Topic: Data-Driven Intelligent Systems: Challenges and Innovations

As the volume of data generated continues to surge, data-driven intelligent systems have become essential for leveraging this information to drive innovation and enhance decision-making across various sectors. These systems utilize advanced algorithms and machine learning techniques to extract meaningful insights from vast datasets, facilitating smarter applications in fields such as intelligent vehicles, smart recommender systems, smart cities, intelligent healthcare systems, and intelligent agricultural systems. However, the rapid evolution of data-driven technologies also presents significant challenges, including issues related to data quality, privacy, security, and algorithmic bias. The increasing complexity of data sources and the demand for real-time processing further complicate the development and deployment of these intelligent systems.

This Special Issue aims to explore the latest advancements, challenges, and innovative solutions in the realm of data-driven intelligent systems. We seek to provide a comprehensive understanding of current trends and future directions in this dynamic field. Topics of interest include, but are not limited to:
● Machine Learning and Deep Learning Techniques;
● Data Quality Assessment and Improvement;
● Privacy-Preserving Data Mining;
● Algorithmic Fairness and Bias Mitigation;
● Real-Time Data Processing and Analytics;
● Data Integration and Fusion Techniques;
● Edge Computing for Data-Driven Applications;
● Explainable Artificial Intelligence (XAI);
● Cooperation and control of intelligent multi-robotic systems;
● Network and communication security of intelligent vehicles;
● Applications of Intelligent Systems in Various Domains.

Academics, research students, and professionals are invited to submit their original work. Extended conference papers with at least 50% new content are also welcome.

Data-driven systems, machine learning,explainable artificial intelligence (XAI)

31 May 2025