Search Results (8)

Road surface condition monitoring is critical for ensuring safe and efficient transportation networks. This study proposes and evaluates a framework that compares imagery-, Light Detection and Ranging (LiDAR), and accelerometer-based approaches for pavement anomaly detection. The analysis first focused on a 5-mile urban roadway segment, in which all three sensing modalities were evaluated under identical survey conditions using manually interpreted reference anomalies to compare detection accuracy, severity classification, and processing efficiency. The imagery-based Convolutional Transformer-based Crack Segmentation (CT-CrackSeg) model achieved a precision, recall, and F1-score of 88.5%, 88.5%, and 88.5%, respectively, but remained sensitive to environmental factors such as shadows, curbs, roadside features, and pavement texture variations. The LiDAR-based method achieved an F1-score of 93.0%, while the accelerometer-based Isolation Forest and Adaptive Threshold methods achieved F1-scores of 95.2% and 97.2%, respectively. These results indicate strong detection performance under the evaluated validation conditions; however, the reported precision values should be interpreted as dataset-specific rather than universal performance levels. Given the accelerometer-based approach’s strong detection performance, minimal processing time, and low deployment cost, it was further applied across a 36-mile roadway network to evaluate its scalability for network-level monitoring. Across the full route, the spatial agreement among accelerometer systems exceeded 0.91, while the agreement between the two detection methods exceeded 0.96, with 962–996 surface defects detected depending on the sensor and method. Integrating the anomaly detection results into a Potree-based web portal enabled interactive validation with geotagged imagery and point clouds, improving interpretability and diagnostic insight. Overall, the findings highlight that accelerometer-based monitoring, even with consumer-grade sensors, provides a practical, scalable, and low-cost solution for pavement evaluation, while LiDAR and imagery serve as complementary tools for detailed verification and characterization. Full article

Effective laboratory training is essential in engineering education, yet conventional on-site instruction is often constrained by time, accessibility, and safety considerations. To address these challenges, this study presents the design, implementation, and evaluation of a web-based virtual reality (WebVR) representation of a large-scale engineering laboratory constructed from massive colorized point cloud data. This study proposes a novel WebVR approach that integrates Unity and Potree for high-fidelity point-cloud visualization combined with advanced interactive capabilities in a browser-based virtual laboratory. It supports immersive first-person exploration, guided navigation, interactive hotspots conveying equipment and safety information, and emergency evacuation simulations. The usability, usefulness, and acceptance of the virtual laboratory were evaluated through an anonymous questionnaire administered to students and laboratory staff. User evaluation results indicated consistently positive feedback, with 100% of respondents rating the interface/navigation and visual/interactive content as good or excellent, 88.6% identifying scene realism as the biggest system strength (the most frequently selected), 74.3% reporting significantly higher engagement compared with traditional online laboratory training, and 82.9% indicating they would definitely recommend the system as a learning resource. In addition, a thematic analysis of qualitative feedback was performed to inform future enhancements of the WebVR environment. Overall, the findings demonstrate that the WebVR-based virtual laboratory can effectively complement conventional on-site laboratory instruction, offering a scalable, accessible, and low-risk platform that enhances learning experiences in engineering education. Full article

The Oymaağaç Höyük Project (2005–today) investigates a 6,500-year-oldmulti-period settlement in the district of Vezirköprü at the southern edge of the Black Sea province of Samsun in northern Türkiye. According to cuneiform texts, the site can be associated with the Hittite cult city of Nerik (17th–12th century BC). Automatic multi-image photogrammetry, also known as Structure from Motion (SfM), has proven to be a powerful and flexible means for the three-dimensional documentation of objects and finds of different shapes and sizes. Data products were created in the form of 3D point clouds, textured surface models, orthophotos, sections, and 3D prints (physical 3D models). Visualization of 3D data was realized via an internet browser (Potree Viewer, Babylon.js) and virtual reality (VR) techniques. Photogrammetry is very flexible in its application because the accuracy depends essentially on the scale of the images. On the other hand, the constantly growing volume of data as a result of the evolving technical possibilities requires sustainable data management, which is difficult to realize in practice due to limited financial resources. The article provides an overview of the use of photogrammetry in the project. Full article

