Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research
| Author | : Gaurav Tripathi |
| Publisher | : Springer Nature |
| Total Pages | : 339 |
| Release | : |
| Genre | : |
| ISBN | : 9819716853 |
Big Data Artificial Intelligence And Data Analytics In Climate Change Research
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Big Data, Artificial Intelligence, and Data Analytics in Climate Change Research
| Author | : Gaurav Tripathi |
| Publisher | : Springer |
| Total Pages | : 0 |
| Release | : 2024-06-08 |
| Genre | : Science |
| ISBN | : 9789819716845 |
This book explores the potential of big data, artificial intelligence (AI), and data analytics to address climate change and achieve the Sustainable Development Goals (SDGs). Furthermore, the book covers a wide range of related topics, including climate change data sources, big data analytics techniques, remote sensing, renewable energy, open data, public–private partnerships, ethical and legal issues, and case studies of successful applications. The book also discusses the challenges and opportunities presented by these technologies and provides insights into future research directions. In order to address climate change and achieve the SDGs, it is crucial to understand the complex interplay between climate and environmental factors. The use of big data, AI, and data analytics can play a vital role in this effort by providing the means to collect, process, and analyze vast amounts of environmental data. This book is an essential resource for researchers, policymakers, and practitioners interested in leveraging these technologies to tackle the pressing challenge of climate change and achieve the SDGs.
Data Science Applied to Sustainability Analysis
| Author | : Jennifer Dunn |
| Publisher | : Elsevier |
| Total Pages | : 312 |
| Release | : 2021-05-11 |
| Genre | : Science |
| ISBN | : 0128179775 |
Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. - Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery - Includes considerations sustainability analysts must evaluate when applying big data - Features case studies illustrating the application of data science in sustainability analyses
Big Data Mining for Climate Change
| Author | : Zhihua Zhang |
| Publisher | : Elsevier |
| Total Pages | : 344 |
| Release | : 2019-11-20 |
| Genre | : Science |
| ISBN | : 0128187034 |
Climate change mechanisms, impacts, risks, mitigation, adaption, and governance are widely recognized as the biggest, most interconnected problem facing humanity. Big Data Mining for Climate Change addresses one of the fundamental issues facing scientists of climate or the environment: how to manage the vast amount of information available and analyse it. The resulting integrated and interdisciplinary big data mining approaches are emerging, partially with the help of the United Nation's big data climate challenge, some of which are recommended widely as new approaches for climate change research. Big Data Mining for Climate Change delivers a rich understanding of climate-related big data techniques and highlights how to navigate huge amount of climate data and resources available using big data applications. It guides future directions and will boom big-data-driven researches on modeling, diagnosing and predicting climate change and mitigating related impacts. This book mainly focuses on climate network models, deep learning techniques for climate dynamics, automated feature extraction of climate variability, and sparsification of big climate data. It also includes a revelatory exploration of big-data-driven low-carbon economy and management. Its content provides cutting-edge knowledge for scientists and advanced students studying climate change from various disciplines, including atmospheric, oceanic and environmental sciences; geography, ecology, energy, economics, management, engineering, and public policy.
Encyclopedia of Data Science and Machine Learning
| Author | : Wang, John |
| Publisher | : IGI Global |
| Total Pages | : 3296 |
| Release | : 2023-01-20 |
| Genre | : Computers |
| ISBN | : 1799892212 |
Big data and machine learning are driving the Fourth Industrial Revolution. With the age of big data upon us, we risk drowning in a flood of digital data. Big data has now become a critical part of both the business world and daily life, as the synthesis and synergy of machine learning and big data has enormous potential. Big data and machine learning are projected to not only maximize citizen wealth, but also promote societal health. As big data continues to evolve and the demand for professionals in the field increases, access to the most current information about the concepts, issues, trends, and technologies in this interdisciplinary area is needed. The Encyclopedia of Data Science and Machine Learning examines current, state-of-the-art research in the areas of data science, machine learning, data mining, and more. It provides an international forum for experts within these fields to advance the knowledge and practice in all facets of big data and machine learning, emphasizing emerging theories, principals, models, processes, and applications to inspire and circulate innovative findings into research, business, and communities. Covering topics such as benefit management, recommendation system analysis, and global software development, this expansive reference provides a dynamic resource for data scientists, data analysts, computer scientists, technical managers, corporate executives, students and educators of higher education, government officials, researchers, and academicians.
