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    4. Referensverk och tvärvetenskap

    Artificial Intelligence for Sustainable Infrastructure and Environmental Systems

    Towards 2030

    AvAkashbhai Ashokbhai Dave,Mariya Ouaissa

    Inbunden, Engelska, 2027

    1 468 kr

    Slutsåld

    Beskrivning

    This book explores how artificial intelligence is reshaping the design, management, and resilience of critical infrastructure while accelerating progress toward the United Nations Sustainable Development Goals (SDGs) 2030 Agenda. As the world faces pressing challenges related to climate change, rapid urbanization, resource scarcity, and environmental degradation, AI has emerged as a transformative technology capable of enabling smarter, more efficient, and more sustainable engineering solutions.Bringing together contributions from leading researchers and practitioners, this volume presents cutting-edge advances in AI-driven sustainable infrastructure, environmental systems, digital twins, predictive maintenance, federated learning, cyber-physical systems, intelligent transportation, smart water and energy networks, healthcare infrastructure, and engineering decision support. The book further examines the ethical, social, policy, and human dimensions of AI, emphasizing responsible innovation and inclusive technological development.The chapters demonstrate how AI can contribute directly to the achievement of several UN Sustainable Development Goals, including SDG 3 (Good Health and Well-being) through intelligent healthcare systems; SDG 6 (Clean Water and Sanitation) through smart water resource management; SDG 7 (Affordable and Clean Energy) through AI-enabled energy optimization; SDG 9 (Industry, Innovation and Infrastructure) by advancing resilient and intelligent infrastructure; SDG 11 (Sustainable Cities and Communities) through smart urban development and mobility; SDG 12 (Responsible Consumption and Production) via resource optimization; SDG 13 (Climate Action) by supporting low-carbon and climate-resilient infrastructure; SDG 16 (Peace, Justice and Strong Institutions) through secure and trustworthy AI-enabled cyber-physical systems; and SDG 17 (Partnerships for the Goals) by promoting interdisciplinary collaboration across engineering, computer science, environmental sciences, and public policy.Rather than viewing artificial intelligence solely as a technological innovation, this book positions AI as a strategic enabler of sustainable development—supporting data-driven decision-making, improving resource efficiency, strengthening infrastructure resilience, and fostering environmentally responsible engineering practices. By integrating technological innovation with sustainability principles and the global ambitions of the 2030 Agenda for Sustainable Development, the volume provides a timely and comprehensive reference for researchers, academics, engineers, policymakers, industry professionals, and graduate students working at the intersection of artificial intelligence, sustainable infrastructure, and environmental systems.The book serves as both a scientific reference and a practical roadmap, demonstrating how responsible AI can help build resilient infrastructure, sustainable communities, and a more inclusive, secure, and environmentally sustainable future in alignment with the vision of the United Nations Sustainable Development Goals.

    Produktinformation

    • Utgivningsdatum:2027-01-18
    • Mått:178 x 254 x undefined mm
    • Format:Inbunden
    • Språk:Engelska
    • Antal sidor:352
    • Förlag:Taylor & Francis Ltd
    • ISBN:9781041386551

    Utforska kategorier

    • Referensverk och tvärvetenskap inom Samhälle och politik
    • Tillverkningsteknik inom Naturvetenskap och teknik
    • Byggnadsteknik inom Naturvetenskap och teknik

