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This article explores the potential of the Unreal Engine as a tool for creating realistic 3D visualizations of large-scale areas (1000 km2 and more) using GIS datasets. Unlike small-scale visualizations, large-scale visualizations are rare and often not public, which presents significant problems since they present different challenges and require different approaches. This article presents several relevant scientific studies and projects that have successfully used game engines for similar purposes. This case study focuses on the computational techniques used in Unreal Engine for the 3D visualization of GIS data and the potential application of Unreal Engine in large-scale geo-visualizations. It explores the potential for using GIS data within a game engine, including plug-ins that provide additional functionality for working with GIS data, such as the Vitruvio plug-in to implement procedural modeling of buildings. The case study is applied to GIS datasets of the historical Vltava Valley covering an area of 1670 km2 to demonstrate the unique challenges of using Unreal Engine to create realistic visualizations of large-scale historical landscapes. The resulting visualizations are presented. The practical application of this research provides insights into the potential of the Unreal Engine as a tool for creating realistic 3D visualizations of large-scale historical areas. [ABSTRACT FROM AUTHOR]

This study explores how combining virtual reality (VR) and augmented reality (AR) with geographic information systems (GIS) revolutionizes data visualization. It traces the historical development of these technologies and highlights key milestones that paved the way for this study's objectives. While existing platforms like Esri's software and Google Earth VR show promise, they lack complete integration for immersive GIS visualization. This gap has led to the need for a dedicated workflow to integrate selected GIS data into a game engine for visualization purposes. This study primarily utilizes QGIS for data preparation and Unreal Engine for immersive visualization. QGIS handles data management, while Unreal Engine offers advanced rendering and interactivity for immersive experiences. To tackle the challenge of handling extensive GIS datasets, this study proposes a workflow involving tiling, digital elevation model generation, and transforming GeoTIFF data into 3D objects. Leveraging QGIS and Three.js streamlines the conversion process for integration into Unreal Engine. The resultant virtual reality application features distinct stations, enabling users to navigate, visualize, compare, and animate GIS data effectively. Each station caters to specific functionalities, ensuring a seamless and informative experience within the VR environment. This study also delves into augmented reality applications, adapting methodologies to address hardware limitations for smoother user experiences. By optimizing textures and implementing augmented reality functionalities through modules Swift, RealityKit, and ARKit, this study extends the immersive GIS experience to iOS devices. In conclusion, this research demonstrates the potential of integrating virtual reality, augmented reality, and GIS, pushing data visualization into new realms. The innovative workflows and applications developed serve as a testament to the evolving landscape of spatial data interpretation and engagement. [ABSTRACT FROM AUTHOR]

Gamification techniques have been proven effective in various fields such as education and industry. In this paper, we introduce a novel approach that applies gamification techniques to the identification of road assets in Mobile Laser Scanning (MLS) data. Our method utilises three gamification techniques: avatar (vehicle), point cloud segmentation into levels, and scoring. We implemented these techniques in Unreal Engine and evaluated their performance using three real-world case studies. We also compared two ways of point cloud visualisation: mesh-based and point-based. Our results demonstrate that our gamification approach improves the handling and visualisation of point clouds when compared to other free software such as Cloud Compare. Specifically, the point-based visualisation method provides a more accurate representation of the road environment and the input point cloud and is easier to import into Unreal Engine. However, this method requires more computational resources for visualisation. On the other hand, level segmentation ensures a constant frame rate of 60 frames per second. Furthermore, our gamification approach enhances the experience of road asset identification, making it more enjoyable for the user. However, we acknowledge that the quality of the point cloud remains the primary factor affecting the accuracy of asset identification, regardless of the software used. Overall, our proposed gamification approach offers a promising solution for improving the identification of road assets in MLS data and has the potential to be applied to other fields beyond road asset identification. [ABSTRACT FROM AUTHOR]

To improve the rapidity of path planning for drones in unknown environments, a new bio-inspired path planning method using E-DQN (event-based deep Q-network), referring to introducing event stream to reinforcement learning network, is proposed. Firstly, event data are collected through an airsim simulator for environmental perception, and an auto-encoder is presented to extract data features and generate event weights. Then, event weights are input into DQN (deep Q-network) to choose the action of the next step. Finally, simulation and verification experiments are conducted in a virtual obstacle environment built with an unreal engine and airsim. The experiment results show that the proposed algorithm is adaptable for drones to find the goal in unknown environments and can improve the rapidity of path planning compared with that of commonly used methods. [ABSTRACT FROM AUTHOR]

