001452784 000__ 04991cam\a2200565Ii\4500
001452784 001__ 1452784
001452784 003__ OCoLC
001452784 005__ 20230314003318.0
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001452784 007__ cr\cn\nnnunnun
001452784 008__ 220712s2023\\\\sz\a\\\\ob\\\\000\0\eng\d
001452784 020__ $$a9783031068294$$q(electronic bk.)
001452784 020__ $$a3031068297$$q(electronic bk.)
001452784 020__ $$z9783031068287
001452784 020__ $$z3031068289
001452784 0247_ $$a10.1007/978-3-031-06829-4$$2doi
001452784 035__ $$aSP(OCoLC)1335125379
001452784 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dOCLCF$$dOCLCQ
001452784 049__ $$aISEA
001452784 050_4 $$aHD9715.A2
001452784 08204 $$a624.0285$$223/eng/20220712
001452784 1001_ $$aElghaish, Faris,$$eauthor.
001452784 24510 $$aBlockchain of things and deep learning applications in construction :$$bdigital construction transformation /$$cFaris Elghaish, Farzad Pour Rahimian, Tara Brooks, Nashwan Dawood, Sepehr Abrishami.
001452784 264_1 $$aCham :$$bSpringer,$$c[2023]
001452784 264_4 $$c©2023
001452784 300__ $$a1 online resource :$$billustrations (chiefly color)
001452784 336__ $$atext$$btxt$$2rdacontent
001452784 337__ $$acomputer$$bc$$2rdamedia
001452784 338__ $$aonline resource$$bcr$$2rdacarrier
001452784 504__ $$aIncludes bibliographical references.
001452784 5050_ $$aBlockchain applications in Construction: A comprehensive review -- Scientometric analysis of blockchain uses in construction -- Internet of Things (IoT) applications in Construction: A comprehensive review -- Blockchain of Things (BCoT): Beyond the concept -- Integrated Project Delivery with Blockchain: Sharing risk/reward system -- The feasibility of blockchain for Integrated Project Delivery (IPD): An exploratory Study -- A decentralised financial system-based blockchain: Towards digitalised construction -- A comprehensive solution for financial challenges in the construction industry: Blockchain-based solution -- Smart Common Data Environment (SCDE) based blockchain: An automated collaboration platform -- Deep learning applications in the construction industry: A critical analysis -- Developing a new deep learning CNN model to detect and classify highway cracks -- An optimized CNN model to detect irregular pavement distresses: Face recognition-based solution -- Integrating Artificial intelligence into immersive and drones technologies: A conceptual framework and practical use cases.
001452784 506__ $$aAccess limited to authorized users.
001452784 520__ $$aThis 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 to exploit 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 books 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.
001452784 588__ $$aDescription based on print version record.
001452784 650_0 $$aConstruction industry$$xTechnological innovations.
001452784 650_0 $$aBlockchains (Databases)
001452784 650_0 $$aInternet of things.
001452784 650_0 $$aArtificial intelligence.
001452784 655_0 $$aElectronic books.
001452784 7001_ $$aRahimian, Farzad Pour,$$eauthor.$$1https://isni.org/isni/0000000495788127
001452784 7001_ $$aBrooks, Tara,$$eauthor.
001452784 7001_ $$aDawood, Nashwan,$$eauthor.
001452784 7001_ $$aAbrishami, Sepehr,$$eauthor.
001452784 77608 $$iPrint version:$$aElghaish, Faris.$$tBlockchain of things and deep learning applications in construction.$$dCham : Springer, 2022$$z9783031068287$$w(OCoLC)1334124365
001452784 852__ $$bebk
001452784 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-031-06829-4$$zOnline Access$$91397441.1
001452784 909CO $$ooai:library.usi.edu:1452784$$pGLOBAL_SET
001452784 980__ $$aBIB
001452784 980__ $$aEBOOK
001452784 982__ $$aEbook
001452784 983__ $$aOnline
001452784 994__ $$a92$$bISE