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Using digital and mobile technologies provides smart healthcare options for the inhabitants of urban centers. The IOT revolution that has exploded in the segment of energy, transportation, security and infrastructure will have sweeping healthcare implications. A centralized healthcare system, data collection and sharing, analysis and testing methods will usher in a new age to combat modern times. Emerging technologies like Artificial Intelligence, 5G, and smart cameras as well as innovative strategies and design are just a few of the ways smart cities can address healthcare problems. Smart cities rely heavily on sensors to perceive parameters such as temperature, humidity, allergens, pollution and power grid status. All these affect deeply the way cities function and the adaptation phase cities will pass in achieving a balanced 'out of danger' co-living with Covid-19.
The scope of this publication encompasses empirical work and scientific documentation on the two meeting areas: resilience and the smart city in the case of the Covid-19 pandemic in cities. Moreover, interface concept development and urban technologies production systems that can be replicable in many cities, including AI, machine learning and ICT are discussed. Strategically responding to system data updates enables healthcare to be smarter. Building capacity programs on how a community might gain universal access to valuable information, partners, networks, new learning paradigms and/or to eventually familiarize itself with innovative tracking, mentoring and fighting technologies and address the challenges in solving today's healthcare challenges.
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Smart Cities and Machine Learning in Urban Health
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Smart Cities and Machine Learning in Urban Health (Advances in Human Services and Public Health)
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Condizione: 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. Codice articolo 596927302
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Buch. Condizione: 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. Codice articolo 9781799871767
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