Vasilis Sarhosis – författare

Digital Transformation in the Construction Industry: Sustainability, Resilience, and Data-Centric Engineering delivers timely and much sought-after guidance related to novel, digital-first practices and the latest technological tools, the gradual adoption of which is being embraced to significantly reshape the way buildings and other infrastructure assets are designed, constructed, operated, and maintained.Methodological and practice-informed investigations by scholars and researchers from across the globe, providing a wealth of knowledge relevant for, and applicable to, different geographical and economic contexts, are coherently collated in this edited volume. This systematic analysis of cutting-edge developments (such as Building Information Modeling, Internet of Things, Artificial Intelligence, Machine Learning, Big Data, Augmented Reality, Virtual Reality, 3D Printing, and Structural Health Monitoring) is accompanied by discussions on challenges and opportunities that digitalization engenders. Additionally, real-word case studies enrich the coverage, highlighting how these innovative solutions can contribute to establishing working efficiencies that can at the same time aid the impactful realization of globally recognized sustainability goals.Readers in both academic and professional settings are, therefore, not only equipped with a comprehensive overview of the state of the art but also offered an insightful reference resource for future works in the area.Covers emerging technologies comprehensivelyEmphasizes the use of digital tools to support achievements for worldwide net zero targetsFocuses on lean and agile construction practices to improve project efficiency and reduce waste

Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers.

Data Driven Methods for Civil Structural Health Monitoring and Resilience: Latest Developments and Applications provides a comprehensive overview of data-driven methods for structural health monitoring (SHM) and resilience of civil engineering structures, mostly based on artificial intelligence or other advanced data science techniques. This allows existing structures to be turned into smart structures, thereby allowing them to provide intelligible information about their state of health and performance on a continuous, relatively real-time basis. Artificial-intelligence-based methodologies are becoming increasingly more attractive for civil engineering and SHM applications; machine learning and deep learning methods can be applied and further developed to transform the available data into valuable information for engineers and decision makers.

The book focuses on all typological aspects of arches and vaults within the heritage of design and construction, while bringing attention to new “green” materials, promoting a circular economy informed by limitations caused by global warming.