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AI- and Security-Empowered End-Edge-Cloud Modular Platform in Complex Industrial Processes: A Case Study on Municipal
Jian Tang1,2, Tianzheng Wang1,2, Hao Tian1,2
1School of Information Science and Technology, Beijing University of Technology, Beijing 100124, China.
This study introduces the AI- and security-empowered end-edge-cloud modular platform (AISE3CMP) to optimize complex industrial processes. The platform ensures secure data transmission and efficient AI integration, bridging the gap between research and industrial application.
Area of Science:
- Industrial Process Optimization
- Artificial Intelligence in Engineering
- Cyber-Physical Systems
Background:
- Complex industrial processes (CIPs) face challenges in stable optimization due to unclear mechanisms, fluctuating conditions, and regulations.
- A gap exists between academic AI algorithms and their practical industrial deployment.
- Existing platforms lack robust security and integration efficiency for CIPs.
Purpose of the Study:
- To introduce the AI- and security-empowered end-edge-cloud modular platform (AISE3CMP).
- To bridge the gap between AI research and industrial application in CIPs.
- To enhance optimization, control, and data security in industrial settings.
Main Methods:
- Developed a modular platform (AISE3CMP) with four integrated systems: whole-process AI modeling, end-side AI decision-making, edge-side AI control, and cloud-side AI optimization.
- Deployed a data isolation collection module at a municipal solid waste incineration (MSWI) power plant for real-world data collection.
- Validated functionality and effectiveness using developed software and hardware.
Main Results:
- Demonstrated efficient and reliable signal transmission between platform systems.
- Confirmed the platform's capability to meet computational demands for AI-based optimization and control.
- AISE3CMP features a dual-security transmission mechanism and modular design for enhanced integration.
Conclusions:
- AISE3CMP is the first portable, end-to-end cloud platform with a dual-layer security mechanism for CIPs.
- The platform effectively addresses data transmission security but requires further enhancement in cloud-side protection and end-side operational safety.
- Future research directions include industry-specific large language model development through multi-region data sharing.
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