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Author: J Joshua Thomas
Publisher: Information Science Reference
ISBN: 9781799871774
Category :
Languages : en
Pages : 296
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Book Description
The perception of smart cities encompasses a strategy that uses different types of technologies, artificial intelligence (AI), and machine learning and in which, through the internet of things (IoT) and sensor-based data collection, the strategy extrapolates information using insights gained from that data to manage or monitor or track assets, resources, and services efficiently in an urban area. Both these models deeply affect the localities where they are applied and can create together immense possibilities for urban recovery, better quality of life, physical and mental health protection, and economic and social redevelopment. Smart Cities and Machine Learning in Urban Health promotes interdisciplinary work that develops and illustrates the concept of resilience in relation to smart city and machine learning. The book examines the ability of an area and its communities to recover quickly from difficulties; the rigidness and resistance of an area and its communities to possible crisis; the ability of an area, its communities, infrastructure, and business to spring back into shape; and the responsiveness and mitigation towards the crisis with a special look at the impact of the COVID-19 pandemic. The research's theoretical foundation rests on a wide range of non-architectural sources, primarily AI, sociology, urban studies, and technological development, but it explores everything on cases taken from real cities, thus transforming them into pieces of architectural interest. Covering topics such as carbon emissions, digital healthcare systems, and urban transformation, this book is an essential resource for graduate and post-graduate students, policymakers, researchers, university faculty, engineers, public management, hospital administration, professors, and academicians.
Author: J Joshua Thomas
Publisher: Information Science Reference
ISBN: 9781799871774
Category :
Languages : en
Pages : 296
Get Book Here
Book Description
The perception of smart cities encompasses a strategy that uses different types of technologies, artificial intelligence (AI), and machine learning and in which, through the internet of things (IoT) and sensor-based data collection, the strategy extrapolates information using insights gained from that data to manage or monitor or track assets, resources, and services efficiently in an urban area. Both these models deeply affect the localities where they are applied and can create together immense possibilities for urban recovery, better quality of life, physical and mental health protection, and economic and social redevelopment. Smart Cities and Machine Learning in Urban Health promotes interdisciplinary work that develops and illustrates the concept of resilience in relation to smart city and machine learning. The book examines the ability of an area and its communities to recover quickly from difficulties; the rigidness and resistance of an area and its communities to possible crisis; the ability of an area, its communities, infrastructure, and business to spring back into shape; and the responsiveness and mitigation towards the crisis with a special look at the impact of the COVID-19 pandemic. The research's theoretical foundation rests on a wide range of non-architectural sources, primarily AI, sociology, urban studies, and technological development, but it explores everything on cases taken from real cities, thus transforming them into pieces of architectural interest. Covering topics such as carbon emissions, digital healthcare systems, and urban transformation, this book is an essential resource for graduate and post-graduate students, policymakers, researchers, university faculty, engineers, public management, hospital administration, professors, and academicians.
Author: Wenzhong Shi
Publisher: Springer Nature
ISBN: 9811589836
Category : Social Science
Languages : en
Pages : 941
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Book Description
This open access book is the first to systematically introduce the principles of urban informatics and its application to every aspect of the city that involves its functioning, control, management, and future planning. It introduces new models and tools being developed to understand and implement these technologies that enable cities to function more efficiently – to become ‘smart’ and ‘sustainable’. The smart city has quickly emerged as computers have become ever smaller to the point where they can be embedded into the very fabric of the city, as well as being central to new ways in which the population can communicate and act. When cities are wired in this way, they have the potential to become sentient and responsive, generating massive streams of ‘big’ data in real time as well as providing immense opportunities for extracting new forms of urban data through crowdsourcing. This book offers a comprehensive review of the methods that form the core of urban informatics from various kinds of urban remote sensing to new approaches to machine learning and statistical modelling. It provides a detailed technical introduction to the wide array of tools information scientists need to develop the key urban analytics that are fundamental to learning about the smart city, and it outlines ways in which these tools can be used to inform design and policy so that cities can become more efficient with a greater concern for environment and equity.
