Discrete-event simulation of an irrigation system using Internet of Things



Digital Manufacturing, Internet of Things, Smart Farming


Agricultural water consumption represents 69% of all freshwater used on the planet. In addition, it is necessary to increase food production by 50% by 2050. The use of Internet of Things platforms to carry out the sensing and monitoring of the agricultural environment is increasingly present in the literature. One of the difficulties that such platforms face is to validate the platform's operation in different irrigation systems, as it is often necessary for specialists to work in the connection of sensors and actuators that already exist on farms or that are defined in the design of such systems. Within this context, a discrete-event simulation of an irrigation system integrated into an Internet of Things platform was developed in this work. The digital manufacturing software Plant Simulation was used to perform the discrete event simulation. An OPC UA server establishes real-time communication between the Internet of Things platform and the simulation software. Thus, farmers may verify, in real-time, how a given irrigation prescription, sent by the IoT platform, takes place in the irrigation system.


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Author Biographies

Rafael Gomes Alves, Eletrical Engineering Department, Centro Universitário FEI

Graduated in Mechanical Engineering from Centro Universitário FEI (2017) and got his master's degree in Mechanical Engineering from Centro Universitário FEI (2020). He is currently pursuing a PhD in electrical engineering with an emphasis on artificial intelligence applied to automation and robotics. He has worked on the Smart Water Management Platform (SWAMP) project. His topics of interest are internet of things, digital twins, artificial intelligence and urban agriculture.

Rodrigo Filev Maia, Deakin University

He has received his doctorate from Universidade de São Paulo - Escola Politécnica (2010). He is a Senior Research Fellow at Deaking University, working with automation and machine learning to improve irrigation outcomes inexperimental and commercial farms. He has done research for the European projects INSTINC (FP6),BELIEF (FP6), SAMBA (FP7), eMundus (ErasmusMundus) and SWAMP (Horizon 2020), as well asin UK (Netwon Funds) and Agrifutures and CRDCin Australia. Current investigation interests include the impact of technology and water and labor savings, as well as impacts in farm security due to data harvest and automatic control.

Fabio Lima, Centro Universitário FEI

He has received his doctorate from Universidade de São Paulo - Escola Politécnica (2010). He is the coordinator of the Digital Manufacturing laboratory at Centro Universitário FEI. He conducts research related to Digital Manufacturing, Systems Automation and Advanced Manufacturing(Industry 4.0). He is a scientific advisor to FAPESP and a member of the IEEE Industrial Electronics Society.


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How to Cite

Gomes Alves, R., Filev Maia, R., & Lima, F. (2022). Discrete-event simulation of an irrigation system using Internet of Things. IEEE Latin America Transactions, 20(6), 941–947. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/5920