## 5 Results
In the context of smart cities, the general objective was to explore sustainable design using Digital Twin technology, GIS (Geographic Information System), and BIM (Building Information Modeling). The applicability of Digital Twins extends to related fields such as education, energy production, and the oil industry. This multi-faceted approach underscores the versatility of Digital Twin technology in enhancing urban planning, resource management, and environmental sustainability. Compared to previous studies examining the evolution of Digital Twins over several years, common elements such as DT definitions, research paradigms, and reference architectures were identified. This study, however, placed greater emphasis on highlighting the temporal evolution of DTs in research and their application across various fields, including PSSs (Product-Service Systems), CPS, smart cities, and medicine. A detailed classification of Digital Twins was sought to shape a holistic approach, focusing on identifying the advantages and limitations of DT usage from specialized literature. This study proposed a holistic approach to Digital Twin technology across various domains (PSS, CPS, medicine, and smart cities) to provide a comprehensive view of its potential contributions. By highlighting both the advantages and disadvantages of Digital Twin technology, this analysis offers valuable insights into its role in digital transformation. The selection of reference architectures and application frameworks in medicine and other fields provides a foundation for future research aimed at developing a general architecture for Digital Twins. This holistic vision encompasses defining the concept, identifying characteristics of a general architecture, and focusing on practical examples of DT applications, enhancing the understanding of its benefits and limitations. The integration of Digital Twin technology in the field of civil engineering, particularly in bridge health monitoring systems, offers significant advancements as evidenced by multiple studies. [PERSON] et al. [106] demonstrated the potential of Digital Twins to create virtual bridge models that enable simulation, prediction, and real-time health analysis by leveraging sensor data and artificial intelligence algorithms. This approach facilitates early problem detection, cost optimization, durability enhancement, and rapid interventions. [PERSON] et al. [107] introduced an innovative method for identifying rubber bearing deteriorations using Mean Squared Error (MSE) and Sailfish Optimization (SFO), which, when integrated into the Digital Twin framework, significantly boosts the safety and longevity of bridge infrastructure. [PERSON] et al. [108] highlighted the critical role of addressing missing sensor data in structural health monitoring, proposing advanced machine learning algorithms for accurate data recovery, essential for robust infrastructure monitoring. Furthermore, [PERSON] et al. [109] presented a novel method using DCNN-LSTM networks for modeling temperature-induced bearing displacement, demonstrating the highest prediction accuracy through the integration of elastic module data. These studies collectively underscore the transformative impact of Digital Twin technology in enhancing structural health monitoring, enabling precise, real-time evaluation, and optimizing maintenance strategies, thereby extending the lifespan and reliability of critical infrastructure. In the AECO sector, the integration of Digital Twin technology has been highlighted as essential for enhancing interoperability and collaboration among stakeholders. [PERSON] et al. [111] emphasized the need for detailed studies to identify platforms that facilitate these aspects, focusing on a common language for data acquisition, storage, transmission, and modeling. In preserving Built Cultural Heritage (BCH), Digital Twins not only utilize specialized simulation software but also apply predictive analyses through statistical methods and AI tools, requiring continuous interdisciplinary collaboration.