Artificial Intelligence and Machine Learning for Smart and Sustainable Waste Treatment
Emerging Applications and Best Practices
- 1st Edition - February 1, 2027
- Latest edition
- Editors: Izharul Haq, Krishna Chaitanya Maturi
- Language: English
Artificial Intelligence and Machine Learning for Smart and Sustainable Waste Treatment provides a much-needed, specialized resource on the application of Artificial intell… Read more
Description
Description
Artificial Intelligence and Machine Learning for Smart and Sustainable Waste Treatment provides a much-needed, specialized resource on the application of Artificial intelligence (AI) and machine learning in sustainable waste management. The book provides methods to help streamline processes, improve recycling rates, reduce contamination, and lower operational costs along with Machine learning models that can enhance forecasting and planning, allowing municipalities to optimize collection schedules and waste processing strategies. By combining theoretical insights with practical solutions, this book closes the gap between advanced technology and real-world applications, providing a roadmap for transforming solid waste management through data-driven, AI-powered approaches and seeks to drive forward the integration of intelligent, sustainable solutions into waste management practices across the globe.
Key features
Key features
- Clear Methodologies and Frameworks: The book provides structured methodologies for integrating AI and machine learning techniques into various facets of solid waste management
- Actionable Case Studies and Real-World Examples: To help readers understand the practical applications of AI in waste management, the book presents detailed case studies from cities, companies, and research projects that have successfully implemented AI and machine learning
- Tools for Optimization and Sustainability: The book equips readers with the tools they need to optimize waste management processes. This includes AI models that predict waste patterns, recommend sorting improvements, and streamline recycling operations
Readership
Readership
Students of Environmental and Chemical Engineering, as well as Waste management researchers and research institutes
Table of contents
Table of contents
1. Introduction and Historical perspective to AI and ML in solid waste management industry and their practices
2. Segregation, and implementation of zero bin cities using AI approaches
3. AI driven strategy for implementing transfer stations and treatment technologies for SWM
4. AI applications in implementing decision supporting system for high success rate of SWM projects
5. Applications of deep learning in thermal and biological processes
6. AI and ML applications in thermal conversion of organic waste
7. Biological treatment optimizations using AI techniques
8. Fusing AI and Mechanistic simulations for efficient bioenergy generation
9. Forecasting Biochemical Processes for Advancing Biofuel, Bioproduct, and Biomaterial Innovation using AI techniques.
10. Assessment of case studies on AI based solid waste management projects
11. Incorporation of AI tools in Solid Waste Management: Case studies from a Waste Management perspective
12. Cost-Benefit Analysis of Artificial Intelligence Applications in Solid Waste Management
13. AI-Driven Innovations in Recycling, Regulatory Monitoring, and Smart Waste Technologies: Market Landscape and Application Insights
14. Ethical, Governance, and Circular Economy Considerations in AI-Driven Solid Waste Management Systems
15. Future perspective, Challenges, and Limitations of AI and ML applications in providing best practices for SWM.
2. Segregation, and implementation of zero bin cities using AI approaches
3. AI driven strategy for implementing transfer stations and treatment technologies for SWM
4. AI applications in implementing decision supporting system for high success rate of SWM projects
5. Applications of deep learning in thermal and biological processes
6. AI and ML applications in thermal conversion of organic waste
7. Biological treatment optimizations using AI techniques
8. Fusing AI and Mechanistic simulations for efficient bioenergy generation
9. Forecasting Biochemical Processes for Advancing Biofuel, Bioproduct, and Biomaterial Innovation using AI techniques.
10. Assessment of case studies on AI based solid waste management projects
11. Incorporation of AI tools in Solid Waste Management: Case studies from a Waste Management perspective
12. Cost-Benefit Analysis of Artificial Intelligence Applications in Solid Waste Management
13. AI-Driven Innovations in Recycling, Regulatory Monitoring, and Smart Waste Technologies: Market Landscape and Application Insights
14. Ethical, Governance, and Circular Economy Considerations in AI-Driven Solid Waste Management Systems
15. Future perspective, Challenges, and Limitations of AI and ML applications in providing best practices for SWM.
Product details
Product details
- Edition: 1
- Latest edition
- Published: February 1, 2027
- Language: English
About the editors
About the editors
IH
Izharul Haq
Izharul Haq is working as an Assistant Professor at the Manipal University Jaipur, India, where he specializes in environmental biotechnology, with a focus on waste management using microbial processes and evaluating the toxicity of pollutants. He completed his PhD in Microbiology at the CSIR-Indian Institute of Toxicology Research, Lucknow, India, and later conducted postdoctoral research at the Indian Institute of Technology, Guwahati. His current research work is in the field of environmental microbiology and pollutant remediation.
Affiliations and expertise
Assistant Professor, Manipal University Jaipur, IndiaKM
Krishna Chaitanya Maturi
Krishna Chaitanya Maturi is an Assistant Professor in Department of civil engineering at Gati Shakti Vishwavidyalaya. He holds a B. Tech in Civil Engineering from JNTU Kakinada and an M. Tech in Civil/Environmental Engineering from IIT Guwahati. He completed his Ph.D. in Civil/Environmental Engineering, specializing in Solid Waste Management from IIT Guwahati. He has also served as a Research Associate at Hong Kong Baptist University and worked as a Project Scientist II in the Department of Civil Engineering at IIT Roorkee. His expertise spans environmental engineering, focusing on sustainable waste management practices, waste to energy, and Plastics and bioplastics in waste streams.
Affiliations and expertise
Assistant Professor, Department of civil engineering at Gati Shakti Vishwavidyalaya, India