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Top1. Introduction
Today, health prediction systems are the most popular in the world. A health prediction system helps to overcome some of the common issues of sudden changes in patient emergencies, such as car accidents, the arrival of an ambulance during natural disasters, as well as routine outpatient needs, which drive demand for healthcare services in a number of hospitals (Mtonga, K., 2019). The real-time data is not able to get by the hospitals. The IoT is a communication channel that remotely connects computers and physical items It also uses cutting-edge microprocessor processors to deliver real-time data collection.
Healthcare is defined as the promotion and preservation of health through disease diagnosis and prevention. SPECT, MRI, PET, and CT diagnostic devices are used to find the ruptures below the skin on a human body. Similarly, some of the other conditions like epilepsy and heart attack can be monitored (Mosenia, A., 2017). The increase in the population and the irregular development of chronic diseases have put pressure on modern healthcare systems. These issues demands the medical resources including nurses, hospital beds, and doctors at a higher requirement (Iqbal, N., 2021). To reduce such demands, healthcare initiatives aimed at improving the essence and standards of healthcare services are required (Wu, T., 2017). IoT offers a variety of options in healthcare systems and medical facilities. For example, RFID technology used to minimize medical expenditures and improve healthcare delivery. Through healthcare monitoring programmes, doctors may quickly monitor patients' cardiac impulses, allowing them to deliver an accurate diagnosis (Birje, M. N., & Hanji, S. S. 2020). To offer stable wireless data transfer, a variety of wearable appliances have been developed. There are several benefits of IoT in healthcare domain, at same time both IT and medical professionals are more concerned about data security (Shahbazi, Z., 2020). As a result, various studies were carried out to develop new technology by combining IoT and ML with data integrity techniques.
IoT (Gupta, P. K., 2017) is one of the rapidly growing techniques for next-generation. It refers to the association of uniquely identified smart devices and gadgets. IoT is surrounded by a variety of things that are hidden throughout the environment (Verma, P., 2018). Today Health Monitoring systems becomes one of the most common research applications in smart wearable electronics. Smart HM combines smart computing with remote HM and the Internet of Things (Subramaniyam, M., 2018). An accelerometer, a cardioverter-defibrillator, and a pacemaker are examples of wearable or implanted devices that make up body sensor networks (BSN) (Saheb, T., & Izadi, L. 2019). BSN is an essential component of the Internet of Things (Chui, K. T., 2019; Jagadeeswari, V., 2018). These gadgets are used to collect critical information such as adequate changes in well-being restraint and to refresh the weightiness of the therapeutic parameters over a predetermined period (Ganesan, M., & Sivakumar, N. 2019). When a patient’s health state changes, then the patients' data is remotely collected through IoT-enabled medical devices, and sent to clinical database for further process (Kumar, P. M., 2018; Kamble, A., 2018). IoT lowers costs and expands the reach of medical facilities to rural areas, while also improving the quality of services (Ani, R., 2017). This type of technology can help chronic HD patients. Patients with these conditions face a high risk of death because their heart function could stop at any time (Fayoumi, A., & BinSalman, K. 2018) Obesity, stress, oily food and a lack of exercise, in combination with genetic factors, are the main causes of such disorders. Furthermore, hypertension, diabetes, raised blood fat and weight gain associated with menopause might lead to a heart attack in women (Akbulut, F. P., & Akan, A. 2018).