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{ "item_title" : "Multimodal Intelligent Technologies for a Sustainable Future in Water, Health, and Climate", "item_author" : [" Chetna Sharma", "Monit Kapoor", "Amandeep Kaur "], "item_description" : "This book explores the transformative potential of artificial intelligence (AI), machine learning (ML), deep learning, Internet of Things (IoT), and multimodal intelligent technologies in addressing critical challenges related to water security, public health, climate resilience, and sustainable development. It presents cutting-edge research, real-world applications, and emerging technological innovations that support the achievement of global sustainability goals. This book: - Explores AI-driven solutions for water resource management, water quality monitoring, sanitation systems, and smart environmental infrastructure.- Provides insights into intelligent healthcare technologies, including disease prediction, health analytics, medical decision support systems, and digital health innovations.- Examines advanced climate intelligence techniques for climate risk assessment, disaster prediction, environmental monitoring, and resilience planning.- Discusses the integration of multimodal data analytics, IoT-enabled sensing, and ML frameworks for sustainable decision-making across interconnected domains.- Covers ethical, governance, policy, and societal considerations associated with the deployment of intelligent technologies for sustainable development. The text is primarily written for senior undergraduate and graduate students, academic researchers, policymakers, environmental scientists, healthcare professionals, computer scientists, data scientists, AI practitioners, and engineers working in the fields of sustainability, water resources, public health, climate science, and intelligent systems.", "item_img_path" : "https://covers3.booksamillion.com/covers/bam/1/04/135/059/1041350597_b.jpg", "price_data" : { "retail_price" : "280.00", "online_price" : "280.00", "our_price" : "280.00", "club_price" : "280.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Multimodal Intelligent Technologies for a Sustainable Future in Water, Health, and Climate|Chetna Sharma

Multimodal Intelligent Technologies for a Sustainable Future in Water, Health, and Climate

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Overview

This book explores the transformative potential of artificial intelligence (AI), machine learning (ML), deep learning, Internet of Things (IoT), and multimodal intelligent technologies in addressing critical challenges related to water security, public health, climate resilience, and sustainable development. It presents cutting-edge research, real-world applications, and emerging technological innovations that support the achievement of global sustainability goals.

This book:

- Explores AI-driven solutions for water resource management, water quality monitoring, sanitation systems, and smart environmental infrastructure.
- Provides insights into intelligent healthcare technologies, including disease prediction, health analytics, medical decision support systems, and digital health innovations.
- Examines advanced climate intelligence techniques for climate risk assessment, disaster prediction, environmental monitoring, and resilience planning.
- Discusses the integration of multimodal data analytics, IoT-enabled sensing, and ML frameworks for sustainable decision-making across interconnected domains.
- Covers ethical, governance, policy, and societal considerations associated with the deployment of intelligent technologies for sustainable development.

The text is primarily written for senior undergraduate and graduate students, academic researchers, policymakers, environmental scientists, healthcare professionals, computer scientists, data scientists, AI practitioners, and engineers working in the fields of sustainability, water resources, public health, climate science, and intelligent systems.

This item is Non-Returnable

Details

  • ISBN-13: 9781041350590
  • ISBN-10: 1041350597
  • Publisher: CRC Press
  • Publish Date: December 2026
  • Page Count: 356

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