Digital twins are increasingly gaining popularity as a method for simulating intricate natural and urban environments, with the precise segmentation of 3D objects playing an important role. This study focuses on developing a methodology for extracting buildings from textured 3D meshes, employing the PicassoNet-II semantic segmentation architecture. Additionally, we integrate Markov field-based contextual analysis for post-segmentation assessment and cluster analysis algorithms for building instantiation. Training a model to adapt to diverse datasets necessitates a substantial volume of annotated data, encompassing both real data from Quebec City, Canada, and simulated data from Evermotion and Unreal Engine. The experimental results indicate that incorporating simulated data improves segmentation accuracy, especially for under-represented features, and the DBSCAN algorithm proves effective in extracting isolated buildings. We further show that the model is highly sensible for the method of creating 3D meshes. [ABSTRACT FROM AUTHOR]

This article demonstrates recent technological advancements enabling the creation of digital twins for expansive real-world terrains. Focusing on the archaeological site Uruk-Warka in southern Iraq the German Archaeological Institute deployed the Delta Quad Pro, a winged UAV equipped with vertical take-off and landing capabilities. This UAV captured 32,000 aerial images of the ancient city and its immediate environment. Each image was precisely geotagged using an integrated DGNSS receiver. Utilizing advanced 3D photogrammetry software, we synthesized these images into a single georeferenced model. The outcome was a detailed triangulated mesh, comprising of one billion triangles and 1024 8k-resolution texture files, representing a 40 square kilometers terrain. When rendered in a game-engine and applying the new technologies Nanite and Streaming Virtual Texture, this massive dataset can be visualized in real-time. The result is 'Uruk-VR,' a digital twin of the Uruk-Warka archaeological site, most of which has never been investigated. Basic tools have been implemented to annotate features and measure distances within the Uruk-VR. The methodologies showcased here are scalable for creating digital twins of diverse terrains. Uruk-VR's potential extends to research, education and conservation, exemplifying how game engines can seamlessly integrate vast and diverse geospatial data in 3D space. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) have emerged as a highly efficient means of monitoring landslide-prone regions, given the growing concern for urban safety and the increasing occurrence of landslides. Designing optimal UAV flight routes is crucial for effective landslide monitoring. However, in real-world scenarios, the testing and validating of flight path planning algorithms incur high cost and safety concerns, making overall flight operations challenging. Therefore, this paper proposes the use of the Unreal Engine simulation framework to design UAV flight path planning specifically for landslide monitoring. It aims to validate the authenticity of the simulated flight paths and the correctness of the algorithms. Under the proposed simulation framework, we then test a novel flight path planning algorithm. The simulation results demonstrate that the model reconstruction obtained using the novel flight path algorithm exhibits more detailed textures, with a 3D model simulation accuracy ranging from 10 to 14 cm. Among them, the RMSE value of the novel flight route algorithm falls within the range of 10 to 11 cm, exhibiting a 2 to 3 cm improvement in accuracy compared to the traditional flight path algorithm. Additionally, it effectively reduces the flight duration by 9.3% under the same flight path compared to conventional methods. The results confirm that the simulation framework developed in this paper meets the requirements for landslide damage monitoring and validates the feasibility and correctness of the UAV flight path planning algorithm. [ABSTRACT FROM AUTHOR]

A realistic and visible dynamic simulation platform can significantly facilitate research on underwater robots. This paper uses the Unreal Engine to generate a scene that resembles real ocean environments, before building a visual dynamic simulation platform in conjunction with the Air-Sim system. On this basis, the trajectory tracking of a biomimetic robotic fish is simulated and assessed. More specifically, we propose a particle swarm optimization algorithm-based control strategy to optimize the discrete linear quadratic regulator controller for the trajectory tracking problem, as well as tracking and controlling discrete trajectories with misaligned time series through introducing a dynamic time warping algorithm. Simulation analyses of the biomimetic robotic fish following a straight line, a circular curve without mutation, and a four-leaf clover curve with mutation are carried out. The obtained results verify the feasibility and effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

