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Synopsis
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.
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Smart Cities and Machine Learning in Urban Health
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Information Science Reference, 2021
ISBN 10: 1799871770
ISBN 13: 9781799871774
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Smart Cities and Machine Learning in Urban Health
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Smart Cities and Machine Learning in Urban Health
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Smart Cities and Machine Learning in Urban Health
Published by
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ISBN 10: 1799871770
ISBN 13: 9781799871774
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Smart Cities and Machine Learning in Urban Health
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ISBN 10: 1799871770
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Smart Cities and Machine Learning in Urban Health
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ISBN 10: 1799871770
ISBN 13: 9781799871774
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Smart Cities and Machine Learning in Urban Health
Published by
Information Science Reference, 2021
ISBN 10: 1799871770
ISBN 13: 9781799871774
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Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 in. Seller Inventory # 615084927
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Smart Cities and Machine Learning in Urban Health
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ISBN 13: 9781799871774
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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. Seller Inventory # 9781799871774
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