Author: Andriy Burkov
Publisher:
ISBN: 9781999579500
Category : Machine learning
Languages : en
Pages : 141
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Book Description
Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue.
Author: Silvio Carta
Publisher: John Wiley & Sons
ISBN: 111974962X
Category : Architecture
Languages : en
Pages : 676
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Book Description
Machine Learning and the City Explore the applications of machine learning and artificial intelligence to the built environment Machine Learning and the City: Applications in Architecture and Urban Design delivers a robust exploration of machine learning (ML) and artificial intelligence (AI) in the context of the built environment. Relevant contributions from leading scholars in their respective fields describe the ideas and techniques that underpin ML and AI, how to begin using ML and AI in urban design, and the likely impact of ML and AI on the future of city design and planning. Each section couples theoretical and technical chapters, authoritative references, and concrete examples and projects that illustrate the efficacy and power of machine learning in urban design. The book also includes: An introduction to the probabilistic logic that underpins machine learning Comprehensive explorations of the applications of machine learning and artificial intelligence to urban environments Practical discussions of the consequences of applied machine learning and the future of urban design Perfect for designers approaching machine learning and AI for the first time, Machine Learning and the City: Applications in Architecture and Urban Design will also earn a place in the libraries of urban planners and engineers involved in urban design.
Author: Armand Prieditis
Publisher: Morgan Kaufmann
ISBN: 1483298663
Category : Computers
Languages : en
Pages : 606
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Book Description
Machine Learning Proceedings 1995
Author: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
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Book Description
An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
Author: Ethem Alpaydin
Publisher: MIT Press
ISBN: 0262028182
Category : Computers
Languages : en
Pages : 639
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Book Description
Introduction -- Supervised learning -- Bayesian decision theory -- Parametric methods -- Multivariate methods -- Dimensionality reduction -- Clustering -- Nonparametric methods -- Decision trees -- Linear discrimination -- Multilayer perceptrons -- Local models -- Kernel machines -- Graphical models -- Brief contents -- Hidden markov models -- Bayesian estimation -- Combining multiple learners -- Reinforcement learning -- Design and analysis of machine learning experiments.
Author: Christopher Grant Kirwan
Publisher: Elsevier
ISBN: 0128170247
Category : Political Science
Languages : en
Pages : 274
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Book Description
Smart Cities and Artificial Intelligence offers a comprehensive view of how cities are evolving as smart ecosystems through the convergence of technologies incorporating machine learning and neural network capabilities, geospatial intelligence, data analytics and visualization, sensors, and smart connected objects. These recent advances in AI move us closer to developing urban operating systems that simulate human, machine, and environmental patterns from transportation infrastructure to communication networks. Exploring cities as real-time, living, dynamic systems, and providing tools and formats including generative design and living lab models that support cities to become self-regulating, this book provides readers with a conceptual and practical knowledge base to grasp and apply the key principles required in the planning, design, and operations of smart cities. Smart Cities and Artificial Intelligence brings a multidisciplinary, integrated approach, examining how the digital and physical worlds are converging, and how a new combination of human and machine intelligence is transforming the experience of the urban environment. It presents a fresh holistic understanding of smart cities through an interconnected stream of theory, planning and design methodologies, system architecture, and the application of smart city functions, with the ultimate purpose of making cities more liveable, sustainable, and self-sufficient.
Author: Uttam Ghosh
Publisher: Springer Nature
ISBN: 3030720659
Category : Technology & Engineering
Languages : en
Pages : 411
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Book Description
This book presents the latest advances in computational intelligence and data analytics for sustainable future smart cities. It focuses on computational intelligence and data analytics to bring together the smart city and sustainable city endeavors. It also discusses new models, practical solutions and technological advances related to the development and the transformation of cities through machine intelligence and big data models and techniques. This book is helpful for students and researchers as well as practitioners.
Author: John Anderson
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
