LOW COST REMOTE REALTIME HEALTH CARE MONITORING SYSTEM WITH INTEGRATED IOT AND CLOUD

摘要

LOW COST REMOTE REALTIME HEALTH CARE MONITORING SYSTEM WITH INTEGRATED IOT AND CLOUD Remote monitoring of health care system is promoted with revolutionized modern technologies in the recent past due to the development of Information and Communication technologies for effective treatment and administration. GSM techniques were used in earlier days to send the SMS about the patient conditions to the doctors or care takers. The main drawback of this system is that the entire case history of the patient will not be displayed only current data will be updated. There are two major challenges faced in the remote health care monitoring system are caring patients in the environments like residence and intensive care units and rising health care cost. The present health care system is completely restructured using IOT in socio-technological and economical aspects. Applications Internet of Things (IOT) spreads out in different domains especially in the field of medical and health care. With this in mind an Advanced Patient Health Care System is developed by integrating cloud and IOT. The system is built with the Temperature Sensor, Glucose sensor and Pulse sensor. The sensors provide a monitoring data continuously to both data centre and observation server simultaneously and to provide data retrieval capability whenever needed with the help of integrated cloud and IOT platform. Moreover the system is interfaced with- the THINK VIEW Application software, which graphically displays the sensed temperature, blood glucose and pulse rate of the ill patient to the authenticated person or to the care taker once in every 60 seconds. The system uses a photodiode which is attached to the glucose sensor to measure the blood glucose level without collecting raw blood sample from the patient by keeping the skin as a medium is one of the main features of this proposed health care system. t The system is tested with the patients of different category like sleeping, sitting and walking graphical representation of the monitored data makes the patient themselves to know about whether they are normal or abnormal.