<p>This book provides a timely and insightful exploration of how emerging digital technologies can be leveraged to achieve sustainability and build environmental resilience in the face of escalating global challenges. It offers readers a practical and theoretical foundation for understanding&#xa0;<span class="markoue8zm9xz" data-markjs="true" data-ogac="" data-ogab="" data-ogsc="" data-ogsb="">data</span>-driven sustainability, a concept that refers to the integration of advanced&#xa0;<span class="markoue8zm9xz" data-markjs="true" data-ogac="" data-ogab="" data-ogsc="" data-ogsb="">data</span>&#xa0;tools—such as artificial intelligence, big&#xa0;<span class="markoue8zm9xz" data-markjs="true" data-ogac="" data-ogab="" data-ogsc="" data-ogsb="">data</span>&#xa0;analytics, Internet of Things (IoT), and blockchain—into environmental planning, policy, and operations. With climate change, biodiversity loss, pollution, and resource scarcity accelerating at an alarming pace, traditional approaches to sustainability are proving inadequate. The need for real-time&#xa0;<span class="markoue8zm9xz" data-markjs="true" data-ogac="" data-ogab="" data-ogsc="" data-ogsb="">data</span>, predictive analytics, intelligent automation, and transparent monitoring has never been more urgent. This book addresses that critical need by illustrating how&#xa0;<span class="markoue8zm9xz" data-markjs="true" data-ogac="" data-ogab="" data-ogsc="" data-ogsb="">data</span>-centric technologies can help bridge the gap between sustainability ambitions and tangible action. It explores how big&#xa0;<span class="markoue8zm9xz" data-markjs="true" data-ogac="" data-ogab="" data-ogsc="" data-ogsb="">data</span> can transform environmental intelligence, enabling governments, businesses, and communities to track environmental performance in real time, anticipate risks, and intervene proactively. Artificial intelligence is examined as a powerful tool for optimizing resource use, modeling climate scenarios, enabling smart agriculture, and enhancing energy efficiency through learning algorithms and pattern recognition.</p>

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Data-Driven Sustainability: Harnessing Technology for A Greener Future and Environmental Resilience

摘要

This book provides a timely and insightful exploration of how emerging digital technologies can be leveraged to achieve sustainability and build environmental resilience in the face of escalating global challenges. It offers readers a practical and theoretical foundation for understanding data-driven sustainability, a concept that refers to the integration of advanced data tools—such as artificial intelligence, big data analytics, Internet of Things (IoT), and blockchain—into environmental planning, policy, and operations. With climate change, biodiversity loss, pollution, and resource scarcity accelerating at an alarming pace, traditional approaches to sustainability are proving inadequate. The need for real-time data, predictive analytics, intelligent automation, and transparent monitoring has never been more urgent. This book addresses that critical need by illustrating how data-centric technologies can help bridge the gap between sustainability ambitions and tangible action. It explores how big data can transform environmental intelligence, enabling governments, businesses, and communities to track environmental performance in real time, anticipate risks, and intervene proactively. Artificial intelligence is examined as a powerful tool for optimizing resource use, modeling climate scenarios, enabling smart agriculture, and enhancing energy efficiency through learning algorithms and pattern recognition.