Global Navigation Satellite Systems (GNSS) receivers are nowadays commonly used in monitoring applications, e.g., in estimating crustal and infrastructure displacements. This is basically due to the recent improvements in GNSS instruments and methodologies that allow high-precision positioning, 24 h availability and semiautomatic data processing. In this paper, GNSS-estimated displacements on a dam structure have been analyzed and compared with pendulum data. This study has been carried out for the Eleonora D’Arborea (Cantoniera) dam, which is in Sardinia. Time series of pendulum and GNSS over a time span of 2.5 years have been aligned so as to be comparable. Analytical models fitting these time series have been estimated and compared. Those models were able to properly fit pendulum data and GNSS data, with standard deviation of residuals smaller than one millimeter. These encouraging results led to the conclusion that GNSS technique can be profitably applied to dam monitoring allowing a denser description, both in space and time, of the dam displacements than the one based on pendulum observations.

It is incontrovertible that an exchange of files is essentially required at several stages of the workflow in the architecture, engineering, and construction (AEC) industry. Therefore, investigating and detecting the capabilities/inabilities of building information modeling (BIM) software packages with respect to interoperability can be informative to stakeholders who exchange data between various BIM packages. The work presented in this paper includes a discussion on the interoperability of different software platforms commonly used in the AEC industry. Although, in theory, flawless interoperability of some types of files between different BIM platforms is ensured, in practical applications, this is not always the case. Hence, this research aims to identify faults in data exchange by assessing different possible scenarios where a sample Industry Foundation Classes (IFC) four-dimensions (4D) BIM model and related Gantt charts are exchanged. Throughout the interoperability analysis of both IFC file and Gantt charts, the following checks were carried out: geometrical and nongeometrical information exchange through IFC files, 4D information correct readability, and presence of missing schedule information in Gantt charts after their import/export procedure. The results show that interoperability between the analyzed platforms is not always ensured, providing useful insight into realistic scenarios.

This paper investigates quality management (QM) during the execution phase of structural elements by proposing, developing, and testing a complete framework by integrating building information modeling (BIM) and augmented reality (AR) technology. QM during execution is boosted by BIM–AR integration through a dedicated web-based system aimed at reducing the occurrence of omissions and negligence. With such a system, efficiency is improved by allowing the entering of inspection data directly in a shared digital environment, where people involved in QM have permanent access to updated information and inspection results, clearly organized, and entered in real time. The system has been developed in the asp.net framework using C# language where, by generating a web-based checklist and establishing its link to AR, it can enhance the process of information extraction from industry foundation class (IFC) 4D BIM models and the recording of inspection data. A test has been performed on a real case study in Budapest, to assess the effectiveness of the system in the field. Results demonstrate the following benefits brought by such a type of QM system: improved understanding of the design, access to information, and overview of the quality status of the project, leading to reductions in defects and reworking, as well as improved and quicker response and decision-making.

The International Service for the Geoid (ISG, https://www.isgeoid.polimi.it/, last access: 31 March 2021) provides free access to a dedicated and comprehensive repository of geoid models through its website. In the archive, both the latest releases of the most important and well-known geoid models, as well as less recent or less known ones, are freely available, giving to the users a wide range of possible applications to perform analyses on the evolution of the geoid computation research field. The ISG is an official service of the International Association of Geodesy (IAG), under the umbrella of the International Gravity Field Service (IGFS). Its main tasks are collecting, analysing, and redistributing local, regional, and continental geoid models and providing technical support to people involved in geoid-related topics for both educational and research purposes. In the framework of its activities, the ISG performs research taking advantage of its archive and organizes seminars and specific training courses on geoid determination, supporting students and researchers in geodesy as well as distributing training material on the use of the most common algorithms for geoid estimation. This paper aims at describing the data and services, including the newly implemented DOI Service for geoid models (https://dataservices.gfz-potsdam.de/portal/?fq=subject:isg, last access: 31 March 2021), and showing the added value of the ISG archive of geoid models for the scientific community and technicians, like engineers and surveyors (https://www.isgeoid.polimi.it/Geoid/reg_list.html, last access: 31 March 2021).

Dams are one of the most important engineering works of the current human society, and it is crucial to monitor and obtain analytical data to log their conditions, predict their behavior and, eventually, receive early warnings for planning interventions and maintenance activities. In this context, GNSS-based point displacement monitoring is nowadays a consolidated technique that is able to provide daily millimeter level accuracy, even with less sophisticated and less expensive single-frequency equipment. If properly designed, daily records of such monitoring systems produce time series that, when long enough, allow for an accurate reconstruction of the geometrical deformation of the structure, thus guiding semi-automatic early warning systems. This paper focuses on the procedure for the GNSS time series processing with a statistical approach. In particular, real-world times series collected from a dam monitoring test case are processed as an example of data filtering. A remove–restore technique based on a collocation approach is applied here. Basically, it consists of an initial deterministic modeling by polynomials and periodical components through least squares adjustment and Fourier transform, respectively, followed by a stochastic modeling based on empirical covariance estimation and a collocation approach. Filtered time series are interpreted by autoregressive models based on environmental factors such as air or water temperature and reservoir water level. Spatial analysis is finally performed by computing correlations between displacements of the monitored points, as well as by visualizing the overall structure deformation in time. Results positively validate the proposed data processing workflow, providing useful hints for the implementation of automatic early warning systems in the framework of structural monitoring based on continuous displacement measurements.