complaints, promptly responding to reports and processing them based on the priority and type of damage reported. Therefore, this application brings significant changes by improving public services and ensuring better infrastructure maintenance.

Using Emr In A Corporate Hospital: Healthcare Providers Perspective From Bangladesh

Background: An Electronic Medical Record (EMR) is an essential tool for delivering high-quality healthcare in a hospital. In recent years, hospitals have increased their investment in EMRs to improve the level of integrated management of information. The purpose of this study was to explore the perspectives of using EMR among healthcare providers (HCPs) in a corporate hospital in Bangladesh.
 Methods: This cross-sectional study was conducted among 153 HCPs (doctors, nurses, lab technicians, drug dispensers, billing managers, and administrative personnel) who have access to EMR and working in a selected corporate hospital of Dhaka city. The study period was January to December 2019. HCPs were selected by convenience sampling technique. Data were collected by face-to-face interview using semi structured questionnaire. Data analysis was done by IBM SPSS software. Ethical issues were maintained strictly.
 Result: Study revealed that 59.5% HCPs were in the age group of 18-29 years with the mean age being 29.26 (±7.58) years. Only 32.7% HCPs had previous experience of using this type of software before working in the current hospital and 62.7% got technical training on EMR within the current hospital. The majority (81.7%) of the HCPs found that the technical training was effective for using the EMR software. The difficulty of using EMR was significantly associated with the age (p<0.001), gender (p<0.001), professional status (p<0.001) and highest level of education (p<0.001) of the HCPs. HCPs ability to overcome job related challenges was significantly associated with the professional status of them (p<0.001). HCPs perception regarding effectiveness of EMR was found significantly associated with their place of technical training (p=0.004) and duration of the training (p=0.012).
 Conclusion: EMR can be a helpful tool for the health service providers to provider health services at the corporate hospitals. Digital literacy need to be increased among the HCPs to ensure effective use of EMRs. Regular maintenance and upgrades of the technology infrastructure are necessary for advanced record-keeping and quality service.
 JOPSOM 2021; 41(2):12-19

Remote area nurses' experiences of workplace safety in very remote primary health clinics: A qualitative study.

To explore Remote Area Nurses' experiences of the implementation of workplace health and safety policies and risk mitigation strategies in Australian very remote primary health clinics. This qualitative study used online semi-structured interviews, with participants purposively sampled to maximize variation in work location and service type. Data were analysed using a reflexive thematic analysis approach. Coding was carried out inductively, with NVivo 12 aiding data management. The interviews were conducted from 24 Februrary 2021 to 06 March 2021 with Remote Area Nurses from very remote primary health clinics in Australia. Fifteen Remote Area Nurses participated in the study. Thematic analysis revealed varied approaches to workplace safety among the different health services and regions. While the spread of 'never alone' policies in many clinics addressed one of the significant risks faced by Remote Area Nurses, gaps remained even for hazards specifically highlighted in existing work health and safety legislation. Meaningful collaboration with staff and the community, local orientation, preparation for the role and providing quality care were protective factors for staff safety. Understaffing, unsafe infrastructure and inadequate equipment were common concerns among Remote Area Nurses. Health services need to prioritize workplace safety and take a continuous quality improvement approach to its implementation. This will include ensuring safety strategies are appropriate for the local context, improving infrastructure maintenance, and establishing sustainable second responder systems such as a pool of drivers with local knowledge. Poor personal safety contributes to burnout and high turnover of staff. Nurses' insights into the barriers and enablers of current workplace safety strategies will aid policymakers and employers in future improvements. COREQ reporting guidelines were followed. A panel of six Remote Area Nurses collaborated in the development of this project.

