Advancing Real-time Analytics in Industrial Internet-of-Things
摘要截稿:
全文截稿: 2024-04-30
影响因子: 2.816
期刊难度:
CCF分类: C类
中科院JCR分区:
• 大类 : 计算机科学 - 3区
• 小类 : 计算机:信息系统 - 3区
• 小类 : 工程:电子与电气 - 3区
• 小类 : 电信学 - 3区
Overview
The Industrial Internet-of-Things (IIoT) revolutionizes industry with advanced connectivity and real-time analytics, turning sensor data into immediate, actionable insights for better operations. Real-time analytics is key to preventing downtime and managing risks, but integrating it with IIoT involves challenges such as ensuring data integrity, meeting computational demands, securing the system, and overcoming network delays. Robust, efficient network design is essential for smooth data flow and overcoming these challenges is crucial for leveraging real-time analytics' full benefits in IIoT.
This special issue aims to provide a comprehensive exploration of real-time analytics in IIoT, its potential, challenges, and the innovative solutions emerging in the domain. Topics of interest include, but are not limited to:
Foundations of Instant Data Interpretation in IIoT
Edge and Fog Computing for Real-Time Insights in IIoT
Energy-Efficient Real-Time Analytics in IIoT
Low Latency and Robust Data Transfer Network Architectures for IIoT
Data Integrity and Reliability in Real-Time Data Streams
Privacy-Preserving Techniques for Real-Time Analytics in IIoT
Real-Time AI-Driven Decision-Making and Anomaly Detection in IIoT
Scalability in Large-Scale IIoT Real-Time Analytics
Timely and Reliable Data Services in IIoT
Integration of 5G and Beyond for Accelerated Analytics
Case Studies of Real-World Successes and Challenges in IIoT Real-Time Analytics
Guest editors:
Long Cheng, PhD
North China Electric Power University, Beijing, China
Anca Jurcut, PhD
University College Dublin, Dublin, Ireland
Qingzhi Liu, PhDWageningen University, Wageningen, Netherlands