TY - GEN
T1 - Harnessing Unreal Engine for the Development of Extended Reality Platforms for Remote Building Management
AU - Akinshipe, Olushola
AU - Aigbavboa, Clinton
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
PY - 2026
Y1 - 2026
N2 - In the current era of digital transformation within the built environment, Extended Reality (XR) technologies offer new ways to manage buildings remotely. This study explores and justifies the use of Unreal Engine as a suitable environment for developing XR applications for remote building monitoring and control. Unreal Engine’s real-time rendering capabilities, advanced physics simulation, Blueprint visual scripting, and support for multi-user collaboration make it a compelling choice for engineering realistic, interactive, and data-driven virtual environments. The study presents a practical case study in which a prototype XR platform was designed and created using Unreal Engine to simulate and monitor building operations. The platform integrates architectural models and live IoT sensor data to create an XR platform, enabling users to interact with systems. The study established some key insights from the development process. This includes the usefulness of Blueprint scripting for non-programmers, the importance of real-time collaboration tools, and the value of photorealistic rendering in boosting multiple stakeholder engagement. Findings from the study suggest that Unreal Engine XR platforms can be useful in varying degrees of complexity, from a simple tool for visualisation to comprehensive decision-making and support systems. The study recommended that Unreal Engine can be used more in implementing smart building initiatives. Also, the industry will benefit from further research into long-term use, scalability, and integration with IoT and AI technologies. Ultimately, this study reinforces the possibility of the engine’s role in supporting smarter, more connected, and more responsive building environments.
AB - In the current era of digital transformation within the built environment, Extended Reality (XR) technologies offer new ways to manage buildings remotely. This study explores and justifies the use of Unreal Engine as a suitable environment for developing XR applications for remote building monitoring and control. Unreal Engine’s real-time rendering capabilities, advanced physics simulation, Blueprint visual scripting, and support for multi-user collaboration make it a compelling choice for engineering realistic, interactive, and data-driven virtual environments. The study presents a practical case study in which a prototype XR platform was designed and created using Unreal Engine to simulate and monitor building operations. The platform integrates architectural models and live IoT sensor data to create an XR platform, enabling users to interact with systems. The study established some key insights from the development process. This includes the usefulness of Blueprint scripting for non-programmers, the importance of real-time collaboration tools, and the value of photorealistic rendering in boosting multiple stakeholder engagement. Findings from the study suggest that Unreal Engine XR platforms can be useful in varying degrees of complexity, from a simple tool for visualisation to comprehensive decision-making and support systems. The study recommended that Unreal Engine can be used more in implementing smart building initiatives. Also, the industry will benefit from further research into long-term use, scalability, and integration with IoT and AI technologies. Ultimately, this study reinforces the possibility of the engine’s role in supporting smarter, more connected, and more responsive building environments.
KW - Augmented Reality (AR)
KW - Building management
KW - Extended Reality (XR)
KW - Immersive technologies
KW - Unreal engine
KW - Virtual Reality (VR)
UR - https://www.scopus.com/pages/publications/105021838586
U2 - 10.1007/978-3-032-07992-3_34
DO - 10.1007/978-3-032-07992-3_34
M3 - Conference contribution
AN - SCOPUS:105021838586
SN - 9783032079916
T3 - Lecture Notes in Networks and Systems
SP - 508
EP - 522
BT - Proceedings of the Future Technologies Conference, FTC 2025, Volume 4
A2 - Arai, Kohei
PB - Springer Science and Business Media Deutschland GmbH
T2 - Future Technologies Conference, FTC 2025
Y2 - 6 November 2025 through 7 November 2025
ER -