Smart Cities and Machine Learning in Urban Health

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.

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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.