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Regular inspection and monitoring of buildings and infrastructure, that is collectively called the built environment in this paper, is critical. The built environment includes commercial and residential buildings, roads, bridges, tunnels, and pipelines. Automation and robotics can aid in reducing errors and increasing the efficiency of inspection tasks. As a result, robotic inspection and monitoring of the built environment has become a significant research topic in recent years. This review paper presents an in-depth qualitative content analysis of 269 papers on the use of robots for the inspection and monitoring of buildings and infrastructure. The review found nine different types of robotic systems, with unmanned aerial vehicles (UAVs) being the most common, followed by unmanned ground vehicles (UGVs). The study also found five different applications of robots in inspection and monitoring, namely, maintenance inspection, construction quality inspection, construction progress monitoring, as-built modeling, and safety inspection. Common research areas investigated by researchers include autonomous navigation, knowledge extraction, motion control systems, sensing, multi-robot collaboration, safety implications, and data transmission. The findings of this study provide insight into the recent research and developments in the field of robotic inspection and monitoring of the built environment and will benefit researchers, and construction and facility managers, in developing and implementing new robotic solutions.

The management and monitoring of territorial development projects in Morocco face persistent challenges due to fragmented data systems, weak coordination, and the lack of real-time evaluation mechanisms. This study examines a GIS-based digital platform developed for Taza Province, designed to centralize project information, track progress, and support evidence-based decision-making. Using a mixed-methods approach that combines spatial analysis of more than 3,000 projects, stakeholder interviews, and performance metrics, the research assesses the platform's impact on governance, transparency, and strategic planning. Findings show that the system improves spatial equity by identifying underserved areas, optimizes resource allocation, and strengthens accountability through interactive dashboards, project management tools, and automated alerts. In addition, citizen engagement features foster participatory governance and increase trust in public policies. The Taza case demonstrates the transformative potential of GIS-driven platforms for territorial development, with clear prospects for scaling across Moroccan provinces to support national digital transformation and decentralization strategies.

Successful project management depends on ensuring the project’s objectives. Within these objectives, technical success is associated with achieving the expectations of the project baseline. The baseline of the project is made up of the definition of the scope (WBS), time (schedule) and costs (S curve) of the project. Directly, the project is expected to be technically successful if it manages to deliver its full scope on schedule and without associated cost overruns. Baseline performance management is how project managers track and control the progress of deliverables, timelines and associated costs. In a traditional approach, for waterfall-type projects that use the critical path paradigm, the baseline performance management tool par excellence is earned value management (EVM). Earned value management, in practice, works well when project costs are monitored and controlled; however, applying this approach to measure the status of the schedule presents serious inconsistencies. Over the last several decades, different variations of the original earned value have been developed to overcome some of these inconsistencies when used to measure project schedule status. Within these variations, we have the critical path earned value; the work in progress earned value; the critical path earned value and the work in progress; the earned schedule; and the critical path earned schedule. Each of these proposals tries to address some weakness of the original earned value management applied to time monitoring and control, for example, considering critical tasks as a focus on monitoring the progress of the schedule, solving the problem of task recognition late finishers, reporting schedule variances in time units and measuring adherence to the project’s schedule (P factor). Due to the exposed situation, it is necessary to determine which alternative of the versions of the original earned value is the most appropriate for the management of the project schedule, considering that there are several evaluation criteria that must be considered. In the present research, a systematic review and comparison of EVM and its variations for measuring project baseline schedule performance are performed to determine the most suitable methods for monitoring and controlling the project baseline schedule. For this purpose, the analytic hierarchy process (AHP) is used, and five comparison criteria are considered: schedule variation focused on critical tasks, recognition and measurement of the delay of tasks that finish late, schedule variation in time units, measurement of schedule adherence (P factor) and software support and development. The result of the AHP performed for comparing the methods shows that the best method for monitoring and controlling the project baseline schedule is the critical path earned schedule because it behaves adequately in comparison with the other methods for the evaluated comparison categories.

A combination of anthropogenic stressors and overharvesting has led to a loss of oyster reefs and the important ecosystem services they provide. Addressing these losses through restoration is now a focus of coastal and estuarine conservation efforts. The present study tested a low-cost, qualitative rapid assessment approach for monitoring habitat characteristics of subtidal oyster reefs differing in restoration activity. The study was conducted in 4 tributaries of the Choptank River complex, Maryland, USA, which included harvest areas and no-take reserves (sanctuaries). At each site, a categorical score ranging from 0 to 3 was compared with percent cover of oyster shell and of fouling organisms. Restored reefs in oyster sanctuaries had higher scores (2 to 3) and percent cover of oyster shell and fouling organisms than unrestored sanctuary reefs or reefs open to harvest; higher scores were also associated with greater percent cover of hard substrate and fouling organisms. The Harris Creek sanctuary reef system had the highest percentage of scores of 3 (40%), followed by tributaries with partially restored reef systems (14% in Little Choptank, 6% in Tred Avon) and harvest areas (2% in Broad Creek). Although validation with metrics of live oysters is needed, rapid video assessment appears to be an effective, low-cost tool for qualitative monitoring of subtidal oyster reefs in areas with adequate visibility.