An efficient pavement distress detection scheme through drone–ground vehicle coordination

Efficient road maintenance is imperative for infrastructure longevity and safety. Conventional ground vehicle-based methods for detecting pavement distress, however, encounter limitations in practice when dealing with complex road structures. Drones, endowed with greater spatial freedom, can access road segments that are hard-to-reach to ground vehicles, thereby enhancing detection efficiency and expanding detection coverage. By harnessing the complementary strengths of both detection modalities, we propose a scheme that capitalizes on the cooperative coordination of drones and ground vehicles for effective pavement distress detection. Our proposed scheme is evaluated using realistic road networks in practice. Results reveal that the coordinated detection scheme strikes a favorable balance between fixed device-related expenses and detection efficiency. This scheme offers promising policy implications, streamlining maintenance across diverse road networks and meeting extensive infrastructure needs, offering policymakers an efficient and viable scheme for road infrastructure maintenance.

RoBétArmé Project: Human-robot collaborative construction system for shotcrete digitization and automation through advanced perception, cognition, mobility and additive manufacturing skills.

The importance of construction automation has grown worldwide, aiming to deliver new machineries for the automation of roads, tunnels, bridges, buildings and earth-work construction. This need is mainly driven by (i) the shortage and rising costs of skilled workers, (ii) the tremendous increased needs for new infrastructures to serve the daily activities and (iii) the immense demand for maintenance of ageing infrastructure. Shotcrete (sprayed concrete) is increasingly becoming popular technology among contractors and builders, as its application is extremely economical and flexible as the growth in construction repairs in developed countries demand excessive automation of concrete placement. Even if shotcrete technology is heavily mechanized, the actual application is still performed manually at a large extend. RoBétArméEuropean project targets the Construction 4.0 transformation of the construction with shotcrete with the adoption of breakthrough technologies such as sensors, augmented reality systems, high-performance computing, additive manufacturing, advanced materials, autonomous robots and simulation systems, technologies that have already been studied and applied so far in Industry 4.0. The paper at hand showcases the development of a novel robotic system with advanced perception, cognition and digitization capabilities for the automation of all phases of shotcrete application. In particular, the challenges and barriers in shotcrete automation are presented and the RoBétArmésuggested solutions are outlined. We introduce a basic conceptual architecture of the system to be developed and we demonstrate the four application scenarios on which the system is designated to operate.

The Soil-Arching Effect in Pile-Supported Embankments: A Review

Pile-supported embankments are widely used in foundation treatments, owing to their safety, efficient construction, and economy. The soil-arching effect is a key load-transferring mechanism in a pile-supported embankment, and it reduces the even settlement on the embankment surface. In recent years, researchers and engineers have conducted extensive research on the soil-arching phenomenon in pile-supported embankments. This paper reviews relevant studies on the effect of soil arching in pile-supported embankments in order to better understand the mechanism and influencing factors of the distribution of the arching effect. First, the development history of the practice and theory related to pile-supported embankments is discussed. This is followed by a review of theoretical studies on the soil-arching effect, load distribution and soil deformation on pile-supported embankments (with and without geogrid reinforcement), and structures and factors influencing soil arching. The results of these studies are summarized, and finally, topics for future research are suggested, providing references for the design and maintenance of civil infrastructure.

Law and democracy in the globalisation of infrastructure as an asset class

ABSTRACT In 2018, the G20 endorsed the ‘Roadmap to Infrastructure as an Asset Class’. This document crystallizes a roaring policy agenda focused on transforming ‘infrastructure’ into a homogeneous, tradeable investment opportunity, attractive to global financial markets. Although the Roadmap is formally a mere policy blueprint, this article studies it as a legal document—one whose purpose is to code infrastructures into capital. Specifically, the article makes three claims, two analytical and one normative. First, that the Roadmap’s way of attracting investors ultimately consists in shielding the decision-making processes related to the design and maintenance of infrastructures from democratic interference. Second, that these restrictions are enforced through global governance mechanisms that push the relevant decision-making authority from the national to the global. And third, that the Roadmap’s agenda is problematic from a democratic standpoint, because it disempowers those who should have a say over the development and maintenance of these infrastructures.

