Smart Cities and Machine Learning in Urban Health
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Smart Cities and Machine Learning in Urban Health

J. Joshua Thomas (UOW Malaysia KDU Penang University College, Malaysia), Vasiliki Geropanta (Technical University of Crete, Greece), Anna Karagianni (Technical Chamber of Greece, Greece), Vladimir Panchenko (Russian University of Transport, Russia) and Pandian Vasant (UniversitiTeknologi PETRONAS, Malaysia)
Pages: 300
ISBN13: 9781799871767|ISBN10: 1799871762|EISBN13: 9781799871781|DOI: 10.4018/978-1-7998-7176-7

Description

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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Author(s)/Editor(s) Biography

J. Joshua Thomas is a senior lecturer at KDU Penang University College, Malaysia since 2008. He obtained his PhD (Intelligent Systems Techniques) in 2015 from University Sains Malaysia, Penang, and Master’s degree in 1999 from Madurai Kamaraj University, India. From July to September 2005, he worked as a research assistant at the Artificial Intelligence Lab in University Sains Malaysia. From March 2008 to March 2010, he worked as a research associate at the same University. Currently, he is working with Machine Learning, Big Data, Data Analytics, Deep Learning, specially targeting on Convolutional Neural Networks (CNN) and Bi-directional Recurrent Neural Networks (RNN) for image tagging with embedded natural language processing, End to end steering learning systems and GAN. His work involves experimental research with software prototypes and mathematical modelling and design He is an editorial board member for the Journal of Energy Optimization and Engineering (IJEOE), and invited guest editor for Journal of Visual Languages Communication (JVLC-Elsevier). He has published more than 30 papers in leading international conference proceedings and peer reviewed journals.