Faculty of Mechanical Engineering and Aeronautics, Rzeszów University of Technology, 35-959 Rzeszów, Poland.
Faculty of Electrical and Computer Engineering, Rzeszów University of Technology, 35-959 Rzeszów, Poland.
Sensors (Basel). 2022 Mar 22;22(7):2445. doi: 10.3390/s22072445.
This article presents the results of research with the main goal of identifying possible applications of edge computing (EC) in industry. This study used the methodology of systematic literature review and text mining analysis. The main findings showed that the primary goal of EC is to reduce the time required to transfer large amounts of data. With the ability to analyze data at the edge, it is possible to obtain immediate feedback and use it in the decision-making process. However, the implementation of EC requires investments not only in infrastructure, but also in the development of employee knowledge related to modern computing methods based on artificial intelligence. As the results of the analyses showed, great importance is also attached to energy consumption, both in ongoing production processes and for the purposes of data transmission and analysis. This paper also highlights problems related to quality management. Based on the analyses, we indicate further research directions for the application of edge computing and associated technologies that are required in the area of intelligent resource scheduling (for flexible production systems and autonomous systems), anomaly detection and resulting decision making, data analysis and transfer, knowledge management (for smart designing), and simulations (for autonomous systems).
本文介绍了一项研究的结果，该研究的主要目的是确定边缘计算 (EC) 在工业中的可能应用。本研究采用了系统文献综述和文本挖掘分析的方法。主要研究结果表明，EC 的主要目标是减少传输大量数据所需的时间。通过在边缘分析数据，可以获得即时反馈，并将其用于决策过程。然而，实施 EC 需要不仅在基础设施方面进行投资，还需要在与人工智能为基础的现代计算方法相关的员工知识方面进行投资。正如分析结果所示，能源消耗也非常重要，无论是在正在进行的生产过程中，还是在数据传输和分析的目的方面。本文还强调了与质量管理相关的问题。基于分析，我们指出了进一步研究边缘计算及其相关技术在智能资源调度（用于灵活生产系统和自主系统）、异常检测和决策、数据分析和传输、知识管理（用于智能设计）以及模拟（用于自主系统）领域的应用方向。
