For studying operational and organizational systems, modeling and simulation tools are becoming increasingly relevant. It is possible to build a lot of systems and study their behavior, which saves a lot of effort, time, and cost, where it cannot or difficult to study its behavior in the real world. There are many frameworks to implement modeling and simulation using a computer. in this paper DEVS-Suite for discrete events is used to implement a simulation of cargo unloading problem which represents a study on estimating the optimal number of trucks and cranes required in process of unloading goods and according to some determinants. The duration of the simulation is one month which is equivalent to 43,200 minutes. Based on the performance measures that were adopted in this study, the optimal number of trucks and cranes is 5 out of three assumptions of 3, 5, and 10, where the work will be in a permanent state of work and high productivity.

Most fresh water is used in agriculture. There has been a constant interest in presenting systems and solutions that rationalize water resources in agriculture without reducing productivity. In contrast the solutions must improve production while utilizing less water. On the other hand, The Internet of Things is a prominent recent technology that provides various solutions in many disciplines, including agriculture and irrigation. This paper proposes an Internet-of-Things-based architecture for smart irrigation by developing a prototype with a controller unit, water pumps, and sensors. These systems monitor the soil's irrigation needs and determine the right amount based on sensor data. As these values are delivered through cloud computing to a user's mobile app, irrigation may be monitored and controlled from multiple angles. This comprises manual irrigation mode, automatic irrigation mode, and determine the right amount of irrigation based on sensor relationships.