IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA 2025)

The IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA 2025) is dedicated to all aspects of computational intelligence, virtual environments and human-computer interaction technologies for measurement systems and related applications.

Topics

• Intelligent measurement in Internet-of-Things and Cyber-Physical Systems
• Intelligent measurement systems
• Augmented and virtual reality
• Human-computer interaction
• Accuracy and precision of virtual environments
• Accuracy and precision of neural and fuzzy components
• Multimodal sensing
• Perception, neurodynamics, neurophysiology, psychophysics
• Sensors and displays
• Multimodal (visual, haptic, audio, etc) virtual environments
• Multi-sensor data fusion and intelligent sensor fusion
• Calibration
• Neural and fuzzy technologies for identification, prediction, and control of complex dynamic systems
• Intelligent monitoring and control systems
• Evolutionary techniques for optimization and logistics
• Evolutionary monitoring and control
• Neural and fuzzy signal/image processing for entertainment and educational applications
• Neural and fuzzy signal/image processing for industrial, environmental and domotic applications
• Object modeling
• Image understanding and recognition
• Virtual reality languages
• Object and system model validation
• Computational intelligence technologies for medical and bioengineering applications
• Computational intelligence technologies for robotics and vision
• Machine learning for sensing systems and virtual reality
• Computational intelligence for entertainment and educational applications
• Model-based telecommunications and telecontrol
• Collaborative distributed virtual environments
• Fuzzy and neural components for embedded systems
• Hybrid systems
• Neural, fuzzy and genetic/evolutionary algorithms for system optimization and calibration
• Hardware implementation of neural and fuzzy systems for measurements
• Reliability of fuzzy and neural components
• Neural and fuzzy techniques for system diagnosis
• Neural and fuzzy techniques for quality measurement
• Fault tolerance and testing in fuzzy and neural components
• Standards