Guest Editorial: Edge Intelligence for Next Generation Industrial IoT Applications

IF 1.3 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS

IET Networks Pub Date : 2025-07-04 DOI:10.1049/ntw2.70008

Varun G. Menon, Mainak Adhikari, Brij Bhooshan Gupta, Abhishek Hazra, Spyridon Mastorakis

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引用次数: 0

Abstract

The transformation of industrial systems through real-time analytics, autonomous control, and intelligent data acquisition has underscored the pivotal role of Industrial Edge Computing (IEC) in next-generation Industrial Internet of Things (IIoT) environments. By enabling decentralized processing close to data sources, IEC enhances responsiveness, supports latency-sensitive applications, and reduces the strain on centralized infrastructure. However, as IIoT ecosystems grow in scale and complexity, traditional edge solutions face increasing challenges related to device heterogeneity, dynamic network conditions, bandwidth constraints, and energy efficiency. This special issue explores emerging advancements in edge intelligence that address these pressing challenges. It brings together innovative research that leverages artificial intelligence, advanced communication technologies, and architectural innovations to improve the adaptability, resilience, and performance of edge-enabled industrial systems. The featured studies contribute novel techniques for real-time data processing, secure and efficient communication, and intelligent decision-making at the edge, all of which are essential for supporting industrial automation, predictive maintenance, and cyber-physical operations. Collectively, these contributions highlight the immense potential of edge intelligence to redefine the operational landscape of industrial systems. This issue is intended to support ongoing research and practical innovation in the evolving domain of edge-enabled IIoT technologies.

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嘉宾评论：下一代工业物联网应用的边缘智能

通过实时分析、自主控制和智能数据采集，工业系统的转型凸显了工业边缘计算（IEC）在下一代工业物联网（IIoT）环境中的关键作用。通过启用靠近数据源的分散处理，IEC增强了响应能力，支持对延迟敏感的应用程序，并减少了集中式基础设施的压力。然而，随着工业物联网生态系统的规模和复杂性的增长，传统的边缘解决方案面临着与设备异构、动态网络条件、带宽限制和能源效率相关的越来越多的挑战。本期特刊探讨了解决这些紧迫挑战的边缘智能的新进展。它汇集了利用人工智能、先进通信技术和架构创新的创新研究，以提高边缘启用工业系统的适应性、弹性和性能。这些特色研究为实时数据处理、安全和高效通信以及边缘智能决策提供了新技术，所有这些都是支持工业自动化、预测性维护和网络物理操作所必需的。总的来说，这些贡献突出了边缘智能在重新定义工业系统运营环境方面的巨大潜力。该问题旨在支持边缘IIoT技术不断发展的领域中的持续研究和实际创新。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IET Networks COMPUTER SCIENCE, INFORMATION SYSTEMS-

CiteScore

5.00

自引率

0.00%

发文量

审稿时长

33 weeks

期刊介绍： IET Networks covers the fundamental developments and advancing methodologies to achieve higher performance, optimized and dependable future networks. IET Networks is particularly interested in new ideas and superior solutions to the known and arising technological development bottlenecks at all levels of networking such as topologies, protocols, routing, relaying and resource-allocation for more efficient and more reliable provision of network services. Topics include, but are not limited to: Network Architecture, Design and Planning, Network Protocol, Software, Analysis, Simulation and Experiment, Network Technologies, Applications and Services, Network Security, Operation and Management.