APPLICATION OF NEURAL NETWORK MODELS IN THE MAPPING OF TELECOMMUNICATIONS INFRASTRUCTURE OBJECTS

Abstract. UAV photogrammetry plays an essential role in applications such as disaster management, food security, and mapping due to its adaptability, scalability, and accuracy in data collection. Consequently, the increasing popularity of the UAV photogrammetry domain has led to a growing demand for comprehensive education accessible through academic institutions. Meanwhile, the flexibility and freedom associated with online education have sparked significant demand for online learning programs. Different users actively seek online courses and materials to delve into the intricacies of UAV photogrammetry. However, the abundance of online resources in this area poses challenges in finding such reliable courses.To address this challenge, the ITC team from the UAV centre and EOS Department at the University of Twente investigated the current online education courses related to UAV Photogrammetry offered globally. They compiled an inventory of these courses, categorizing them according to different educational levels- introductory, intermediate, and advanced—to align with the needs of key photogrammetry user categories. The project also investigated the currently available UAV datasets and software packages supporting technical training and professional applications. Further details are available on the project website.Besides, the project gathers insights into gaps in UAV photogrammetry knowledge areas and UAV applications in geoscience by designing, distributing, and analysing a UAV Gap survey.

CORR Synthesis: When Should the Orthopaedic Surgeon Use Artificial Intelligence, Machine Learning, and Deep Learning?

Automatic crack detection and structural inspection of cultural heritage buildings using UAV photogrammetry and digital twin technology

The development and management of green open spaces are essential in overcoming environmental problems such as air pollution and urban warming. 3D modeling and biomass calculation are the example efforts in managing green open spaces. In this study, 3D modeling was carried out on point clouds data acquired by the UAV photogrammetry and UAV LiDAR methods. 3D modeling is done explicitly using the point clouds fitting method. This study uses three fitting methods: the spherical fitting method, the ellipsoid fitting method, and the spherical harmonics fitting method. The spherical harmonics fitting method provides the best results and produces an R2 value between 0.324 to 0.945. In this study, Above-Ground Biomass (AGB) calculations were also carried out from the modeling results using three methods with UAV LiDAR and Photogrammetry data. AGB calculation using UAV LiDAR data gives better results than using photogrammetric data. AGB calculation using UAV LiDAR data gives an accuracy of 78% of the field validation results. However, for visualization purposes with a not-too-wide area, a 3D model of photogrammetric data using the spherical harmonics method can be used.

Unmanned aerial vehicles, equipped with various sensors and devices, are increasingly used to acquire geospatial data in geodesy, geoinformatics, and environmental studies. In this context, a new research and professional field has been developed – UAV photogrammetry – dealing with photogrammetry data acquisition and data processing, acquired by unmanned aerial vehicles. In this study, we analyse the selected factors that impact the quality of data provided using UAV photogrammetry, with the focus on positional accuracy; they are discussed in three groups: (a) factors related to the camera properties and the quality of images; (b) factors related to the mission planning and execution; and (c) factors related to the indirect georeferencing of images using ground control points. These selected factors are analysed based on the detailed review of relevant scientific publications. Additionally, the influence of the number of ground control points and their spatial distribution on point clouds' positional accuracy has been investigated for the case study. As the conclusion, key findings and recommendations for UAV photogrammetric projects are given; we have highlighted the importance of suitable lighting and weather conditions when performing UAV missions for spatial data acquisition, quality equipment, appropriate parameters of UAV data acquisition, and a sufficient number of ground control points, which should be determined with the appropriate positional accuracy and their correct distribution in the field.

The increasing availability of highly detailed and accurate three-dimensional (3D) geospatial data are currently pushing the 3D change detection analysis towards a new 3D mapping frame. In this paper, medium-term changes (8 years) at a coastal rocky cliff are quantified using and comparing 2.5D and 3D methods to estimate the volume of rockfalls and three datasets: one Terrestrial Laser Scanner (TLS) acquired in 2010 and two coincident Unmanned Aerial Vehicles (UAV: multirotor and fixed-wing) datasets acquired in 2018. Advantages and limitations of these techniques, platforms and methods are discussed and the role of Ground Control Points (GCPs) distribution was analysed. Maps of 3D changes were produced by means of the Multiscale-Model-to-Model Cloud-Comparison algorithm (M3C2). The volume of the eroded-deposited material was estimated using two 2.5D and one 3D approaches: 1) rasterizing M3C2 distances using a conventional top-view perspective, 2) rasterizing the M3C2 distances rotated and orientated with the z vector normal and, 3) for the largest rockfalls, the volume was estimated using the Poisson Surface Reconstruction (PSR) algorithm (3D). The 3D models produced using both UAV platforms showed cm-level accuracies with Root Mean Square Error (RMSE) of 0.02 and 0.03 m for the multirotor and the fixed-wing, respectively, and faithfully represented cliff geometry. GCP configuration analysis showed that, at least, two stripes of GCPs evenly distributed at different heights are necessary, but three are recommended. The spatial pattern of change between the TLS and the two UAVs datasets was similar. The quantification of the volume of the eroded-accumulated material (using the M3C2 distances and the two UAV datasets) resulted in significant differences as the fixed-wing underestimated the values calculated using the multirotor dataset. The 2.5D strategies used to quantify the volume of change underestimated the eroded volume of the largest rockfalls (compared to the PSR 3D method), which provided the most accurate volume estimates.

