Sang-Bing Tsai - Böcker

A central concern that has remained relevant in recent years has been the management of waste and pollution. Improper disposal methods such as open-air burning and unsafe recycling have led to significant public and environmental health issues including respiratory disorders, resource depletion, and infant mortality. Adopting new waste management techniques is a necessity in order to preserve the health of the global community and ecosystem.Waste Management Techniques for Improved Environmental and Public Health provides innovative insights into the advancing methods and technologies of reducing pollution and promoting sustainable development. The content within this publication examines ecological technologies, risk assessment, and green operation. It is designed for ecologists, biologists, researchers, enterprises, academicians, policymakers, scientists, environmental engineers, and students seeking current research on developing theories and techniques within waste moderation and environmental protection.

As data volumes grow exponentially, the challenge is no longer limited to speed and scalability—but to sustainability and responsibility. Sustainable Big Data Pipelines: Architectures, Energy Optimization, and Ethical Governance presents a forward-looking exploration of how modern big data systems can be designed and operated with environmental efficiency, ethical integrity, and regulatory awareness at their core.Edited by leading scholars Jaheer Mukthar K.P and Sang-Bing Tsai, this volume brings together interdisciplinary research and practical insights on energy-efficient data architectures, green computing strategies, privacy-preserving analytics, ethical data governance, and compliance with global regulations. The book bridges theory and practice by offering actionable frameworks, monitoring approaches, and real-world use cases that guide organizations toward responsible data-driven innovation.Designed for researchers, practitioners, policymakers, and graduate students, this book serves as a critical resource for building big data pipelines that not only perform at scale but also align with sustainability goals and societal values.