## 2 Related Study and General Methodology  
The revolution in technology and innovations such as internet services, smart phones, smart gadgets and the emergence of fifth-generation internet services has enabled health workers and professionals to provide online health services and analyze patients' records online through cloud storage [11; 12; 14; 15]. The trend analysis of the health records of a particular geographical region, particular disease or particular patient, could be possible and further, predictions could be made with the advancement of technologies. Utilizing affective computing and advanced electronic physiological sensors, cameras, locating devices etc., machines could be able to adapt to different human states and perform diagnosis-related activities without human-initiated errors [14; 15; 16]. Such high-level computing and communication machines could collect health related data \(24\times 7\) and further, data analysis could be performed on analytical platforms. Most researchers in this area have efficiently utilized infrared based thermometers to measure human body temperature in real time [17; 18; 19]. A fog computing-based facial identification system was deployed in an industrial environment by [PERSON], et al. [20], who implemented a local binary patterns-based algorithm over a cloud connected Fog system. [PERSON] et al. [21] proposed an IoT-connected image recognition and navigation-based assistive system for visually challenged people to support them with navigation. They also implemented a cloud and IoT based system to identify the sensory environment of autism impacted individuals and implemented an assistive system to reduce the impact of surrounding over sensitive inputs by providing alerts and feedbacks. [PERSON] & [PERSON] [22] utilized an IoT-based framework for the surveillance of wildfire and a cloud system was implemented to store and analyze the collected data from internet connected sensors. [PERSON] et al. [23] focused on Internet of Things (IoT) based applications along with fog computing for monitoring, collection of data and proper analysis of collected data in drought areas. The collection and analysis parameters included humidity, temperature, soil moisture and groundwater. The data was collected remotely with the help of IoT-based modules and the analysis for drought prediction was performed efficiently. [PERSON] et al. [24; 25; 26] analyzed human body temperatures through a sensor-based IoT system in a heat stroke scenario. They utilized a specially designed sensor-based wristband to measure changes in body temperature, and the device issued an alert to the caregivers regarding adverse case conditions. [PERSON] et al. [27] utilized a sensor-based IoT and cloud system for managing the most sensitive Neonatal Intensive Care Unit (NICU) and implemented various sensors for measuring and controlling the humidity, temperature, and heart rate of the patients. The patients' health conditions were also analyzed through IoT and cloud-connected systems. A heart rate and body temperature measurement system along with an error sensing technique was developed by [PERSON] et al. [28] and achieved an error of less than 0.55 percent. Handheld devices, mobile technologies and multi-location architectures have played vital role in the implementations of disease detection technologies [29; 30; 31; 32]. It is necessary to closely monitor the anonymous spread of the present COVID-19, especially when an individual is unaware of their infection and could spread the virus unknowingly. Real time monitoring is essential to stop such infections from spreading, and the real time internet-connected cloud-based monitoring and recording of data related to human subjects such as body temperature, facial image, location of capture, etc., could be considered as the need of the hour. Such monitoring could also be required at different locations where people gather in larger numbers.