Due to the complexity of wetland ecosystems, wetlands have a wide area of alternating land and water zones and complex vegetation composition, making it challenging to achieve dynamic displays of virtual wetland scenes using three-dimensional modeling. This study proposes a workflow of game engine-based virtual wetland scene construction for the rapid modeling of virtual wetland scenes. The virtual wetland scene construction work utilized Poyang Lake as the primary research area. It integrated unmanned aerial vehicle data collection technology and geographic information technology with 3D (three-dimensional) modeling of wetland elements and scene program modeling of the game engine to complete the construction and dynamic development of virtual wetland scenes. In addition, it used various virtual reality technologies to display the virtual wetland scene. The virtual scene of Poyang Lake combined with actual data was more realistic and had higher simulation. In reality, the digital wetland scene of Poyang Lake realizes multiple forms of virtual experience and provides users with a profoundly immersive virtual experience. This comprehensive virtual scene workflow in the study can serve as a technical resource for building 3D scenes. It can also provide a technical reference for the digital twin watershed project of Poyang Lake, which has practical application value. [ABSTRACT FROM AUTHOR]

Earthquakes significantly impact societies and economies, underscoring the need for effective search and rescue strategies. As AI and robotics increasingly support these efforts, the demand for high-fidelity, real-time simulation environments for training has become pressing. Earthquake simulation can be considered as a complex system. Traditional simulation methods, which primarily focus on computing intricate factors for single buildings or simplified architectural agglomerations, often fall short in providing realistic visuals and real-time structural damage assessments for urban environments. To address this deficiency, we introduce a real-time, high visual fidelity earthquake simulation platform based on the Chaos Physics System in Unreal Engine, specifically designed to simulate the damage to urban buildings. Initially, we use a genetic algorithm to calibrate material simulation parameters from Ansys into the Unreal Engine's fracture system, based on real-world test standards. This alignment ensures the similarity of results between the two systems while achieving real-time capabilities. Additionally, by integrating real earthquake waveform data, we improve the simulation's authenticity, ensuring it accurately reflects historical events. All functionalities are integrated into a visual user interface, enabling zero-code operation, which facilitates testing and further development by cross-disciplinary users. We verify the platform's effectiveness through three AI-based tasks: similarity detection, path planning, and image segmentation. This paper builds upon the preliminary earthquake simulation study we presented at IMET 2023, with significant enhancements, including improvements to the material calibration workflow and the method for binding building foundations. [Display omitted] • RESenv boosts earthquake sim realism using Unreal Engine. • New calibration method improves building fracture accuracy. • Real earthquake data integrated for dynamic simulations. • Automated workflows streamline AI and robotics training. [ABSTRACT FROM AUTHOR]

Today, unmanned systems take on tasks in many areas and successfully fulfill these tasks. However, since these unmanned systems fly autonomously, they need to know both their surroundings and their location. Thanks to the Simultaneous Localization and Mapping (SLAM) method, it is a method that provides an advantage in estimating its location in this environment by instantly obtaining environmental information. However, this method is commonly used for unmanned systems flying at low speeds. In this study, Visual Simultaneous Localization and Mapping(vSLAM) technique is simulated for highspeed flying systems with the help of MATLAB 2021b Simulink UAVToolbox and Unreal Engine v4.25 running on Windows. In this implementation, the photorealistic simulation scenario was produced using Unreal Engine v4.25 and the simulation was carried out via MATLAB Simulink. In this simulation, the ORB-SLAM2.0 algorithm which is camera based vSLAM approach was run with the help of the images obtained from the cameras, and the simulation was successfully carried out at different speed, altitude and paths. It has been observed that vSLAM algorithm can be executed for high speed unmanned systems which is the purpose of simulations. [ABSTRACT FROM AUTHOR]

