The book involves the original research and practical implementations presented at the International Conference on Smart Systems for Sustainable Development (S4SD 2025). This volume provides smart systems and data-driven inventions contributing to sustainable development across various disciplines. It offers a multidisciplinary perspective of how artificial intelligence (AI), machine learning, internet of things, and optimization techniques are being integrated to address challenging real-world problems in the areas of climate, energy, healthcare, agriculture, infrastructure, etc. The volume is interdisciplinary, illustrating knowledge from fields such as engineering, computer science, environmental science, and industrial technology, presenting researchers with the information desired to solve demanding societal issues. Contributions cover theoretical developments in deep learning, swarm intelligence, and cyber-physical systems, applied research for sensor networks, blockchain, forecasting models, etc. Integrating intelligent decision-making with issues of global accessibility and international sustainability, the book aims to contribute to the main global challenges set out in the United Nations Sustainable Development Goals (SDGs).
The introduction of coverage of optimization frameworks, intelligent automation, predictive analytics, and interdisciplinary system design makes the book a value addition for the readers with everything they need to develop resilient and energy-efficient ecosystems in today's digital world. In addition, applied case studies and hybrid methods are presented. This book is an important resource for researchers, academics, graduate students, engineers, data scientists, and industrial professionals interested in using novel methods to advance sustainability, intelligent transportation, environmental science, and artificial intelligence for sustainable development.
The book involves the original research and practical implementations presented at the International Conference on Smart Systems for Sustainable Development (SSSD 2025). This volume provides smart systems and data-driven inventions contributing to sustainable development across various disciplines. It offers a multidisciplinary perspective of how artificial intelligence (AI), machine learning, internet of things, and optimization techniques are being integrated to address challenging real-world problems in the areas of climate, energy, healthcare, agriculture, infrastructure, etc. The volume is interdisciplinary, illustrating knowledge from fields such as engineering, computer science, environmental science, and industrial technology, presenting researchers with the information desired to solve demanding societal issues. Contributions cover theoretical developments in deep learning, swarm intelligence, and cyber-physical systems, applied research for sensor networks, blockchain, forecasting models, etc. Integrating intelligent decision-making with issues of global accessibility and international sustainability, the book aims to contribute to the main global challenges set out in the United Nations Sustainable Development Goals (SDGs).
The introduction of coverage of optimization frameworks, intelligent automation, predictive analytics, and interdisciplinary system design makes the book a value addition for the readers with everything they need to develop resilient and energy-efficient ecosystems in today's digital world. In addition, applied case studies and hybrid methods are presented. This book is an important resource for researchers, academics, graduate students, engineers, data scientists, and industrial professionals interested in using novel methods to advance sustainability, intelligent transportation, environmental science, and artificial intelligence for sustainable development.
Tien Anh Tran
Smart and Sustainable Intelligent Systems sustainable development AI in smart cities Cyber-physical systems for sustainability Smart healthcare systems using AI Energy-efficient smart building technologies Digital transformation Optimization algorithms Forecasting and predictive analytics in sustainability Intelligent technologies for climate resilience