Industrial Internet of Things (I2oT) gives more accessibility and reliability of the industrial systems. Thence, most industrial processes have been tended to be controlled and monitored through the Internet. The control design is an important requirement in the industrial processes. For a long time, there are two main types of controllers that have shown the effectiveness in the industrial control systems, the Proportional-Integral-Derivative (PID) controller and Model Predictive Control (MPC). PID and MPC are introduced to be designed for the control of the Double-tank System (DTS), which is one of the most important control systems in the industrial world. Genetic Algorithm (GA) is used for tuning the PID controller with an IAE performance index. MPC is designed using the state-space model of the system to get more information about the system during the optimization. Simulation results of the controllers are presented to realize the performances of the designed controllers. Node.js frameworks are developed to implement the algorithm of the PID and MPC controllers. Real-time implementation is taken place on the Node.js platform to manifest the best performance of the controllers in the real-time control system.