# Toward Sustainable Development: Exploring the Value and Benefits of Digital Twins
## 5 Discussion  
At present, we are witnessing the Fourth Industrial Revolution [81], and time is driven by digital transformation in the service and manufacturing sectors. Almost every industry, if not all, is currently subject to these changes--which are characterized by interconnectivity via digital tools [82, 83]--that promise to deliver affordable, smart, scalable, and reliable capabilities beyond physical limitations [84]. Future generations of computer systems (FGCs), particularly Digital Twins solutions, are expected to provide support not only to their users but also to their physical counterparts in economic, operational, and strategic domains. Clearly, the FGCs are not off-the-shelf technological products; as such, a variety of unprecedented challenges and issues have already been identified [85, 86, 87], both in terms of their development and deployment. This makes them one of the most complex and demanding endeavors to undertake. Therefore, the expected benefits should be treated with caution and considered over the long term. Collected information suggests that different technologies used to design and develop Digital Twin solutions have been implemented and integrated over time. There is an obvious role for hardware infrastructure, which is a major requirement for efficient data processing units as well as for the system as a whole. Another key component underpinning Digital Twin solutions is a digital definition of its counterpart, along with an attached information model. The last but not least component is a middleware that links physical and digital entities and exchanges data between them. However, combining all these components into one fully operational system is a complex and challenging process that carries additional risks to a deployment effort [88, 89, 90]. Thus, in addition to considering the  
Figure 2: The top 10 benefits of Digital Twin deployment. expected benefits of a DT deployment, it is also important to identify and assess potential threats and vulnerabilities to which the system may be exposed. Our findings are consistent with previous research that has explored the topic of Digital Twins. More generally, the domain of its applications spans many industries, including automotive, aerospace, construction, agriculture, mining, utilities, retail, healthcare, military, natural resources, and public safety sectors [91]. Secondly, since a DT is a theoretical notion and does not exist as such, and takes advantage of four technology pillars--Internet-of-Things [92], Cloud Computing [93], Artificial Intelligence [94], and Extended Reality (XR) [95]--it is able to deliver an added value, originating from the integration of the above pillars and their real-time collaboration. While the adoption of Digital Twin technology has grown significantly in recent years, with many successful application scenarios reported to date, several challenges and issues remain to be addressed. [PERSON] et al. [96] identified such challenges as cost control, data processing, security, and privacy, along with seamless integration of the physical and digital worlds, and integration with intelligent solutions. In the construction domain, [PERSON] et al. [97] claim that the process of deploying effective DT involves highly technical and complex steps. Digital Twin technology requires collecting and utilizing large amounts of data from multiple endpoints, each a potential vulnerability. In addition, employees may show a lack of interest due to concerns about job security, which can hinder adoption. Another significant challenge is the difficulty of integrating the various stakeholders in the construction industry to work as one team. While [PERSON] et al. [98] indicate that Digital Twin (DT) modeling involves physical modeling, virtual modeling, connection modeling, data modeling, and service modeling, on the other hand, such an approach implies several challenges. First, the digital model requires managing a large volume of data, including physical data, virtual data, and their integrated fusion data.