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COVID-19 humanitarian catastrophe, the Artificial Intelligence is a premier technology in the healthcare domain that has emerged to a great extent. In recent two years, a surge of eminent research has considerably contributed to diminish the COVID-19 scourge by enacting different ways of using IoT. The ongoing global health emergency teaches the whole world to enhance and strengthen the capability of current health systems in such a way as to provide the bedrock for future pandemics preparedness. The likelihood of even more severe future health challenges should create a compelling commitment to invest in the development of adequate testing and surveillance services, routine health monitoring, and onset symptoms detection of viral infection in the novel futuristic health systems. Conspicuously, this paper proposed a non-invasive urine-based model for passive health monitoring to predict viral COVID-19 infection in the home environment. It consists of four notable layers namely, automated data acquisition, fog layer, cloud layer, and communication layer. These mentioned layers include IoT sensors embedded in the smart toilet for data acquisition, processes and analyses.
About the author
Prof. Dr. Dian Damayanti, Work EAI publisher, Igi Global Publisher, IEEE and Mendeley Elsevier Senior scientist, Community manager, Managing director, innovation & business Book, Chief Advisor, Reviewer, Editor in Chief, Committee United Nations Prof. Dr. Esti Royani, Drs. Rusna Ristasa, M.Pd Work Tutor and Director Universitas Terbuka
