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In the recent years, important key factor for urban planning is to analyze the sustainability and its functionality towards smart cities. Presently, many researchers employ the conservative machine learning based analysis but those are not appropriate for IoT based health data analysis because of their physical feature extraction and low accuracy. In this paper, we propose remote health monitoring and data analysis by integrating IoT and deep learning concepts. We proposed novel IoT based FoG assisted cloud network architecture that accumulates real-time health care data from patients via several medical IoT sensor networks, these data are analyzed using a deep learning algorithm deployed at Fog based Healthcare Platform. Furthermore, the proposed methodology is applied to the sustainable smart cities to evaluate the process for real-time. The proposed framework not only analyses the healthcare data but …