As computing applications edge closer toward developing human-like ability, the requirement for culture aware human-machine communication is becoming paramount. Ever evolving natural language is full of abstraction, pop-culture reference, and metaphor. Rigid language understanding implementations in Artificial Intelligence (AI) systems like voice assistants often lead to misunderstanding in command execution, degrading the user experience and accuracy of AI applications. Further, the inability for AI to have an understanding of the data in reference to itself limits its ability to fully comprehend conversation. Theorized Artificial General Intelligence (AGI) aids this problem through enabling cognitive data processing. This paper presents a novel method of training an AGI system through a peripheral interface using online news articles to increase its understanding of data in reference to current societal culture while heightening its overall awareness.

Augmented Reality (AR) and Artificial Intelligence (AI) are technological domains that closely interact with space at architectural and urban scale in the broader ambits of cultural heritage and innovative design.This second collection of essays, that originated under the aegis of Representation Challenges, by reintroducing the combination of Augmented Reality (AR) and Artificial Intelligence (AI) explores its new frontiers. The ambitious goal of this second step was to explore the new boundaries that AR and AI mark in the fields of cultural heritage and innovative design, opening to international studies. This goal has been fully achieved and surprisingly surpassed, thanks to the lymph provided by new proposals and new scholars, which we hope – at least in a small part – to have contributed to fuel and stimulate.Papers’ most cited keywords brings out the interests concerning digital technologies, primarily AR and AI, as central themes, and original relationships with digital acquisition methodologies (photogrammetry and UAV photogrammetry), with interpretive and informative visualization (BIM, H-BIM, 3D modelling, VPL, digital fabrication, and mapping), and with visual communication (VR, immersive environment, interactive representation, and hologram).This book collects 49 papers and 5 keynotes lectures and identify five lines of research that may guide future developments.

Augmented Reality (AR) and Artificial Intelligence (AI) are technological domains that closely interact with space at architectural and urban scale in the broader ambits of cultural heritage and innovative design.This second collection of essays, that originated under the aegis of Representation Challenges, by reintroducing the combination of Augmented Reality (AR) and Artificial Intelligence (AI) explores its new frontiers. The ambitious goal of this second step was to explore the new boundaries that AR and AI mark in the fields of cultural heritage and innovative design, opening to international studies. This goal has been fully achieved and surprisingly surpassed, thanks to the lymph provided by new proposals and new scholars, which we hope – at least in a small part – to have contributed to fuel and stimulate.Papers’ most cited keywords brings out the interests concerning digital technologies, primarily AR and AI, as central themes, and original relationships with digital acquisition methodologies (photogrammetry and UAV photogrammetry), with interpretive and informative visualization (BIM, H-BIM, 3D modelling, VPL, digital fabrication, and mapping), and with visual communication (VR, immersive environment, interactive representation, and hologram).This book collects 49 papers and 5 keynotes lectures and identify five lines of research that may guide future developments.

Augmented Reality (AR) and Artificial Intelligence (AI) are technological domains that closely interact with space at architectural and urban scale in the broader ambits of cultural heritage and innovative design.This second collection of essays, that originated under the aegis of Representation Challenges, by reintroducing the combination of Augmented Reality (AR) and Artificial Intelligence (AI) explores its new frontiers. The ambitious goal of this second step was to explore the new boundaries that AR and AI mark in the fields of cultural heritage and innovative design, opening to international studies. This goal has been fully achieved and surprisingly surpassed, thanks to the lymph provided by new proposals and new scholars, which we hope – at least in a small part – to have contributed to fuel and stimulate.Papers’ most cited keywords brings out the interests concerning digital technologies, primarily AR and AI, as central themes, and original relationships with digital acquisition methodologies (photogrammetry and UAV photogrammetry), with interpretive and informative visualization (BIM, H-BIM, 3D modelling, VPL, digital fabrication, and mapping), and with visual communication (VR, immersive environment, interactive representation, and hologram).This book collects 49 papers and 5 keynotes lectures and identify five lines of research that may guide future developments.