The elevation of Synthetic Biology from single cells to multicellular simulations would be a significant scale-up. The spatiotemporal behavior of cellular populations has the potential to be prototyped in silico for computer assisted design through ergonomic interfaces. Such a platform would have great practical potential across medicine, industry, research, education and accessible archiving in bioinformatics. Existing Synthetic Biology CAD systems are considered limited regarding population level behavior, and this work explored the in silico challenges posed from biological and computational perspectives. Retaining the connection to Synthetic Biology CAD, an extension of the Infobiotics Workbench Suite was considered, with potential for the integration of genetic regulatory models and/or chemical reaction networks through Next Generation Stochastic Simulator (NGSS) Gillespie algorithms. These were executed using SBML models generated by in-house SBML-Constructor over numerous topologies and benchmarked in association with multicellular simulation layers. Regarding multicellularity, two ground-up multicellular solutions were developed, including the use of Unreal Engine 4 contrasted with CPU multithreading and Blender visualization, resulting in a comparison of real-time versus batch-processed simulations. In conclusion, high-performance computing and client–server architectures could be considered for future works, along with the inclusion of numerous biologically and physically informed features, whilst still pursuing ergonomic solutions. [ABSTRACT FROM AUTHOR]

As a part of "The Vltava River" project, it was necessary to create a visualisation of the historic Vltava River valley before the construction of the so-called Vltava Cascade (nine dams built in the Vltava River basin between 1930 and 1992). Vectorisations of the Imperial Obligatory Imprints of the Stable Cadastre, and a terrain model created from contour lines from the State Map 1:5000-Derived (SMO-5), prepared in an earlier phase of the project, were used as a basis for this visualisation. Due to the extent of the modelled area, which is approximately 1670 km2, and the available underlying data realistically usable for the visualisation, mainly procedural modelling with the use of the CGA shape grammar was chosen for the creation of 3D objects. These procedurally created 3D models were completed with more detailed models of landmark buildings created in CAD. The outcomes were used to establish a virtual reality (VR) application in the Unreal Engine software. The results are a 3D scene created in a form corresponding approximately to the state of the Vltava River valley in the 19th century, which is available for viewing via a web application, and a VR scene used for demonstration at exhibitions. [ABSTRACT FROM AUTHOR]

• The development and presentation of forest digital twin (FDT). • The forest digital twin is feasible in two-way forest management practices. • A focus on how human–computer interaction enhances FDT performance. • Decision-making feedback could develop the potentiality of FDT. Existing forest digitization studies focus on one-way forest management practice visualization simulation, lacking decision-making feedback and virtual-real interaction synchronization. This paper presents the vision of the forest digital twin paradigm. We construct a forest digital twin to explore a new digital carrier of forest resources using remote sensing data, forest inventory data, the Cesium Digital Earth Engine, forest planning theory and parametric 3D modeling technology. The two-way interaction and thinning experiments showed that the forest digital twin could provide a novel pattern for in-depth analysis of forest spatial structure, individual tree dynamic growth and human-digital twin interaction effects. The successful recognition rate in matching the forest structure seen on real forest structure images with the forest digital scene was 91.3%, indicating that the forest digital twin can characterize the real forest structure significantly. The prediction accuracy of the multi-grade growth model integrating the Bayesian method for DBH, H was more than 90.4%. In addition, ASS-FDT interaction is superior to the assessors (ASS) and forest digital twin (FDT) for stand spatial structure overall optimization. The multi-dimensional stand spatial structure index (F-index) increased by 22.82%. The constructed forest digital twin model shows superior performance in optimizing the stand growth model and enhancing the overall stand spatial structure under the decision-making feedback and real-time interaction strategies. The automatic operation pattern provides a user-friendly forest management practice solution. [ABSTRACT FROM AUTHOR]

The indoor cartography is one of the newest branches of cartography. There is a high probability that the next few years will bring significant development of BIM systems, indoor navigation applications and building management systems (including energy optimisation and security assurance). To achieve these goals, appropriate building models are needed, including cartographic models understood as a kind of map. Tens of thousands of models are now being created worldwide, which is arguably a growing trend. However, research in this area is still relatively scarce. It is not easy to find guidance on data generalisation, the principles of using colours and patterns, the scope of content or how to develop thematic maps. The theory of cartography in this area is still developing. Therefore, according to the authors, further intensification of research in this area is needed. To this end, the concept of a laboratory to support research in the field of indoor cartography has been developed. [ABSTRACT FROM AUTHOR]

