Key Challenges and Emerging Technologies in Industrial IoT Architectures: A Review

Area of Science:

• Computer Science
• Electrical Engineering
• Industrial Automation

Background:

• The Industrial Internet of Things (IIoT) is revolutionizing industrial processes through remote monitoring and intelligent analytics.
• Current adoption of full-stack IIoT solutions is nascent, presenting significant integration and operational challenges.
• The need for robust IIoT architectures is critical for seamless end-to-end system integration.

Purpose of the Study:

• To review and compare three prominent Industrial Internet of Things (IIoT) reference architectures.
• To present a state-of-the-art analysis of conceptual and experimental IIoT architectures.
• To identify key IIoT architectural requirements and evaluate how current designs address them.

Main Methods:

• Literature review and comparative analysis of existing IIoT reference architectures.
• Identification and categorization of critical IIoT architectural requirements.
• Examination of emerging technologies (e.g., edge/fog computing, blockchain, 5G, ML, WSN) applied in IIoT.

Main Results:

• Scalability, interoperability, security, privacy, reliability, and low latency are identified as primary IIoT architectural requirements.
• Current architectures leverage technologies like edge/fog computing, blockchain, SDN, 5G, Machine Learning, and WSN to address these challenges.
• A detailed discussion on the interplay between identified challenges and enabling emergent technologies.

Conclusions:

• Existing IIoT architectures show promise in addressing critical requirements through advanced technologies.
• Further research is needed to fully realize the potential of these technologies for robust IIoT integration.
• Opportunities for future research lie in optimizing the synergy between IIoT challenges and emergent technological solutions.