    Mer om författaren

    Akashbhai Ashokbhai Dave is currently working as associate professor in information technology department at research professional specializing in cloud computing and artificial intelligence, with a focus on AI-driven performance optimization and intelligent cloud infrastructure. He holds advanced academic qualifications in Computer Science / Engineering and is currently engaged in teaching, research, and scholarly publishing. His research centers on live virtual machine migration, workload prediction, and resource management, leveraging machine learning and deep learning techniques such as LSTM-based models and hybrid optimization frameworks. He emphasizes integrated, performance-oriented solutions that reduce migration time, downtime, and SLA violations, rather than isolated algorithmic improvements. His work involves both simulation-based and experimental evaluation of intelligent systems. Mariya Ouaissa is an Assistant Professor in Cybersecurity and Networks at FSSM, Cadi Ayyad University, Marrakech, Morocco. She is a Ph.D. graduated in 2019 in Computer Science and Networks from ENSAM-Moulay Ismail University, Meknes, Morocco. She is a Networks and Telecoms Engineer, graduated in 2013 from National School of Applied Sciences Khouribga, Morocco. She is a Co-Founder and IT Consultant at IT Support and Consulting Center. She was a trainer/Professor in Networks and Systems from 2021 to 2023. She was working for Moulay Ismail University as a Visiting Professor from 2013 to 2021. She is an IEEE Senior Member of Institute of Electrical and Electronics Engineers (IEEE), as well as a member of the International Association of Engineers and International Association of Online Engineering, and since 2021, she is an "ACM Professional Member". Her main research topics are Cybersecurity, IoT, M2M, D2D, WSN, Cellular Networks, and Vehicular Networks.Mariyam Ouaissa is currently an Assistant Professor in Networks and Systems at ENSA, Chouaib Doukkali University, El Jadida, Morocco. She received her Ph.D. degree in 2019 from National Graduate School of Arts and Crafts, Meknes, Morocco and her Engineering Degree in 2013 from the National School of Applied Sciences, Khouribga, Morocco. She is a communication and networking researcher and practitioner with industry and academic experience. Dr Ouaissa's research is multidisciplinary that focuses on Internet of Things, M2M, WSN, vehicular communications and cellular networks, security networks, congestion overload problem and the resource allocation management and access control. She is serving as a reviewer for international journals and conferences including as IEEE Access, Wireless Communications and Mobile Computing. Ahmed A. Elngar is an Associate Professor and Head of the Computer Science Department at the Faculty of Computers and Artificial Intelligence, Beni-Suef University, Egypt. He is also an Associate Professor of Computer Science at the College of Computer Information Technology, American University in the Emirates, United Arab Emirates, and an Adjunct Professor at the School of Technology, Woxsen University, India. Dr. Elngar is the Founder and Head of the Scientific Innovation Research Group (SIRG) and serves as the Director of the Technological and Informatics Studies Center (TISC) at the Faculty of Computers and Artificial Intelligence, Beni-Suef University. His interdisciplinary research extends to the application of Artificial Intelligence and Machine Learning techniques in Civil Engineering, where he actively supervises and collaborates on numerous master’s and Ph.D. theses. His work in this area focuses on AI-driven modeling, prediction, optimization, and intelligent decision-support systems for civil engineering applications, such as material performance analysis, structural behavior prediction, durability assessment, and smart infrastructure systems. C. Kishor Kumar Reddy is a seasoned academician and researcher with over 12 years of experience in computer science and engineering. Currently serving at Stanley College of Engineering and Technology for Women, Hyderabad, he holds a Ph.D. in Computer Science and Engineering and a Postdoctoral Fellowship from Universiti Kebangsaan Malaysia, Malaysia. Dr. Reddy has made significant contributions in areas such as Artificial Intelligence, Machine Learning, Deep Learning, Federated Learning, Cybersecurity, Healthcare 6.0, and Disaster Management.

    Innehållsförteckning

    • Section I: Foundations of Artificial Intelligence for Sustainable Infrastructure and Environmental Systems. Chapter 1: Introduction to Artificial Intelligence for Sustainable Infrastructure. Chapter 2: Artificial Intelligence in Water Resources and Environmental Systems: Concepts, Challenges, and Future Directions. Chapter 3: AI Applications in Sustainable Urban Infrastructure: Challenges and Opportunities. Chapter 4: AI-Enabled Smart Cities: Advancing the 2030 Sustainable Development Goals. Chapter 5: Decision Support and Optimization in Sustainable Engineering. Section II: AI Technologies for Intelligent and Sustainable Infrastructure. Chapter 6: AI-Driven Digital Twins for Sustainable Infrastructure Monitoring and Optimization. Chapter 7: Artificial Intelligence-Driven Digital Twins for Cyber-Physical Smart Infrastructure: Architecture, Communication, and Intelligent Security. Chapter 8: Federated Learning and Privacy-Preserving AI for Smart Infrastructure and Environmental Systems. Chapter 9: Artificial Intelligence for Predictive Maintenance and Smart Infrastructure Asset Management. Section III: AI Applications in Sustainable Infrastructure Systems. Water and Energy Infrastructure. Chapter 10: Digital Twin Frameworks for Real-Time Monitoring and Anomaly Detection in Urban Water Distribution Networks. Chapter 11: Energy-Efficient and Low-Carbon Infrastructure Systems Using AI. Intelligent Transportation Systems. Chapter 12: Artificial Intelligence Driven Intelligent Transportation Systems for Smart Mobility. Chapter 13: Advances in Performance and Security of V2X Communications for Intelligent Transportation Systems in 5G and 6G Networks. Sustainable Healthcare Infrastructure. Chapter 14: AI-Driven Cybersecurity for Sustainable and Resilient Healthcare Infrastructure. Chapter 15: Security Challenges and Protection Strategies for Sustainable Medical Cyber-Physical Systems in Connected Healthcare. Chapter 16: Empowering Precision Medicine: ML, Big Data, and Intelligent Robots in IoT-Enabled AGI Smart Hospitals. Section IV: Human, Ethical, and Future Perspectives. Chapter 17: The Vast Advantages of Human Sustainability Advanced through AI in Reinforcing Human Capital in Global Business: An Affective Perspective. Chapter 18: Ethical, Social, and Policy Dimensions of Artificial Intelligence in Engineering. Chapter 19: Engineering Service-Learning for Sustainable Development.