Guest Editorial: Edge Intelligence for Next Generation Industrial IoT Applications

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.