River restoration is a main emphasis of river management in European countries. Cross-national comparisons of its implementation are still rare in scientific literature. Based on French and German national censuses, this study compares river restoration practices and monitoring by analysing 102 French and 270 German projects. This comparison aims to draw a spatial and temporal framework of restoration practices in both countries to identify potential drivers of cross-national similarities and differences. The results underline four major trends: (1) a lag of almost 15 years in river restoration implementation between France and Germany, with a consequently higher share of projects in Germany than in France, (2) substantial similarities in restored reach characteristics, short reach length, small rivers, and in “agricultural” areas, (3) good correspondences between stressors identified and restoration measures implemented. Morphological alterations were the most important highlighted stressors. River morphology enhancement, especially instream enhancements, were the most frequently implemented restoration measures. Some differences exist in specific restoration practices, as river continuity restoration were most frequently implemented in French projects, while large wood introduction or channel re-braiding were most frequently implemented in German projects, and (4) some quantitative and qualitative differences in monitoring practices and a significant lack of project monitoring, especially in Germany compared to France. These similarities and differences between Germany and France in restoration application and monitoring possibly result from a complex set of drivers that might be difficult to untangle (e.g., environmental, technical, political, cultural).

As timely information about a project’s state is key for management, we developed a data toolchain to support the monitoring of a project’s progress. By extending the Measurify framework, which is dedicated to efficiently building measurement-rich applications on MongoDB, we were able to make the process of setting up the reporting tool just a matter of editing a couple of .json configuration files that specify the names and data format of the project’s progress/performance indicators. Since the quantity of data to be provided at each reporting period is potentially overwhelming, some level of automation in the extraction of the indicator values is essential. To this end, it is important to make sure that most, if not all, of the quantities to be reported can be automatically extracted from the experiment data files actually used in the project. The originating use case for the toolchain is a collaborative research project on driving automation. As data representing the project’s state, 330+ numerical indicators were identified. According to the project’s pre-test experience, the tool is effective in supporting the preparation of periodic progress reports that extensively exploit the actual project data (i.e., obtained from the sensors—real or virtual—deployed for the project). While the presented use case concerns the automotive industry, we have taken care that the design choices (particularly, the definition of the resources exposed by the Application Programming Interfaces, APIs) abstract the requirements, with an aim to guarantee effectiveness in virtually any application context.

The integration of artificial intelligence (AI) into project management (PM) transforms how projects are planned, executed, and monitored. The main objective of this study is to provide a comprehensive bibliometric analysis exploring trends, thematic areas, and future directions in AI applications in project management by examining publications from the last decade. This research uncovers dominant themes such as machine learning, decision making, information management, and resource optimization. The findings highlight the growing use of AI to enhance efficiency, accuracy, and innovation in PM processes, with recent trends favoring data-driven approaches and emerging technologies like generative AI. Geographically, China, India, and the United States lead in publications, while the United Kingdom and Australia show a high citation impact. The research landscape, including AI-enhanced decision-making frameworks and cost analysis, demonstrates the diversity of AI applications in PM. An increased interest in the use of generative AI and its impact on PM and project managers was observed. This analysis contributes to the field by offering a structured overview of research trends, defining the challenges and opportunities for integrating AI into project management practices and offering perspectives on emerging technologies.

PurposeThe successful implementation of hospital projects (HPs) tends to confront sundry challenges in the planning and construction (P&C) phases due to their complexity and particularity. Employing key performance indicators (KPIs) facilitates the monitoring of HPs to advance their successful delivery. This study aims to comprehensively investigate the KPIs for hospital planning and construction (HPC).Design/methodology/approachThe KPIs for HPC were identified through a systematic review. Then a comprehensive assessment of these KPIs was performed utilizing a meta-analysis method. In this process, basic statistical analysis, subgroup analysis, sensitive analysis and publication bias analysis were performed.FindingsResults indicate that all 27 KPIs identified from the literature are significant for executing HPs in P&C phases. Also, some unconventional performance indicators are crucial for implementing HPs, such as “Project monitoring effectiveness” and “Industry innovation and synergy,” as their high significance is reflected in this study. Despite the fact that the findings of meta-analysis are more trustworthy than those of individual studies, a high heterogeneity still exists in the findings. It highlights the inherent uncertainty in the construction industry. Hence, this study applied subgroup analysis to explore the underlying factors causing the high level of heterogeneity and used sensitive analysis to assess the robustness of the findings.Originality/valueThere is no consensus among the prior studies on KPIs for HPC specifically and their degree of significance. Additionally, few reviews in this field have focused on the reliability of the results. This study comprehensively assesses the KPIs for HPC and explores the variability and robustness of the results, which provides a multi-dimensional perspective for practitioners and the research community to investigate the performance of HPs during the P&C stages.

This book will provide readers with an in-depth theoretical awareness and practical guidance on the implementation of an effective monitoring and evaluation (M&E) system to ensure construction projects meet approved quality, cost, time and social sustainability objectives. The authors discuss the drivers, challenges, determinants and benefits of effective M&E implementation together with the theories and models underpinning construction project M&E practices. Further, a comparative overview of M&E practices in developed and developing countries is presented to elucidate the best practices. The book first conceptualizes M&E as a five-factor model comprising stakeholder involvement, budgetary allocation and logistics, technical capacity and training, leadership, and communication. It then presents an M&E case study on the Ghanaian construction industry before expanding on the idea of M&E systems as an effective tool for project performance and in optimizing a project's contribution to society and the environment. The book further provides guidance on M&E practice for construction project managers, investors, professionals, researchers and other stakeholders and is therefore of interest to those in architecture, construction engineering, planning, project management and development studies.