Source code of the agent-based simulator of smart beds with Internet-of-Things for exploring big data analytics called ABS-BedIoT

This dataset contains the source code of an agent-based simulator (ABS) of smart beds with Internet-of-Things for exploring big data analytics called ABS-BedIoT. This ABS allows practitioner to simulate different types of sleeper that adopt different kinds of sleeping postures during the night. Each posture is composed of an orientation (i.e. frontal or lateral) and a pose (i.e. neck bent, body bent, spine S, and normal pose). The sleeper is tracked by a grid of pressure sensors of a smart bed.

Practitioners can test different ways of analyzing the big data from the simulated signals of the sensors of the smart bed. They can either implement a different kind of online analysis implementing another Analyzer agent, or analyze the big data logs generated by the simulator with an independent tool. This dataset includes some examples of the generated logs for each kind of implemented sleeper. The implemented sleeper kinds are bad sleeper, healthy sleeper and restless sleeper. However, practitioners can implement new kinds of sleepers by extending either the “Stochastic Sleeper Agent” class or the “Sleeper Agent” class.

The development of this ABS has followed the Process for developing Efficient ABSs (PEABS). The stochastic behavior of some agents are based on the Technique for developing ABS Apps and Online tools with Nondeterministic Decisions (TABASOND). The current simulator has been implemented with Unity 3D engine, version 5.5.1.

This dataset supports the research of the authors about ABS-BedIoT. The work about this dataset has been accepted for publication by the IEEE Access journal conditioned to certain changes.

If other researchers use the current dataset, they can credit the work of the authors by citing the upcoming article in the IEEE Access journal about ABS-BedIoT. In case the researchers just reuse some components related with either PEABS or TABSAOND, they can cite any of the corresponding articles.

Reference about ABS-BedIoT:

García-Magariño, I., Lacuesta, R., Lloret, J. (2017). Agent-based simulation of smart beds with Internet-of-Things for exploring big data analytics. IEEE Access, In Press.

References about TABSAOND and PEABS:

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.

本数据集包含了一款基于智能床物联网的智能体模拟器（ABS）的源代码，该模拟器旨在探索大数据分析，命名为ABS-BedIoT。此ABS允许实践者模拟夜间采取不同睡眠姿势的各类睡眠者。每种姿势由一个方向（即正面或侧面）和一个姿态（例如颈部弯曲、身体弯曲、脊柱S形和正常姿势）组成。睡眠者通过智能床的压力传感器阵列进行跟踪。实践者可以测试从智能床传感器的模拟信号中分析大数据的不同方法。他们可以实施一种新的在线分析，实现另一个分析智能体，或者使用独立工具分析模拟器生成的大数据日志。本数据集包含了一些实现睡眠者类型的生成日志示例。实现的睡眠者类型包括不良睡眠者、健康睡眠者和不安睡眠者。然而，实践者可以通过扩展“随机睡眠者智能体”类或“睡眠者智能体”类来实现新的睡眠者类型。该ABS的开发遵循了高效ABS开发流程（PEABS）。某些智能体的随机行为基于开发具有非确定性决策的ABS应用程序和在线工具的技术（TABASOND）。当前模拟器使用Unity 3D引擎，版本5.5.1实现。本数据集支持作者对ABS-BedIoT的研究。关于此数据集的工作已被IEEE Access期刊接受发表，但需进行某些修改。如果其他研究人员使用当前数据集，他们可以通过引用即将在IEEE Access期刊上发表的关于ABS-BedIoT的文章来认可作者的工作。如果研究人员仅重用与PEABS或TABSAOND相关的某些组件，他们可以引用任何相应的文章。关于ABS-BedIoT的参考文献：García-Magariño, I., Lacuesta, R., Lloret, J. (2017). 基于物联网的智能床的智能体模拟以探索大数据分析。IEEE Access，In Press。关于TABSAOND和PEABS的参考文献：García-Magariño, I., Palacios-Navarro, G., Lacuesta, R. (2017). TABSAOND：一种用于开发具有非确定性决策的智能体模拟应用程序和在线工具的技术。Simulation Modelling Practice and Theory，77，84-107。García-Magariño, I., Gómez-Rodríguez, A., González-Moreno, J. C., Palacios-Navarro, G. (2015). PEABS：一种开发高效智能体模拟器的流程。Engineering Applications of Artificial Intelligence，46，104-112。