elghaish faris (11 Ergebnisse)

Paperback. Zustand: Brand New. 413 pages. 9.50x6.75x1.00 inches. In Stock.

Zustand: New. In.

Zustand: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | This book significantly contributes the digital transformation of construction. The book explores the capabilities of deep learning to provide smart solutions for the construction industry, particularly in areas of managing equipment, design optimization, energy optimization and detect cracks for buildings and highways. It provides conceptual solutions but also practical techniques. A new deep learning CNN-based highway cracks detection is demonstrated, and its usefulness is tested. The resulting deep learning CNN model will enable users to scan long distance of highway and detect types of cracks accurately in a very short time compared to traditional approaches.The book explores the integration of IoT and blockchain to provide practical solutions to tackle existing challenges like the endemic fragmentation in supply chain, the need for monitoring construction projects remotely and tracking equipment on the site. The Blockchain of Things (BCoT) concept has been introduced toexploit the advantages of IoT and blockchain, and different applications were developed based on this integration in leading industries such as shared economy and health care. Workable potential use cases to exploit successful utilization of BCoT for the construction industry are explored in the book¿s chapters.This book will appeal to researchers in providing a comprehensive review of related literature on blockchain, the IoT and construction identify gaps and offer a springboard for future research. Construction practitioners, research and development institutes and policy makers will also benefit from its usefulness as a reference book and collection of case studies on the application of these new approaches in construction.

Zustand: New.

Taschenbuch. Zustand: Neu. Blockchain of Things and Deep Learning Applications in Construction | Digital Construction Transformation | Faris Elghaish (u. a.) | Taschenbuch | xiii | Englisch | 2023 | Springer | EAN 9783031068317 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Gebunden. Zustand: New. Farzad Pour Rahimian is a Professor of Digital Engineering and Manufacturing at Teesside University, UK.Jack Steven Goulding is Professor of Construction Project Management at the University of Wolverhampton, UK a.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book significantly contributes the digital transformation of construction. The book explores the capabilities of deep learning to provide smart solutions for the construction industry, particularly in areas of managing equipment, design optimization, energy optimization and detect cracks for buildings and highways. It provides conceptual solutions but also practical techniques. A new deep learning CNN-based highway cracks detection is demonstrated, and its usefulness is tested. The resulting deep learning CNN model will enable users to scan long distance of highway and detect types of cracks accurately in a very short time compared to traditional approaches.The book explores the integration of IoT and blockchain to provide practical solutions to tackle existing challenges like the endemic fragmentation in supply chain, the need for monitoring construction projects remotely and tracking equipment on the site. The Blockchain of Things (BCoT) concept has been introduced toexploit the advantages of IoT and blockchain, and different applications were developed based on this integration in leading industries such as shared economy and health care. Workable potential use cases to exploit successful utilization of BCoT for the construction industry are explored in the book's chapters.This book will appeal to researchers in providing a comprehensive review of related literature on blockchain, the IoT and construction identify gaps and offer a springboard for future research. Construction practitioners, research and development institutes and policy makers will also benefit from its usefulness as a reference book and collection of case studies on the application of these new approaches in construction.

Hardcover. Zustand: Brand New. 146 pages. 9.25x6.10x0.47 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book significantly contributes the digital transformation of construction. The book explores the capabilities of deep learning to provide smart solutions for the construction industry, particularly in areas of managing equipment, design optimization, energy optimization and detect cracks for buildings and highways. It provides conceptual solutions but also practical techniques. A new deep learning CNN-based highway cracks detection is demonstrated, and its usefulness is tested. The resulting deep learning CNN model will enable users to scan long distance of highway and detect types of cracks accurately in a very short time compared to traditional approaches.The book explores the integration of IoT and blockchain to provide practical solutions to tackle existing challenges like the endemic fragmentation in supply chain, the need for monitoring construction projects remotely and tracking equipment on the site. The Blockchain of Things (BCoT) concept has been introduced toexploit the advantages of IoT and blockchain, and different applications were developed based on this integration in leading industries such as shared economy and health care. Workable potential use cases to exploit successful utilization of BCoT for the construction industry are explored in the book's chapters.This book will appeal to researchers in providing a comprehensive review of related literature on blockchain, the IoT and construction identify gaps and offer a springboard for future research. Construction practitioners, research and development institutes and policy makers will also benefit from its usefulness as a reference book and collection of case studies on the application of these new approaches in construction.

Paperback. Zustand: Brand New. 206 pages. 9.25x6.10x0.44 inches. In Stock.

Hardcover. Zustand: Brand New. 206 pages. 9.25x6.10x0.67 inches. In Stock.