Faheem Muhammad, Butt Rizwan Aslam
Department of Computer Engineering, Abdullah Gul University, Kayseri, 38080, Turkey.
Department of Electronics Engineering, NED University, Karachi 75270, Pakistan.
Data Brief. 2022 Mar 9;42:108026. doi: 10.1016/j.dib.2022.108026. eCollection 2022 Jun.
The Industry 4.0 revolution is aimed to optimize the product design according to the customers' demand, quality requirements and economic feasibility. Industry 4.0 employs advanced two-way communication technologies for optimizing the manufacturing process to increase the sales of the products and revenues to cope the existing global economy issues. In Industry 4.0, big data obtained from the Internet of Things (IoT)-enabled industrial Cyber-Physical Systems (CPS) plays an important role in enhancing the system service performance to boost the productivity with enhanced quality of customer experience. This paper presents the big datasets obtained from the Internet of things (IoT)-enabled Optical-Wireless Sensor Networks (OWSNs) for optimizing service systems' performance in the electronics manufacturing Industry 4.0. The updated raw and analyzed big datasets of our published work [3] contain five values namely, data delivery, latency, congestion, throughput, and packet error rate in OWSNs. The obtained dataset are useful for optimizing the service system performance in the electronics manufacturing Industry 4.0.
工业4.0革命旨在根据客户需求、质量要求和经济可行性来优化产品设计。工业4.0采用先进的双向通信技术来优化制造过程，以增加产品销量和收入，应对现有的全球经济问题。在工业4.0中，从支持物联网（IoT）的工业网络物理系统（CPS）获得的大数据在提高系统服务性能以提升生产力和增强客户体验质量方面发挥着重要作用。本文展示了从支持物联网（IoT）的光无线传感器网络（OWSNs）获得的大数据集，用于优化电子制造工业4.0中的服务系统性能。我们已发表工作[3]的更新后的原始和分析大数据集包含五个值，即OWSNs中的数据传输、延迟、拥塞、吞吐量和分组错误率。所获得的数据集对于优化电子制造工业4.0中的服务系统性能很有用。