The rapid evolution of the urban landscape highlights the need to digitally document the state and historical transformations of heritage sites in densely urbanised areas through the combination of different geomatics survey approaches. Moreover, it is necessary to raise awareness of sites by developing strategies for their dissemination to a diverse audience through engaging, interactive, and accessible 3D web platforms. This work illustrates a methodology for the digital documentation and narration of a cultural heritage site through the implementation of a lightweight and replicable 3D navigation platform based on open-source technologies. Such a solution aims to be an easy-to-implement low-cost approach. The methodology is applied to the case study of the Farnese Castle in Piacenza (Italy), describing the data collection and documentation carried out with an in situ survey and illustrating how the resulting products were integrated into the web platform. The exploration functionalities of the platform and its potential for different types of audiences, from experts to users not familiar with 3D objects and geomatics products, were evaluated and documented on a ReadTheDocs website, allowing interested users to reproduce the project for other applications thanks to the template code available on GitHub. Full article

This paper presents an online application—called 3D integrator—enabling visual cross-examinations of architectural and acoustic data on web browsers and explains the rationale behind its development. The tool consists of a series of overlays developed over the Potree 3D point cloud renderer. It is used to display visually, in an interactive environment, the 3D point clouds resulting from a survey protocol tailored to the specific needs of the corpus under scrutiny—15 small-scale edifices often referred to as “minor heritage assets”—and to the research’s overall ambition, reasoning on architectural and acoustic features at an interdisciplinary level. One of the tool’s distinctive features is to project abstract information (acoustic descriptors) in a “close to real” 3D space (point clouds), hence merging scientific visualisation and information visualisation practices. The paper first shortly sums up the particularities of the survey protocol and discusses the implementation of the analytical add-ons that have been introduced (visual trace of the survey protocol itself, volume calculation, and exploratory 3D representation of acoustic descriptors). It then focuses on use cases that illustrate what the approach helps to observe concerning the interiors of edifices when capturing and co-examining dimensional and acoustic features. Full article

Road maintenance is a key aspect of road safety and resilience. Traffic signs are an important asset of the road network, providing information that enhances safety and driver awareness. This paper presents a method for the recognition and geolocation of vertical traffic signs based on artificial intelligence and the use of a low-cost mobile mapping system. The approach developed includes three steps: First, traffic signals are detected and recognized from imagery using a deep learning architecture with YOLOV3 and ResNet-152. Next, LiDAR point clouds are used to provide metric capabilities and cartographic coordinates. Finally, a WebGIS viewer was developed based on Potree architecture to visualize the results. The experimental results were validated on a regional road in Avila (Spain) demonstrating that the proposed method obtains promising, accurate and reliable results. Full article

The hypogea of the Punic necropolis of Nora represented a testing ground for the use of photogrammetry as an archaeological survey tool in a highly critical context, both from the point of view of the survey itself and from the point of view of the understanding and dissemination of the underground evidence. The study describes the acquisition techniques and the tools used to share the 3D models, both among the research team and with external users, with a specific focus on web-based tools (Potree). Full article

Currently, the use of free and open-source software is increasing. The flexibility, availability, and maturity of this software could be a key driver to develop useful and interesting solutions. In general, open-source solutions solve specific tasks that can replace commercial solutions, which are often very expensive. This is even more noticeable in areas requiring analysis and manipulation/visualization of a large volume of data. Considering that there is a major gap in the development of web applications for photogrammetric processing, based on open-source technologies that offer quality results, the application presented in this article is intended to explore this niche. Thus, in this article a solution for photogrammetric processing is presented, based on the integration of MicMac, GeoServer, Leaflet, and Potree software. The implemented architecture, focusing on open-source software for data processing and for graphical manipulation, visualization, measuring, and analysis, is presented in detail. To assess the results produced by the proposed web application, a case study is presented, using imagery acquired from an unmanned aerial vehicle in two different areas. Full article