Advances in Machine Learning for Engineering Applications and Sustainable Development

Erscheinungsjahr 2027
ISBN: 978-0-443-43049-7
Verlag: Elsevier Science & Technology

Buch, Englisch, Format (B × H): 152 mm x 229 mm

Advances in Machine Learning for Engineering Applications and Sustainable Development, published as Volume 145 of the serial Advances in Computers, provides a comprehensive and timely exploration of how artificial intelligence (AI) and machine learning (ML) are transforming engineering practice and advancing sustainability goals. The volume brings together contributions from leading researchers to examine the integration of data-driven methods in concrete technology, digital fabrication, structural health monitoring, materials engineering, and industrial process optimisation. It highlights emerging paradigms such as AI-driven 3D printing, predictive analytics for failure detection, lifecycle and environmental impact assessment, and circular economy strategies.
Spanning foundational methods and real-world implementations, the volume emphasises sustainable materials, eco-efficient construction processes, and intelligent system design. It pays particular attention to the use of ML in improving resource efficiency, enabling recycling of industrial by-products, and enhancing the performance of green materials such as biochar-based composites. By combining theoretical insights, mathematical modelling, and application-oriented case studies, this volume serves as a critical reference for advancing resilient, efficient, and environmentally responsible engineering systems.

Autoren/Hrsg.

Weitere Mitwirkende

Shuaib, Mohammad

Tabassum, Sazia

Alam, Shadab

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Software Engineering
• Mathematik | Informatik Mathematik Mathematik Allgemein

Inhaltsverzeichnis

1. Machine learning in concrete construction: Applications, challenges, and future aspects
2. Digital Fabrication for Cementitious Materials: AI-Driven 3D Printing Technologies
3. Internet of Things in Sustainable Concrete Production
4. AI-Driven Quality Control and Crack Detection in Concrete Structures with mathematical modelling
5. Artificial Intelligence for Recycling By-Products and Enhancing Performance
6. Machine Learning for Structural Health Monitoring in Engineering Systems
7. Predictive Analytics for Material Performance and Failure Detection
8. AI in the Design and Optimization of Engineering Systems
9. Eco-Efficient Technologies for Sustainable Concrete Production Using Machine Learning and AI
10. AI-Driven Analysis of Engineering Properties of Green Materials and Their Applications
11. Biochar as a Sustainable Supplement in Cement Mortar and Concrete: Machine Learning applications
12. AI-Based Benefit-Cost Analysis of Sustainable Engineering Solutions
13. Circular Economy in Engineering Applications: AI and Machine Learning for Resource Optimization and Waste Reduction
14. Machine Learning for Sustainable Industrial Process Automation
15. AI-Driven Innovations in Sustainable Engineering Projects
16. Artificial Intelligence for Energy-Efficient Systems Design
17. Artificial Intelligence (AI) Tools for Lifecycle and Environmental Impact Assessment in Construction
18. Future Trends in AI and Machine Learning for Sustainable Development

Über Autor(innen)

Alam, Shadab
Dr. Shadab Alam is an Associate Professor at Jazan University, Kingdom of Saudi Arabia. He received his PhD in Computer Science from Aligarh Muslim University, India, where he also completed his master’s and bachelor’s degrees. His research expertise includes information security, blockchain, Internet of Things (IoT), and smart healthcare systems.
Dr. Alam has published over 80 research articles in high-impact journals and leading international conference proceedings. He holds five international patents, including those granted in the USA and Australia, and three national patents. He is a Senior Member of IEEE and holds memberships in several professional bodies, including ACM, CSI, CRSI, IAENG, CSTA, IACSIT, and ICSE. He also serves as an Academic Editor for several peer-reviewed journals, including PLOS ONE and Computational and Mathematical Methods series journals.

Shuaib, Mohammad
Dr. Mohammed Shuaib works at College of Computer science & Engineering at Jazan University, specializing in blockchain, IoT, cybersecurity, and machine learning applications in engineering. He holds a PhD in Computer Engineering from Universiti Teknologi Malaysia (UTM), Malaysia. With 4 patents, Dr. Shuaib is a prolific researcher with more than 58 publications in ISI-ranked and Scopus-indexed journals, alongside 25 conference papers. His expertise spans machine learning, AI-driven optimizations, and sustainable development, particularly in applying AI techniques such as artificial neural networks (ANN), adaptive neuro-fuzzy inference systems (ANFIS), and reinforcement learning (RL) across engineering disciplines.

Dr. Shuaib's editorial experience currently as Associate Editor for Sustainable Computing: Informatics and Systems, and his roles on editorial boards including, position him as an ideal editor for a book addressing the intersection of machine learning, AI, engineering applications, and sustainable development. He is also a member of professional organizations such as IEEE, ACM, and IAENG, reflecting his commitment to advancing research in his fields of interest.