# Toward Sustainable Development: Exploring the Value and Benefits of Digital Twins
## 2 Background  
It is widely accepted that the concept of a \"digital twin\" originated from the National Aeronautics and Space Administration (NASA) in the 1960s, where it was referred to as a \"living model\" of the Apollo mission [19]. The term itself was first used by [PERSON] in 2002 [20]. According to [PERSON] and [PERSON], a Digital Twin (DT) is defined as \"a virtual representation of a physical system (and its associated environment and processes) that is updated through the exchange of information between the physical and virtual systems\" [21]. [PERSON] [22] classified Digital Twin use cases along three prevailing dimensions:  
1. The hierarchical level at which the Digital Twin is deployed includes six levels (Informational, Component, Product, Process, System, and Multi-system). 2. The life-cycle phase in which the Digital Twin is deployed involves six phases (Design, Build, Operate, Maintain, Optimize, and Decomposition). 3. The use of the Digital Twin refers to seven uses (Digitize, Visualize, Simulate, Emulate, Extract, Orchestrate, and Predict). In total, 252 potential use cases are defined by combining the seven most common uses, six hierarchical levels, and six phases. It seems quite evident that researchers and practitioners have so far have documented and classified a plethora of use cases of the Digital Twin in many different sectors, introducing different sets of criteria, ranging from the general to the very technical [23]. In general, the architecture of a Digital Twin in terms of its modeling can be divided into three main layers [24, 25]:  
* The physical layer, which encompasses the physical entities of the system, environment, and processes;
* The virtual layer, which involves virtual models of the physical entities at different levels of abstraction;
* The interconnection layer, which serves as the bidirectional data proxy between the physical and virtual layers. From the perspective of a solution vendor, the first physical reality layer is independent and is the object of observation, analysis, and understanding; while the remaining two dependent layers are the object of modeling, implementing, and testing. Four core tech nologies typically employed in modeling and developing a DT are Artificial Intelligence (AI), Big Data (BD), Internet-of-Things (IoT), and mobile/wireless networks [26]. AI aims to empower a Digital Twin with capabilities of perceiving, synthesizing, and inferring information to learn and adapt to new situations and circumstances [27]. Some researchers and practitioners argue that AI is an imperative component for some DT applications, such as autonomous driving systems [28] and additive manufacturing [29]. In particular, machine learning algorithms are commonly used to explore data for hidden patterns [30], detect anomalies [31], make predictions [32], or construct classifiers [33]. Big Data (BD) spans over the \"high\" seven Vs--namely, Volume, Velocity, Variety, Veracity, Variability, Visualization, and Value [34]. In short, Big Data refers to relatively larger, more complex data repositories [35], especially from new data sources [36]. For [PERSON] [37], the concept Big Data really means \"harvesting meaning from data\", which \"is coming in faster, from more sources, and in more varied formats than ever before\" [38]. In a practical sense [39], Big Data technology refers to a software utility designed to \"analyze process and extract information from extremely complex and large data sets which traditional data processing software could never handle\" [40]. The modern big data solutions available in the market are [41] Apache Hadoop [42], Apache Spark [43], and Hortonworks Data Platform (HDP) [44]. The term Internet of Things (IoT) is understood as \"the collective network of connected devices and the technology that facilitates communication between devices and the cloud, as well as between the devices themselves\" [45]. In general, IoT capacitates the Digital Twin model to support new intelligent services to connect and interact with physical objects [46].