Self-Help Provision and Maintenance of Housing Infrastructure in Akure, Nigeria

Aim/Purpose: This study examined self-help provision and maintenance of infrastructure in two communities in Akure, to identify the current modes and nature of infrastructure development in those communities. Background: Community participation is the involvement of people in community projects to solve their own problems. In developing countries like Nigeria, communities have resorted to self-help efforts to provide and maintain the infrastructural facilities in their neighbourhoods due to government neglect. This has negative effects on the state of the infrastructure due to meagre resources and technical know-how. Methodology: A cross-sectional survey of 198 households was conducted in the study area. Data were collected through questionnaire survey and physical observations while the data was subjected to Single-Factor Descriptive Analysis. Findings: Findings reveal poor state of infrastructure, pervasive self-help provision and maintenance of infrastructure in the study areas and that the conditions in the two communities are similar. Impact on Society: The study recommended that the authorities responsible for infrastructure provision and maintenance in the study area should live up to their responsibilities, while ensuring that the community members are involved in this process.

Digitalization of education in the context of personnel training for the maintenance of the Smart city infrastructure

Digitalization has given rise to human-accessible creations such as online textbooks, cloud-based learning systems, virtual laboratories, personal identification of individual students and open educational content, which are becoming a reality for education in Kyrgyzstan. The digitalization that the country has undertaken is one of the main trends in this area. A structural-logical analysis of the creation of a digital educational environment and a review of the literature defined the objectives of this study. One important change in the educational system in Kyrgyzstan is the project Digital CASA - Kyrgyz Republic, part of the regional integration program Digital CASA. This article identified the main factors in the creation of a digital educational environment at the university, which should assist in enhancing the quality of the Kyrgyz educational system. The article presents the projected, planned and erected creations of man and society, for digitalization and for the maintenance of the infrastructure of the Smart city.

An Ensemble Approach for Robust Automated Crack Detection and Segmentation in Concrete Structures.

To prevent potential instability the early detection of cracks is imperative due to the prevalent use of concrete in critical infrastructure. Automated techniques leveraging artificial intelligence, machine learning, and deep learning as the traditional manual inspection methods are time-consuming. The existing automated concrete crack detection algorithms, despite recent advancements, face challenges in robustness, particularly in precise crack detection amidst complex backgrounds and visual distractions, while also maintaining low inference times. Therefore, this paper introduces a novel ensemble mechanism based on multiple quantized You Only Look Once version 8 (YOLOv8) models for the detection and segmentation of cracks in concrete structures. The proposed model is tested on different concrete crack datasets yielding enhanced segmentation results with at least 89.62% precision and intersection over a union score of 0.88. Moreover, the inference time per image is reduced to 27 milliseconds which is at least a 5% improvement over other models in the comparison. This is achieved by amalgamating the predictions of the trained models to calculate the final segmentation mask. The noteworthy contributions of this work encompass the creation of a model with low inference time, an ensemble mechanism for robust crack segmentation, and the enhancement of the learning capabilities of crack detection models. The fast inference time of the model renders it appropriate for real-time applications, effectively tackling challenges in infrastructure maintenance and safety.

Harnessing Deep Learning Techniques for Enhanced Detection and Classification of Cracks in Pavement Imagery

With the increased demand for infrastructure maintenance and the evolving capabilities of deep learning, there is a pressing need to apply advanced techniques for efficient and accurate detection of structural anomalies. This paper delves into the application of Convolutional Neural Networks (CNNs) and transfer learning to address the problem of pavement crack classification using images. Three distinctive models were explored: a 4-layer CNN, a 2-layer CNN, and a VGG-based transfer learning model. Through comprehensive experimentation, we demonstrate the efficacy of these models in accurately classifying Pavement cracks from a curated dataset. Our findings indicate that while each model possesses its unique strengths, the VGG-based transfer learning model exhibits superior performance in terms of precision and recall. This research not only contributes to the growing body of knowledge in infrastructure maintenance using deep learning but also provides practical insights for professionals aiming to employ automated systems for Pavement inspection.