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Automation and Robotics in the Architecture, Engineering, and Construction Industry
Automation and Robotics in the Architecture, Engineering, and Construction Industry provides distinct and unified insight into current and future construction robotics, offering readers a comprehensive perspective for constructing a road map and illuminating improvements for a successful transition towards construction robotization. The book covers the fundamentals and applications of robotics, autonomous vehicles, and human-perceptive machines at construction sites. Through theoretical and experimental analyses, it examines the potential of robotics and automated systems for current and future fieldwork operations and identifies the factors that determine their implementation pace, adoption scale, and ubiquity throughout the industry. The book evaluates the technical, societal, and economic aspects of adopting robots in construction, both as standalone and collaborative systems, which in return can afford the opportunity to investigate these AI-enabled machines more systematically.
Renewable Energy for Buildings
The book covers practical applications and experimental results of integrating renewable energy technologies, energy storage facilities, and intelligent control and operation techniques into building energy systems. It introduces practical approaches to improving the energy systems of buildings in order to reduce energy consumption and cost. Renewable Energy for Buildings is suitable for retrofit engineers, energy engineers, and professionals, as well as researchers and developers in electrical engineering, architectural engineering, and mechanical engineering. Moreover, it can be used by undergraduate and graduate students to become familiar with the most recent developments in building energy systems. Examines the most recent developments in building energy systems; Looks at practical applications and theoretical aspects; Includes case studies.
Advances in Informatics and Computing in Civil and Construction Engineering
This proceedings volume chronicles the papers presented at the 35th CIB W78 2018 Conference: IT in Design, Construction, and Management, held in Chicago, IL, USA, in October 2018. The theme of the conference focused on fostering, encouraging, and promoting research and development in the application of integrated information technology (IT) throughout the life-cycle of the design, construction, and occupancy of buildings and related facilities. The CIB – International Council for Research and Innovation in Building Construction – was established in 1953 as an association whose objectives were to stimulate and facilitate international cooperation and information exchange between governmental research institutes in the building and construction sector, with an emphasis on those institutes engaged in technical fields of research. The conference brought together more than 200 scholars from 40 countries, who presented the innovative concepts and methods featured in this collection of papers.
Application of Machine Learning and Deep Learning Methods to Power System Problems
This book evaluates the role of innovative machine learning and deep learning methods in dealing with power system issues, concentrating on recent developments and advances that improve planning, operation, and control of power systems. Cutting-edge case studies from around the world consider prediction, classification, clustering, and fault/event detection in power systems, providing effective and promising solutions for many novel challenges faced by power system operators. Written by leading experts, the book will be an ideal resource for researchers and engineers working in the electrical power engineering and power system planning communities, as well as students in advanced graduate-level courses.
Computational Techniques in Neuroscience
The text discusses the techniques of deep learning and machine learning in the field of neuroscience, engineering approaches to study the brain structure and dynamics, convolutional networks for fast, energy-efficient neuromorphic computing, and reinforcement learning in feedback control. It showcases case studies in neural data analysis. Features: Focuses on neuron modeling, development, and direction of neural circuits to explain perception, behavior, and biologically inspired intelligent agents for decision making Showcases important aspects such as human behavior prediction using smart technologies and understanding the modeling of nervous systems Discusses nature-inspired algorithms suc...
Intelligent Systems for Human Health and Well-Being
Antonio Di Tecco’s research study focused on creating intelligent systems to improve user experience. Indeed, during his academic journey, he proved how to detect various human states with high accuracy. His results can be applied in healthcare, social support, education, and industry. In particular, they can enhance human-machine interaction and so increase human well-being. Hence, this dissertation presents how to design and develop intelligent systems to reach this goal.
Proceedings of the Third International Conference on Computational Intelligence and Informatics
This book features high-quality papers presented at the International Conference on Computational Intelligence and Informatics (ICCII 2018), which was held on 28–29 December 2018 at the Department of Computer Science and Engineering, JNTUH College of Engineering, Hyderabad, India. The papers focus on topics such as data mining, wireless sensor networks, parallel computing, image processing, network security, MANETS, natural language processing and Internet of things.
Gamification of telematics data to enhance operators’ behaviour for improvement of machine productivity in loading cycles
Construction industry is suffering from low productivity rate in various projects such as excavation. Although this issue is discussed in literature and several approaches are proposed to address it, productivity rate is still low in construction industry compared to other domains like manufacturing. A gamified platform in which different operators from different organizations can share their achievements, or can get scored and ranked in a leader-board will potentially address this issue.
