Source code of the agent-based simulator called ABS-SmartComAgri about smart communication protocols in wireless sensor networks for debugging in precision agriculture

Published: 8 November 2017| Version 1 | DOI: 10.17632/mj974yrjw5.1
Iván García-Magariño,


The goal of this dataset is to provide the source code of the agent-based simulator (ABS) called ABS-SmartComAgri about smart communication protocols in wireless sensor networks for debugging in precision agriculture. This ABS allows network designers to define and simulate new smart communication protocols for wireless sensor networks in the context of agriculture. In particular, this ABS simulates an ecosystem with bugs, and one can test different strategies for fumigating the field through a grid of stations with sensors. These strategies should rely in the proper definition of the smart communication protocols among sensors for (a) saving energy, (b) maintaining the health of the crop, and (c) only using small amounts of pesticides. This ABS includes a user interface for interacting with the system and observing the final simulation state of the field. Developers can define smart communication protocol strategies by extending the "SensorAgent" class and overriding the methods "LiveSensor" and "ManageMsg". The implementations of these methods can invoke other predefined methods of the simulator for respectively (a) checking if a sensor is sending bugs, (b) fumigating, and (c) sending messages to other sensors. The development of this simulator followed the guidelines indicated by PEABS (the Process for developing Efficient ABSs). This simulator also uses nondeterministic decisions following the principles established in TABSAOND (the Technique for developing ABS Apps and Online tools with Nondeterministic Decisions). The presented simulator has been developed with the C# programming language and the Unity 3D engine version 5.5.1. This dataset supports the research of an article about ABS-SmartComAgri that has been submitted to a scientific journal for consideration for publication. Other researchers can credit this dataset by citing any of the articles of the authors related to this research. References of some articles related to this research: García-Magariño, I., Palacios-Navarro, G., Lacuesta, R. (2017). TABSAOND: A technique for developing agent-based simulation apps and online tools with nondeterministic decisions. Simulation Modelling Practice and Theory, 77, 84-107. García-Magariño, I., Gómez-Rodríguez, A., González-Moreno, J. C., Palacios-Navarro, G. (2015). PEABS: a Process for developing Efficient Agent-Based Simulators. Engineering Applications of Artificial Intelligence, 46, 104-112.


Steps to reproduce

Make sure you have installed Unity version 5.5.1. If you have not installed it, you can obtain any Unity version from its Download Archive web page. It may be compatible with other versions of Unity although this has not been tested. Download and unzip the “” file. Open the project of the unzipped folder from the Unity editor. Press the “Play” button to run the simulator. All the source code and other elements are accessible from the opened project.


Free Software, Agent-Based Technology, Debugging, Software Agent, Sensor, Agent-Based Modeling, Precision Agriculture, Multi-Agent Systems