Applied Artificial Intelligence for Industrial Innovation: Current State of the art and New Directions
This special session is organised and supported by the following educational partner
California State University San Bernardino,
United States
Session Chair:
- Dr. Bilal Muhammad Khan
Session Co-Chairs:
- Dr. Khalil Dajani,
- Dr. Wasiq Khan,
- Dr. Jennifer Jin,
- Dr. Yang Zhou
Synopsis:
The use of Artificial intelligence (AI) is becoming prevalent in many industrial processes focusing on the development of intelligent industrial systems and tools that can automate and optimize production processes, improve production quality, and enhance overall efficiency from multiple perspectives. This special session will focus on the practical applications of AI in industrial settings that will include (but not limited to) processes involved in chemical production, nanotechnology, water treatment, logistics, manufacturing, supply chain optimization, automation via decision support. With the increasing momentum in the use of AI in the above settings, the emphasis in this issue will be on the challenges and opportunities associated with implementing these technologies.
Topics:
Contributions to this special session will cover a range of topics related to applied AI in industrial applications, including but not limited to:
- Machine learning algorithms for predictive maintenance
- Reinforcement learning algorithms for production and improvement in maintenance processes
- Data analytics and generation tools for developing new AI based systems for industrial process improvement
- Generative natural language processing technologies for improved productivity and decision support
- Robotics and automation in manufacturing and logistics
- Computer vision and image processing for quality control
- Natural language processing for intelligent customer service
- Decision support systems for supply chain optimization
Original research articles, review articles, and case studies are welcomed that address the practical challenges of implementing AI in industrial processes, as well as the benefits and outcomes of the current directions. Submissions should present novel contributions that demonstrate the potential of AI to transform industrial processes and systems and should provide insights and recommendations for future research and development.
Paper Submission:
Prospective authors are invited to submit full-length papers (not exceeding 6 pages) conform to the IEEE format . All papers will be handled and processed electronically via the EDAS online submission system.