Artificial Intelligence in Future Mining
Cognitive Data Science in Sustainable Computing Series

Artificial Intelligence in Future Mining explores the latest developments in the use of artificial intelligence (AI) in mining and how it will impact the industry’s future. The application of data science and artificial intelligence in future mining involves using advanced technologies to optimize operations, improve decision-making, and enhance safety and sustainability in the industry. After a brief history of AI in mining, the book's editors look closely at different AI techniques used. Chapters explore ocean mining, brine mining, and urban mining. With an eye towards sustainability, the editors then review the future of wastewater mining and green mining.

The book wraps up with chapters on safety and risk, resource planning, and a larger discussion of the opportunities and challenges of mining with AI in the future. This book is a must-have for researchers and professionals who find themselves at the intersection of mining, engineering, and data science.

1. The Evolution of AI in Mining: A Historical Overview
2. AI-Powered Techniques for Improved Continental Mining
3. The Future of Ocean Mining with Artificial Intelligence
4. Revolutionizing Brine Mining through AI-Assisted Techniques
5. Urban Mining and AI: Challenges and Opportunities
6. Wastewater Mining: A New Frontier for AI in Mining
7. Green Mining with AI: A Path to Sustainability
8. Enhancing Safety and Minimizing Risk in Mining Processes with AI
9. AI-Assisted Resource Planning and Management in Mining
10. The Future of the Mining Industry with Artificial Intelligence: Opportunities and Challenge

Amin Beheshti is a Full Professor of Data Science and the Director of AI-enabled Processes
(AIP) Research Centre, School of Computing, Macquarie University. Amin is also the head of
the Data Analytics Research Lab and Adjunct Academic in Computer Science at UNSW Sydney.
Amin completed his Ph.D. and Postdoc in Computer Science and Engineering at UNSW
Sydney and holds a Master and Bachelor in Computer Science both with First Class Honours.
He is the leading author of several authored books in data, social, and process analytics, co?authored with other high-profile researchers.
Mohsen Asadnia is an Associate Professor and group lader in Mechatronics-biomechanics and
at Macquarie University, Australia. He received his PhD degree in Mechanical Engineering
from Nanyang Technological University, Singapore. Prior to joining Macquarie University,
Mohsen had several teaching and research roles with the University of Western Australia,
Massachusetts Institute of Technology and Nanyang Technological University. His research
interest lies in environmental/ biomedical sensors, Artificial Intelligence, and bio-inspired
sensing.