Skip to main content
Fachgebiete
Automobil + Motoren Bauwesen + Immobilien Business IT + Informatik Elektrotechnik + Elektronik Energie + Nachhaltigkeit Finance + Banking Management + Führung Marketing + Vertrieb Maschinenbau + Werkstoffe Versicherung + Risiko
DE
EN
Bücher
Zeitschriften
Themenseiten
Organisationspsychologie Projektmanagement Marketing Smart Manufacturing
Weitere Formate
Podcasts Webinare Technik Webinare Wirtschaft Kongresse Veranstaltungskalender Awards
Jetzt Einzelzugang starten
Zugang für Unternehmen
Referenzkunden
SLX-Digitalkonferenz: Zukunftswerkstatt 2024

Mehr Umsatz mit Top-Kontakten

Am 7. Mai erfahren Sie, wie Vertriebsteams Leadgenerierung, Leadnurturing und Leadstrategien effizient steuern können.
Erweiterte Suche
Anmelden
nach oben

2021 | Buch

Introduction to Artificial Intelligence Kapitel lesen Erstes Kapitel lesen

Artificial Intelligence in Construction Engineering and Management

verfasst von: Dr. Limao Zhang, Dr. Yue Pan, Prof. Xianguo Wu, Prof. Dr. Mirosław J. Skibniewski

Verlag: Springer Singapore

Buchreihe : Lecture Notes in Civil Engineering

Enthalten in: Springer Professional "Wirtschaft+Technik" , Springer Professional "Technik" , Springer Professional "Wirtschaft"

Einloggen, um Zugang zu erhalten
insite
SUCHEN

Über dieses Buch

This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally.

Inhaltsverzeichnis

Frontmatter
Introduction to Artificial Intelligence
Abstract
The term Artificial Intelligence (AI) is a branch of computer science to make computers perform human-like tasks, and thus, computers can appropriately sense and learn inputs for perception, knowledge representation, reasoning, problem-solving, and planning. Various types of innovative AI technologies are designed to imitate the cognitive abilities of human beings, which can, therefore, deal with more complicated and ill-defined problems in an intentional, intelligent, and adaptive manner. Typically, AI can be regarded as a conjunction of machine learning and data analytics.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Knowledge Representation and Discovery
Abstract
Construction is one of the most dangerous industries worldwide, leading to a common interest in improving construction safety performance due to humanitarian reasons and rising costs of worker compensation.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Fuzzy Modeling and Reasoning
Abstract
In recent years, the construction of subway systems and underground utilities has increased dramatically due to population pressure and a lack of surface space. The tunnel boring machine (TBM) has been observed with widespread applications in tunnel construction, which can be used for excavating tunnels for nearly all types of rock and geological conditions.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Time Series Prediction
Abstract
Over the past decades, the rapid development of big cities is raising the demands of underground space utilization. One of the favorable options for urban development is to build underground tunnels. Notably, a lot of tunnels are located at a low depth in soil or soft rock zones under densely populated areas, and thus the excavation works of shallow tunnels in the soft ground tend to result in both lateral and vertical surfaces.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Information Fusion
Abstract
Information fusion is a data-driven technique to combine data from multiple sources, which can generate improved information in higher quality and accuracy for detection, inference, or characterization of an object than a single sensor alone.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Dynamic Bayesian Networks
Abstract
Underground transportation systems are in great demand in many large cities all over the world. Tunnel construction has presented a powerful momentum for rapid economic development worldwide. However, owing to various risk factors in complex project environments, safety violations occur frequently in tunnel construction, leading to large problems on the surface transport operation.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Process Mining
Abstract
BIM, as a new digital revolution for civil engineering, provides a collaborative platform to facilitate information exchange and sharing among participants in different roles for better decision-making.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Agent-Based Simulation
Abstract
In recent years, with the continuous and rapid development of the urban economy, a large number of people have migrated into cities, especially in developing and thriving countries such as China and India, imposing a rigorous challenge on urban transportation systems.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Expert Systems
Abstract
Tunnel construction entails a highly complicated project with large potential risks, which can bring enormous dangers to public safety. Numerous accidents have led to growing public concerns about prior risk identification and assessment in relation to tunnel construction safety. Risk identification plays an important role in the safety assurance process, aiming to reveal the potential safety risk and determine risk factors’ contribution to the occurrence of an accident.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Computer Vision
Abstract
Because of structure degradation, thermal movement, and other reasons, unwanted cracks will unavoidably appear in various types of structures, such as slabs, beams, columns, walls, etc. Unfortunately, harmful and corrosive chemicals, water, and salts will penetrate concrete layers through these existing cracks to exert negative impacts on structural integrity and durability (Adhikari et al. in Autom Constr 39:180–194, 2014). Thus, it is believed that cracks will speed up the degradation and aging of structure, bringing unreliability and failures in the structural systems.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Conclusions and Future Directions
Abstract
Recent decades have witnessed the rapid development of digital technology and the growth of big data in the construction industry. In particular, AI implementation, which attempts to equip machines with human-like intelligent behavior and reasoning, has gained a lot of attention.
Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski
Metadaten
Titel
Artificial Intelligence in Construction Engineering and Management
verfasst von
Dr. Limao Zhang
Dr. Yue Pan
Prof. Xianguo Wu
Prof. Dr. Mirosław J. Skibniewski
Copyright-Jahr
2021
Verlag
Springer Singapore
Electronic ISBN
978-981-16-2842-9
Print ISBN
978-981-16-2841-2
DOI
https://doi.org/10.1007/978-981-16-2842-9