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International Conference on AI-driven Data Science for Autonomous Systems - (ICIADAS-27)

21st - 22nd May 2027 , Fukuoka - Japan

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Call For Papers

The (ICIADAS-27) emphasizes interdisciplinary collaboration by bringing together experts from diverse fields. It encourages research that integrates multiple perspectives to address complex global challenges.

Key areas such as Artificial Intelligence, Data Science, Machine Learning are explored to promote cross-domain knowledge exchange and collaborative innovation.

Authors are invited to submit papers addressing, but not limited to, the following areas:

  • AI applications in autonomous vehicle navigation
  • Data science for traffic prediction models
  • Machine learning for sensor fusion in robotics
  • AI-driven decision making in autonomous systems
  • Data privacy challenges in autonomous technologies
  • AI for enhancing human-robot interaction
  • Predictive maintenance for autonomous vehicles
  • Machine learning for path planning algorithms
  • AI in drone technology and applications
  • Data-driven safety assessments for autonomous systems
  • AI for optimizing fleet management solutions
  • Machine learning in robotics process automation
  • AI applications in smart manufacturing
  • Data visualization for autonomous system performance
  • AI for environmental monitoring in autonomous systems
  • Challenges in deploying autonomous technologies
  • AI in logistics and supply chain automation
  • Data ethics in autonomous system development
  • AI for enhancing mobility solutions
  • Future trends in autonomous systems research

Assessment

All submissions will undergo peer review to ensure quality and interdisciplinary relevance. Accepted papers will be presented and considered for publication in journals and conference proceedings.

Registration

Registering for the conference provides access to keynote sessions, technical presentations, and networking opportunities with global experts.

Publication

Publishing through the conference enhances the visibility of your research and connects your work with a broader academic audience.