The recording and simulation data of forest landscapes are massive, high-dimensional, and abstract, requiring intuitive representation. 3-D visualization is an efficient tool to comprehend possible landscape changes generated by real-world or forest landscape models. Based on current advantages of game engines (realism and convenience), we developed a platform for 3-D visualization of forest landscapes (FLV). FLV streamlines multiple software and programming languages to break barrier between geographic data and game engine and transforms outputs of forest landscape models into visualization parameters. Compared with previous 3-D visualizations, FLV has better realism, efficiency, and navigation. We used simulation data of post-volcanic eruption forest landscape recovery in Changbai Mountain as a case study and demonstrated functionalities of FLV. FLV can visualize seamlessly from individual tree to forest stand and landscape scales, and from individual year to decades and centuries temporal scales. It offers potential solutions for the digital representation of complex environmental change. • Development and application of a 3-D forest landscape visualization platform. • The platform has high realism and efficiency, friendly interaction, and versatility. • The platform has been applied to post-volcanic eruption forest landscape visualization. • Provides an intuitive and stereoscopic visualization solution for the dynamics of the forest landscape in time and space. [ABSTRACT FROM AUTHOR]

BIM, gamification, and Virtual Reality applications are more often used to serve the interests of Design for Manufacture and Assembly (DfMA). This paper presents a comprehensive study to exploit these technologies' innovative approaches and capabilities. The study is specifically adopted to implement small and medium-size architectural and construction practices with a limited budget and time dedicated to visualisation creation. The collected evidence proved that a game-like platform combined with BIM could provide simplified data delivery to a client, leading to customer satisfaction, confidence and increased sales. The designed workflow and templates were tested in the case study of a small self-build construction company. The staff was trained to provide BIM data correctly and use supplied game templates. The case study demonstrated that automation of the VR House Configurator creation is achievable. The study's outcome is an integrated solution to regenerate BIM models in the game environment and utilise the house configurator's organised furniture library and costing interface. Furthermore, the usability tests confirmed the applicability, practicability, and validity of the developed framework and tools to deal with the revealed challenges in the self-build sector. Finally, the research provided a fresh approach for the companies in the sector, a step-by-step guide for implementing the innovative changes, and detailed descriptions of the methodologies and workflows. • A novel BIM, VR, and DfMA framework is developed to streamline the self-build design process • The designed workflow and templates were tested in the case study of a small self-build construction company • The BIM, VR and DfMA based design interface implements the integrated design and customization strategy • Enhancing design quality and reducing potential reworks in manufacturing, assembly & construction fields through automation • Optimizing existing collaboration workflow in BIM standards through making direct link with client in the design process [ABSTRACT FROM AUTHOR]

More and more cities are evolving into smart cities, increasing their attractiveness, energy efficiency, and users' satisfaction. Lighting systems play an important role in the evolution process, thanks to their ability to affect city life at night along with people's mood and behaviour. In this scenario, advanced lighting design methods such as virtual reality (VR) became essential to assess lighting systems from different points of view, especially those linked with the city users' expectations. Initially, the review highlights a list of objective and subjective parameters to be considered for the lighting design of three main city areas/applications: roads, green areas and buildings. Besides, the state-of-art in using VR for outdoor lighting design is established. Finally, the Unreal game engine is used to analyse the ability of VR to take into account the lighting parameters, not yet investigated in current literature and to highlight the VR potential for augmenting lighting design. The results confirm the benefit of using VR in lighting design, even if further investigations are needed to establish its reliability, especially from the photometrical point of view. [ABSTRACT FROM AUTHOR]

We present a new interactive computational virtual reality (VR) visualization framework for geophysical Big Data and models for the development of immersive collaborative virtual reality applications with a focus on targeted processing and interaction of Big Data. The framework includes a high-performance scalable persistent storage solution for the spatial analysis of Geospatial Information System (GIS), which uses an engine based on efficient in-memory computing. To more effectively visualize and interact in a VR environment, a machine learning algorithm library is used for compressing and extracting visual data. The framework supports mainstream rendering engines and VR hardware. The framework is extensible, customizable, cross-platform, and it is based only on open source tools. A workflow was introduced, and the geophysical data visualization and interaction effects were demonstrated by taking the abyss data of the Mariana Trench as example. • A new virtual reality visualization framework developed for geophysical big data processing, visualization and interaction. • The framework includes a high-performance scalable persistent storage solution for the spatial analysis of GIS. • The framework supports mainstream rendering engines and VR hardware. • The framework is extensible, customizable, cross-platform, and it is based only on tools with source tools. • A workflow was introduced by taking the abyss data of the Mariana trench as example. [ABSTRACT FROM AUTHOR]