Environmental Informatics Challenges and Solutions /
Environmental Informatics Challenges and Solutions / [electronic resource] :
edited by P. K. Paul, Amitava Choudhury, Arindam Biswas, Binod Kumar Singh.
- 1st ed. 2022.
- X, 299 p. 91 illus., 81 illus. in color. online resource.
1. Environmental Informatics: Basics, Nature and Applications using Emerging Technologies with reference to Issues & Potentialities -- 2. Exploring the Role of ICCT Underlying Technologies in Environmental and Ecological Management -- 3. The practice of Green Computing for busininess -- 4. Green Information Centres and Allied Foundations: The Concerns of Environmental Information & Documentation Practice -- 5. A study on the social and economic impact of artificial intelligence-based environmental forecasts.
This interdisciplinary book incorporates various aspects of environment, ecology, and natural disaster management including cognitive informatics and computing. It fosters research innovation and discovery on basic science and information technology for addressing various environmental problems, while providing the right solutions in environment, ecology, and disaster management. This book is a unique resource for researchers and practitioners of energy informatics in various scientific, technological, engineering, and social fields to disseminate original research on the application of digital technology and information management theory and practice to facilitate the global transition toward sustainable and resilient energy systems. Cognitive informatics is also the need of the hour and deals with cutting-edge and multidisciplinary research area that tackles the fundamental problems shared by modern informatics, computation, software engineering, AI, cybernetics, cognitive science, neuropsychology, medical science, systems science, philosophy, linguistics, economics, management science, and life sciences, which this book also presents.
9789811920837
10.1007/978-981-19-2083-7 doi
Artificial intelligence.
Energy policy.
Energy and state.
Machine learning.
Sustainability.
Quantitative research.
Refuse and refuse disposal.
Artificial Intelligence.
Energy Policy, Economics and Management.
Machine Learning.
Sustainability.
Data Analysis and Big Data.
Waste Management/Waste Technology.
Q334-342 TA347.A78
006.3
1. Environmental Informatics: Basics, Nature and Applications using Emerging Technologies with reference to Issues & Potentialities -- 2. Exploring the Role of ICCT Underlying Technologies in Environmental and Ecological Management -- 3. The practice of Green Computing for busininess -- 4. Green Information Centres and Allied Foundations: The Concerns of Environmental Information & Documentation Practice -- 5. A study on the social and economic impact of artificial intelligence-based environmental forecasts.
This interdisciplinary book incorporates various aspects of environment, ecology, and natural disaster management including cognitive informatics and computing. It fosters research innovation and discovery on basic science and information technology for addressing various environmental problems, while providing the right solutions in environment, ecology, and disaster management. This book is a unique resource for researchers and practitioners of energy informatics in various scientific, technological, engineering, and social fields to disseminate original research on the application of digital technology and information management theory and practice to facilitate the global transition toward sustainable and resilient energy systems. Cognitive informatics is also the need of the hour and deals with cutting-edge and multidisciplinary research area that tackles the fundamental problems shared by modern informatics, computation, software engineering, AI, cybernetics, cognitive science, neuropsychology, medical science, systems science, philosophy, linguistics, economics, management science, and life sciences, which this book also presents.
9789811920837
10.1007/978-981-19-2083-7 doi
Artificial intelligence.
Energy policy.
Energy and state.
Machine learning.
Sustainability.
Quantitative research.
Refuse and refuse disposal.
Artificial Intelligence.
Energy Policy, Economics and Management.
Machine Learning.
Sustainability.
Data Analysis and Big Data.
Waste Management/Waste Technology.
Q334-342 TA347.A78
006.3