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Название: Cognitive Digital Twins for Smart Lifecycle Management of Built Environment and Infrastructure: Challenges, Opportunities
Автор: Ibrahim Yitmen
Издательство: CRC Press
Год: 2023
Страниц: 240
Язык: английский
Формат: pdf (true)
Размер: 12.2 MB
This book provides knowledge into Cognitive Digital Twins for smart lifecycle management of built environment and infrastructure focusing on challenges and opportunities. It focuses on the challenges and opportunities of data-driven cognitive systems by integrating the heterogeneous data from multiple resources that can easily be used in a Machine Learning model and adjust the algorithms. It comprises Digital Twins incorporating cognitive features that will enable sensing complex and unpredicted behavior and reason about dynamic strategies for process optimization to support decision-making in lifecycle management of the built environment and infrastructure. The book introduces the Knowledge Graph (KG)-centric framework for Cognitive Digital Twins involving process modeling and simulation, ontology-based Knowledge Graph, analytics for process optimizations, and interfaces for data operability. It offers contributions of Cognitive Digital Twins for the integration of IoT, Big Data, Artificial Intelligence, smart sensors, Machine Learning and communication technologies, all connected to a novel paradigm of self-learning hybrid models with proactive cognitive capabilities.
Автор: Ibrahim Yitmen
Издательство: CRC Press
Год: 2023
Страниц: 240
Язык: английский
Формат: pdf (true)
Размер: 12.2 MB
This book provides knowledge into Cognitive Digital Twins for smart lifecycle management of built environment and infrastructure focusing on challenges and opportunities. It focuses on the challenges and opportunities of data-driven cognitive systems by integrating the heterogeneous data from multiple resources that can easily be used in a Machine Learning model and adjust the algorithms. It comprises Digital Twins incorporating cognitive features that will enable sensing complex and unpredicted behavior and reason about dynamic strategies for process optimization to support decision-making in lifecycle management of the built environment and infrastructure. The book introduces the Knowledge Graph (KG)-centric framework for Cognitive Digital Twins involving process modeling and simulation, ontology-based Knowledge Graph, analytics for process optimizations, and interfaces for data operability. It offers contributions of Cognitive Digital Twins for the integration of IoT, Big Data, Artificial Intelligence, smart sensors, Machine Learning and communication technologies, all connected to a novel paradigm of self-learning hybrid models with proactive cognitive capabilities.