Data Science Data Visualization And Digital Twins


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Data Science, Data Visualization, and Digital Twins


Data Science, Data Visualization, and Digital Twins

Author: Sara Shirowzhan

language: en

Publisher: BoD – Books on Demand

Release Date: 2022-02-02


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Real-time, web-based, and interactive visualisations are proven to be outstanding methodologies and tools in numerous fields when knowledge in sophisticated data science and visualisation techniques is available. The rationale for this is because modern data science analytical approaches like machine/deep learning or artificial intelligence, as well as digital twinning, promise to give data insights, enable informed decision-making, and facilitate rich interactions among stakeholders.The benefits of data visualisation, data science, and digital twinning technologies motivate this book, which exhibits and presents numerous developed and advanced data science and visualisation approaches. Chapters cover such topics as deep learning techniques, web and dashboard-based visualisations during the COVID pandemic, 3D modelling of trees for mobile communications, digital twinning in the mining industry, data science libraries, and potential areas of future data science development.

Digital Twins for Smart Cities and Villages


Digital Twins for Smart Cities and Villages

Author: Sailesh Iyer

language: en

Publisher: Elsevier

Release Date: 2024-10-17


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Digital Twins for Smart Cities and Villages provides a holistic view of digital twin technology and how it can be deployed to develop smart cities and smart villages. Smart manufacturing, smart healthcare, smart education, smart agriculture, smart rural solutions, and related methodologies using digital twins are discussed, including challenges in deployment, their solutions and future roadmaps. This knowledge, enriched by a variety of case studies presented in the book, may empower readers with new capabilities for new research as well as new tasks and strategies for practical implementation and real-world problem solving.The book is thoughtfully structured, starting from the background of digital twin concepts and basic know-how to serve the needs of those new to the subject. It continues with implementation to facilitate and improve management in several urban contexts, infrastructures, and more. Global case study assessments further provide a deep characterization of the state-of-the-art in digital twin in urban and rural contexts. - Uniquely focuses on applications for smart cities and villages, including smart services for health, education, mobility, and agriculture - Provides use cases and practical deployment of research involved in the emerging uses of digital twins - Discusses all pertinent issues, challenges, and possible solutions instrumental in implementing digital twins smart solutions in this context - Edited and authored by a global team of experts in their given fields

New Approaches to Data Analytics and Internet of Things Through Digital Twin


New Approaches to Data Analytics and Internet of Things Through Digital Twin

Author: Periyaswami, Karthikeyan

language: en

Publisher: IGI Global

Release Date: 2022-09-30


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Even though many data analytics tools have been developed in the past years, their usage in the field of cyber twin warrants new approaches that consider various aspects including unified data representation, zero-day attack detection, data sharing across threat detection systems, real-time analysis, sampling, dimensionality reduction, resource-constrained data processing, and time series analysis for anomaly detection. Further study is required to fully understand the opportunities, benefits, and difficulties of data analytics and the internet of things in today’s modern world. New Approaches to Data Analytics and Internet of Things Through Digital Twin considers how data analytics and the internet of things can be used successfully within the field of digital twin as well as the potential future directions of these technologies. Covering key topics such as edge networks, deep learning, intelligent data analytics, and knowledge discovery, this reference work is ideal for computer scientists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.