**1.3 Implementing digital twin**

Digital twin begins with procuring both static and dynamic knowledge. After gathering relevant information, a conceptual model or say, mathematical model is designed considering exchange of attributes between physical environment and virtual model. This model virtually represents the physical processes on which tests are performed with the help of experimental data. It is very important to analyze which data should come in and accumulated in the digital twin. For this purpose, physical attributes of the real world are collected with the help of sensors to measure critical inputs and execution of the desired adjustment takes place with the help of accurators. After specifying the data requirement, communication protocols (TCP/IP, Pub/Sub, ERP) are determined for smooth transmission of data. These connections are affirmed with the help of technologies like cloud computing, network communication and security. Data coming from different sources is collected, processed and then aggregated in the database along with the real time data. Then, the virtual model is created by modeling all the input and output factors. This virtual model is capable of getting real time data inputs from the physical environment. By effectively visualizing, monitoring and analyzing data, it enables stimulations to generate a feasible output leading to an efficient decision making [6, 7] (**Figure 2**).