Augmented Reality (AR) and Artificial Intelligence (AI) are technological domains that closely interact with space at architectural and urban scale in the broader ambits of cultural heritage and innovative design.This second collection of essays, that originated under the aegis of Representation Challenges, by reintroducing the combination of Augmented Reality (AR) and Artificial Intelligence (AI) explores its new frontiers. The ambitious goal of this second step was to explore the new boundaries that AR and AI mark in the fields of cultural heritage and innovative design, opening to international studies. This goal has been fully achieved and surprisingly surpassed, thanks to the lymph provided by new proposals and new scholars, which we hope – at least in a small part – to have contributed to fuel and stimulate.Papers’ most cited keywords brings out the interests concerning digital technologies, primarily AR and AI, as central themes, and original relationships with digital acquisition methodologies (photogrammetry and UAV photogrammetry), with interpretive and informative visualization (BIM, H-BIM, 3D modelling, VPL, digital fabrication, and mapping), and with visual communication (VR, immersive environment, interactive representation, and hologram).This book collects 49 papers and 5 keynotes lectures and identify five lines of research that may guide future developments.

Malta, as a small island state, faces increasing challenges from climate change due to its vulnerability to climate impacts. This study investigates the application of geospatial tools and techniques to enhance Malta’s capacity for climate change-related planning and management, aligning with Sustainable Development Goal (SDG) 13: Climate Action. The methodology integrates historic cartographic resources, as detailed in our previous work (Tranchant et al., 2024), with contemporary approaches such as UAV photogrammetry and dataset comparisons using software like Cloud Compare. These datasets are augmented by ground-truthing data, including geotechnical monitoring via tilt plates and ground monitoring nails - both deliverables from a previous project, Coastal Satellite-Assisted Governance (SAGE). The collected data will be compiled into a unified geodatabase to enhance disaster risk reduction efforts through real-time monitoring of climate-enhanced risk levels. The tools and insights, where permissible, will be shared with stakeholders beyond government and academia to promote education and public awareness. While the study does not directly aim to mitigate the effects of climate change, it strengthens the Maltese government’s capacity to proactively evaluate and respond to its impacts, particularly with respect to coastal dynamics. Future efforts will focus on developing an open-source, WebGIS-based A-DiNSAR monitoring system for ground deformation. This system aims to replicate the Copernicus European Ground Motion Service while leveraging higher-resolution datasets to achieve greater precision at localized scales, such as monitoring ground movement and infrastructural stability in cliffside and coastal zones. By addressing areas most susceptible to ground movement and stability issues due to climate change, the study enhances Malta’s resilience to climate impacts, aligning with the objectives of SDG 13: Climate Action.

TPE-BFL: Training Parameter Encryption scheme for Blockchain based Federated Learning system

Augmented Reality (AR) and Artificial Intelligence (AI) are technological domains that closely interact with space at architectural and urban scale in the broader ambits of cultural heritage and innovative design.This second collection of essays, that originated under the aegis of Representation Challenges, by reintroducing the combination of Augmented Reality (AR) and Artificial Intelligence (AI) explores its new frontiers. The ambitious goal of this second step was to explore the new boundaries that AR and AI mark in the fields of cultural heritage and innovative design, opening to international studies. This goal has been fully achieved and surprisingly surpassed, thanks to the lymph provided by new proposals and new scholars, which we hope – at least in a small part – to have contributed to fuel and stimulate.Papers’ most cited keywords brings out the interests concerning digital technologies, primarily AR and AI, as central themes, and original relationships with digital acquisition methodologies (photogrammetry and UAV photogrammetry), with interpretive and informative visualization (BIM, H-BIM, 3D modelling, VPL, digital fabrication, and mapping), and with visual communication (VR, immersive environment, interactive representation, and hologram).This book collects 49 papers and 5 keynotes lectures and identify five lines of research that may guide future developments.

Augmented Reality (AR) and Artificial Intelligence (AI) are technological domains that closely interact with space at architectural and urban scale in the broader ambits of cultural heritage and innovative design.This second collection of essays, that originated under the aegis of Representation Challenges, by reintroducing the combination of Augmented Reality (AR) and Artificial Intelligence (AI) explores its new frontiers. The ambitious goal of this second step was to explore the new boundaries that AR and AI mark in the fields of cultural heritage and innovative design, opening to international studies. This goal has been fully achieved and surprisingly surpassed, thanks to the lymph provided by new proposals and new scholars, which we hope – at least in a small part – to have contributed to fuel and stimulate.Papers’ most cited keywords brings out the interests concerning digital technologies, primarily AR and AI, as central themes, and original relationships with digital acquisition methodologies (photogrammetry and UAV photogrammetry), with interpretive and informative visualization (BIM, H-BIM, 3D modelling, VPL, digital fabrication, and mapping), and with visual communication (VR, immersive environment, interactive representation, and hologram).This book collects 49 papers and 5 keynotes lectures and identify five lines of research that may guide future developments.