Process tomography is a typical non-intrusive visual sensing technique for industrial process perception. It overcomes the limitations of traditional point measurement methods by enabling real-time, undisturbed spatial visualization of internal flow fields, effectively addressing common industrial monitoring challenges such as invisible process states and unmeasurable transient flow behaviors. Long-term systematic research in this field has formed a complete technical system covering multi-modal sensing, high-speed data acquisition and intelligent image reconstruction, supporting robust industrial monitoring applications. With the rapid development of industrial intelligence, traditional tomographic technologies are constrained by limited imaging resolution and poor adaptability to complex operating conditions. The integration of intelligent algorithms significantly improves imaging quality, anti-interference capability and dynamic perception performance. Intelligent process tomography can accurately capture transient flow structures and evolving flow characteristics, realizing automatic flow regime identification, dynamic condition analysis and abnormal state early warning for industrial fluid systems.

This special session focuses on advanced theories, key technologies and industrial applications of intelligent process tomography. It aims to provide a high-level platform for academic and industrial communities to share cutting-edge research, and promote the development and practical deployment of intelligent flow condition monitoring technologies. This special session invites original contributions aligned with the scope of IMEKO TC6, TC9, TC10, TC19, TC20, TC21.

Relevant topics include, but are not limited to:

• Novel sensors and hardware systems for multi-modal process tomography;
• Intelligent reconstruction algorithms and imaging optimization methods;
• Multi-modal sensing fusion for complex industrial flow monitoring;
• High-speed tomographic imaging for transient flow characterization;
• Intelligent flow regime recognition and flow feature analysis;
• Abnormal flow diagnosis and early warning based on tomographic imaging;
• Signal processing and uncertainty evaluation for tomographic monitoring;
• Real-time visualization and edge intelligent monitoring frameworks;
• Industrial verification and engineering applications of tomography systems.

All submissions will undergo rigorous peer review. Accepted papers are expected to present original and innovative advances in intelligent process tomography and industrial flow condition monitoring with practical engineering significance.