# PROSIM in the Cloud: Remote Automation Training Platform with Virtualized Infrastructure
## 2 State of the Art  
With reference to the preliminary description of our system from the introduction, a parallel development using a similar concept for a web-based front-end e-learning approach for various systems such as DC-motor and three-tank plant is presented in [4; 5]. Detailed mathematical modelling for the plants is described together with their discretized implementation. The control design is initially validated in MATLAB and subsequently ported in a backed web application. The solution is readily accessible via the internet on end-user devices such as desktops, laptops and tablet PCs. Integration with the control hardware, namely a Siemens S7-1200 family PLC is carried out by means of an Ethernet data-acquisition hardware. TCP/IP communication allows the access to the coupler while physical signals such as analog and digital inputs and outputs are conveyed to the PLC system through wires. Control performance is illustrated comparatively between the simulation approach and the e-learning discretized plant model with physical hardware controller using typical metrics such as steady-state error, settling time and overshoot. Additionally, for the more complex three-tank model simulation an enhanced functionality is provided that allows local storage of the experiment files by the students on a dedicated server for evaluation and replicability purposes. Relevant related works in the field of (virtualized) e-learning and process simulations in real scenarios that also include hardware modules and components are discussed next, to establish the scientific context and relevance of our contributions. In [6], a web-based solution for student training is described, which revolves around a web application together with RESTful services for data and command exchanges. The system is applicable for discrete manufacturing processes such as flexible assembly lines with a modular software architecture. Validation with the real hardware manufacturing stations is achieved through a dedicated S1000 RTU gateway unit. The two versions, connected to the physical line and to the simulator via TCP/IP communication can be operated in parallel in order to compare the accuracy of the simulation and observe the real behavior of the system. Several considerations are discussed from the point of view of the students which enables safe, remote operation of laboratory installations. In [7], the interoperability between industrial-grade automation equipment and low-cost generic purpose hardware is discussed. The authors describe an application that enables PLC code-testing and SCADA application development for students on prototype plants using an Arduino microcontroller module as signal interface. State machines are used to describe the physical process based on which the control logic is subsequently implemented and tested. Modelling and design for AR/VR applications of industrial automation simulations is presented by [8]. The authors acknowledge the emergence of rich, immersive, multimedia technology with direct application in industrial process modelling for digital twin engineering. This in turn requires suitable training methodologies. The main contributions involve the addition of human-robot interaction in the case of collaborative robots, a large set of tasks and a flexible design that allowsthe decoupling of the simulator-supporting architecture from the simulation applications. The framework defines modules and their integration through interfaces and associated UML models. A state manager module coordinates the concurrent and sequential operation of various defined tasks and subtasks. Examples are provided in aircraft assembly, high-voltage cell and machinery tool operations. Enabling technologies include JSON for process definitions, C# for software implementation alongside the Unity3D engine for environment generation, visualization and interaction.