## 4 Analyses of the Applications of Digital Twin Models
### Digital Twin in Other Domains  
The variety of DTs and their applicability in different fields such as Smart Cities, Energy Production, Oil Industry, and education highlights the impact of this emerging technology, which contributes to development. Within this section, an example of the applicability of DTs is presented in the previously mentioned areas, starting from the modeling of urban infrastructures, optimizing energy production, reducing gas emissions, and exploring innovation in education. Figure 11 presents the number of articles specific to each domain due to the search for the concepts of \"Digital Twin in Smart Cities\", \"Digital Twin in Energy Production\", \"Digital Twin in Oil Industry\", and \"Digital Twin in Education\" in the databases. Figure 11: Digital Twin in various fields. From the point of view of education, with the pandemic generated by the emergence of COVID-19, the transition from traditional to online education was achieved, and with the help of artificial intelligence and DTs, configured learning frameworks were proposed, these being available in [90; 91; 92], based on the concepts of e-learning, mobile learning (m-learning), ubiquitous learning (u-learning), and smart learning (s-learning). In ref. [93], [PERSON] et al., highlighted the integration of the Digital Twin in the educational context, emphasizing the differences between technology-driven customization and human-centered personalized learning, given the promotion of a personalized learning policy in K-12 educational environments. The advancement of Digital Twin integration in the educational domain has coincided with the development of the Metaverse. Technology-driven customization, achieved through Digital Twin integration, supports quantification and power forms based on reference environments, generalizability, and standardized testing. In contrast, human-centered personalized learning does not involve standardization and generalization of involvement, being quantifiable and measurable. The use of the Digital Twin in personalized learning negatively affects the recognition of human relational involvement by teachers. Regarding the datasets provided by the Digital Twin, measures to reduce costs compared to organizing classes in the classroom have been discussed, a phenomenon that amplifies socio-economic disadvantages in the implementation of educational policies. In ref. [94], [PERSON] et al., developed an innovative pedagogical method through the integration of the Digital Twin, avatars, and generative Artificial Intelligence, considering this approach as a complement to traditional teaching. Thus, the focus has been placed on developing platforms that encourage constructivism and collaborative learning, also adopting a problem-solving oriented method. The experiment to validate the new method was conducted with the participation of medical students who attended learning sessions in the metaverse. The learning sessions were facilitated by a real teacher (in the form of an avatar), a digital clinical instructor, and an AI teacher, aiming to provide students with an efficient educational experience, taking into account both human-machine interaction and problem-solving abilities. In ref. [95], [PERSON] and [PERSON] emphasized that during the COVID-19 pandemic, universities with engineering programs encountered difficulties in conducting practical experiments. To address this situation, the organization of laboratory sessions was carried out by creating a Digital Twin for each experiment, using online applications and Augmented and Virtual Reality (AR/VR) technologies. Thus, the Digital Twin provided an efficient framework for laboratory experiments, offering students a synchronized 3D environment to facilitate interaction between the physical and virtual environments. Additionally, [PERSON] and [PERSON] noted that the greatest challenge lay in assessing and improving students' psychomotor skills. Also, in the realm of education, utilizing the Digital Twin and the NVIDIA Omniverse platform, [PERSON] et al.