Applications of Big Data in Large- and Small-Scale Systems
| Author | : Goundar, Sam |
| Publisher | : IGI Global |
| Total Pages | : 377 |
| Release | : 2021-01-15 |
| Genre | : Computers |
| ISBN | : 1799866750 |
With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.
The Power of Data: Driving Climate Change with Data Science and Artificial Intelligence Innovations
| Author | : Aboul Ella Hassanien |
| Publisher | : Springer Nature |
| Total Pages | : 255 |
| Release | : 2023-03-11 |
| Genre | : Computers |
| ISBN | : 3031224566 |
This book discusses the advances of artificial intelligence and data sciences in climate change and provides the power of the climate data that is used as inputs to artificial intelligence systems. It is a good resource for researchers and professionals who work in the field of data sciences, artificial intelligence, and climate change applications.
Internet of Things and Big Data Analytics for a Green Environment
| Author | : Yousef Farhaoui |
| Publisher | : CRC Press |
| Total Pages | : 358 |
| Release | : 2024-11-27 |
| Genre | : Computers |
| ISBN | : 1040224733 |
This book studies the evolution of sustainable green smart cities and demonstrates solutions for green environmental issues using modern industrial IoT solutions. It is a ready reference with guidelines and a conceptual framework for context-aware product development and research in the IoT paradigm and Big Data Analytics for a Green Environment. It brings together the most recent advances in IoT and Big Data in Green Environments, emerging aspects of the IoT and Big Data for Green Cities, explores key technologies, and develops new applications in this research field. Key Features: • Discusses the framework for development and research in the IoT Paradigm and Big Data Analytics. • Highlights threats to the IoT architecture and Big Data Analytics for a Green Environment. • Present the I-IoT architecture, I-IoT applications, and their characteristics for a Green Environment. • Provides a systematic overview of the state-of-the-art research efforts. • Introduces necessary components and knowledge to become a vital part of the IoT revolution for a Green Environment. This book is for professionals and researchers interested in the emerging technology of sustainable development, green cities, and Green Environment.
Big data analytics for smart healthcare applications
| Author | : Celestine Iwendi |
| Publisher | : Frontiers Media SA |
| Total Pages | : 1365 |
| Release | : 2023-04-17 |
| Genre | : Medical |
| ISBN | : 2832515754 |
Artificial Intelligence and Big Data Analytics for Smart Healthcare
| Author | : Miltiadis Lytras |
| Publisher | : Academic Press |
| Total Pages | : 292 |
| Release | : 2021-10-22 |
| Genre | : Medical |
| ISBN | : 0128220627 |
Artificial Intelligence and Big Data Analytics for Smart Healthcare serves as a key reference for practitioners and experts involved in healthcare as they strive to enhance the value added of healthcare and develop more sustainable healthcare systems. It brings together insights from emerging sophisticated information and communication technologies such as big data analytics, artificial intelligence, machine learning, data science, medical intelligence, and, by dwelling on their current and prospective applications, highlights managerial and policymaking challenges they may generate. The book is split into five sections: big data infrastructure, framework and design for smart healthcare; signal processing techniques for smart healthcare applications; business analytics (descriptive, diagnostic, predictive and prescriptive) for smart healthcare; emerging tools and techniques for smart healthcare; and challenges (security, privacy, and policy) in big data for smart healthcare. The content is carefully developed to be understandable to different members of healthcare chain to leverage collaborations with researchers and industry. - Presents a holistic discussion on the new landscape of data driven medical technologies including Big Data, Analytics, Artificial Intelligence, Machine Learning, and Precision Medicine - Discusses such technologies with case study driven approach with reference to real world application and systems, to make easier the understanding to the reader not familiar with them - Encompasses an international collaboration perspective, providing understandable knowledge to professionals involved with healthcare to leverage productive partnerships with technology developers
