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As population growth increases rapidly, the challenges to maintain patient health records and to analyze a huge amount of patient information also increase. Thus IoT and machine learning is used to automatically collect and process the huge set of data and thereby make healthcare systems more robust and dynamic. There are various applications of machine learning in the field of healthcare. These include identifying the diseases and diagnosing, smart health record systems, drug discovering and manufacturing, developing personalized medicines, emergency care, medical image diagnosis, clinical research and trails, disease outbreak prediction, etc. [16]. Some of the real-time applications are:

 Determine sudden fluctuations in blood pressure. The observed fluctuations are analyzed and checked to see if they are normal or not and the emergency alert service is activated accordingly. Real-time monitoring is necessary to find such critical data and act accordingly. The data patterns of the patients are studied with the machine learning technique.

 Closest healthcare center can be located and an ambulance can be guided there. The body sensors collect patient data which can be used to check up on the patient’s health.

 Patient’s body posture and movement can be deducted and used to check if a patient is in need of help. Solutions on assisted living can be developed based on these types of services.