Digital Twin for Safety and Security: Perspectives on Building Lifecycle

Abstract

As digital twins are gaining importance in various industries, research on their impact, use cases, and implementation in the field of construction is accelerating. In this study, we examine the impact of digital twins on building safety and security throughout their lifecycle, utilizing two state-of-the-art use cases for fire and anomaly detection. The solution employs advanced sensors, 3D visualizations for detecting safety and security threats, and data analysis to predict potential future threats. Using the data that was collected over a seventeen-month period, we present an implementation architecture for safety and security digital twins in buildings, explore the benefits and shortcomings of such a system, and discuss the learnings applicable to different lifecycle stages of a building. This paper contributes to the creation and study of a digital twin for fire safety, analyzing its performance using two real-world use cases and reporting the implementation results. Additionally, we extrapolate the learnings from the use phase of a facility to other lifecycle phases of buildings and facilities.INDEX TERMS Digital twin, building lifecycle management, fire safety, safety and security in buildings.

Next Generation Computing and Communication Hub for First Responders in Smart Cities

“…Digital twins have been applied to various problems in smart cities, such as creating 3D representations of smart city entities, incorporating time-series and historical data, heatmaps, geometries, and shapes related to traffic flows, bus routes/stops, and cycling paths [3]. This technology has also found applications in first responder tasks such as global wildfire prediction [50] and fire safety [75]; a guiding system for pedestrian emergency evacuation [47]; and cognitive personalized systems of smart city [76]. Digital twin methodology, including model-and twin-enablingtechniques (e.g., physical-to-virtual and virtual-to-physical techniques), as well as perspectives on the trajectory of digital twin technology over the next decade, can be found in [70,71].…”

Digital-Twin-Based Fire Safety Management Framework for Smart Buildings

“…Furthermore, DTs utilize AI tools, such as machine learning (ML) and deep learning (DL), to organize and analyze data effectively in real time. This enables various functionalities, including condition monitoring, environmental learning, system failure prediction, real-time feedback, and bi-directional information integration throughout the entire lifecycle of the asset [21,22].…”

“…Recently, researchers have made significant progress in the development of DT technologies and tools for fire safety [22][23][24]. For instance, Jiang et al [23] proposed a system that combines DT technology, semantic web technologies, and IoT data to enable the dynamic monitoring and predictive operation of fire protection systems.…”

“…This system integrates domain knowledge, BIM information, and IoT data to enhance the effectiveness of building fire protection measures. Khajavi et al [22] proposed a framework for implementing DT throughout a building's lifecycle. They utilized sensor packages, 3D visualization, and AI techniques to detect and predict potential fire threats in buildings.…”

Residents' satisfaction of property management mobile applications: a study in the context of strata property in Kuala Lumpur, Malaysia

“…Mobile applications for property management serve as effective tools for managing facilities, streamlining facility management processes and ensuring properties are well-maintained for residents (Burgess and Quinio, 2018). By incorporating mobile-based applications technology in property management, the security of residential properties can respond to security incidents swiftly, ultimately enhancing the safety and security of residents (Khajavi et al, 2023). The mobile technology usage via application for managing visitors are effective, allowing property managers to digitally record visitors' data, and streamline the process effective (Khokhariya et al, 2022).…”