This compilation of papers captures the essence of the International Conference on Smart Systems for Sustainable Development using Advanced Computational Techniques (ICSSA 2025). It provides a comprehensive exploration of how next-generation computing drives ecological and social resilience and highlights the pivotal role of intelligent automation and data-driven strategies in solving complex global challenges.It delves into the integration of Artificial Intelligence (AI), Internet of Things (IoT), and high-performance computing to create "e;green"e; technological ecosystems. This book covers a broad spectrum of research, including smart grid management, precision agriculture, carbon footprint optimization through machine learning, and the development of circular economy models via blockchain. By synthesizing theoretical frameworks with real-world case studies, the contributions illustrate how advanced algorithms can minimize resource waste while maximizing industrial efficiency. Together, these papers offer a roadmap for sustainable digital transformation across energy, healthcare, and urban planning sectors by emphasizing the shift toward "e;Cognitive Sustainability"e;, where systems do not just automate tasks but actively learn to balance human needs with environmental constraints.This book is an essential resource for academic researchers, post-graduate students, and industry practitioners specializing in computer science and environmental engineering. It also serves policymakers and urban planners seeking data-backed strategies to implement sustainable technologies within smart city infrastructures and corporate ESG frameworks.

This compilation of papers captures the essence of the International Conference on Smart Systems for Sustainable Development using Advanced Computational Techniques (ICSSA 2025). It provides a comprehensive exploration of how next-generation computing drives ecological and social resilience and highlights the pivotal role of intelligent automation and data-driven strategies in solving complex global challenges.It delves into the integration of Artificial Intelligence (AI), Internet of Things (IoT), and high-performance computing to create "e;green"e; technological ecosystems. This book covers a broad spectrum of research, including smart grid management, precision agriculture, carbon footprint optimization through machine learning, and the development of circular economy models via blockchain. By synthesizing theoretical frameworks with real-world case studies, the contributions illustrate how advanced algorithms can minimize resource waste while maximizing industrial efficiency. Together, these papers offer a roadmap for sustainable digital transformation across energy, healthcare, and urban planning sectors by emphasizing the shift toward "e;Cognitive Sustainability"e;, where systems do not just automate tasks but actively learn to balance human needs with environmental constraints.This book is an essential resource for academic researchers, post-graduate students, and industry practitioners specializing in computer science and environmental engineering. It also serves policymakers and urban planners seeking data-backed strategies to implement sustainable technologies within smart city infrastructures and corporate ESG frameworks.

This compilation of papers captures the essence of the International Conference on Smart Systems for Sustainable Development using Advanced Computational Techniques (ICSSA 2025). It provides a comprehensive exploration of how next-generation computing drives ecological and social resilience and highlights the pivotal role of intelligent automation and data-driven strategies in solving complex global challenges.It delves into the integration of Artificial Intelligence (AI), Internet of Things (IoT), and high-performance computing to create "e;green"e; technological ecosystems. This book covers a broad spectrum of research, including smart grid management, precision agriculture, carbon footprint optimization through machine learning, and the development of circular economy models via blockchain. By synthesizing theoretical frameworks with real-world case studies, the contributions illustrate how advanced algorithms can minimize resource waste while maximizing industrial efficiency. Together, these papers offer a roadmap for sustainable digital transformation across energy, healthcare, and urban planning sectors by emphasizing the shift toward "e;Cognitive Sustainability"e;, where systems do not just automate tasks but actively learn to balance human needs with environmental constraints.This book is an essential resource for academic researchers, post-graduate students, and industry practitioners specializing in computer science and environmental engineering. It also serves policymakers and urban planners seeking data-backed strategies to implement sustainable technologies within smart city infrastructures and corporate ESG frameworks.