Multi-Parameter Smart Health Monitoring System using Internet of Things

Low-cost, lightweight, tiny, and intelligent physiological sensor nodes have been designed in the recent technical developments in sensor systems, low power integrated circuits and wireless communications. These sensor nodes can detect analyses and transmit one or more vital signs and can be incorpo...

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Bibliographic Details
Published in2022 Second International Conference on Artificial Intelligence and Smart Energy (ICAIS) pp. 1326 - 1334
Main Authors Noel Jeygar Robert, V, Ragupathy, P, Chandraprabha, K., Nandhini, A. Sunitha, Gnanasekaran, M.
Format Conference Proceeding
LanguageEnglish
Published IEEE 23.02.2022
Subjects
Arduino-UNO
BLYNK app
Body Temperature
Economics
Health monitoring
Heart Beat Rate
Hospitals
IoT
Surveillance
Temperature measurement
Temperature sensors
Tracking
Wireless communication
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Summary:Low-cost, lightweight, tiny, and intelligent physiological sensor nodes have been designed in the recent technical developments in sensor systems, low power integrated circuits and wireless communications. These sensor nodes can detect analyses and transmit one or more vital signs and can be incorporated smoothly into healthcare social sensor networks. This network promises to change healthcare by enabling cheap, invasive, ongoing ambulatory health surveillance with online medical data updated nearly in real time. Despite several continuous research efforts, several technological, economic and societal issues are essential to the There are still some technological challenges to be addressed in order to develop diverse social sensor networks applicable to medical, economic and social and power efficiency applications. In this proposed work, novel method which is used to track patients in hospitals at home as well. The experimental analysis starts with the implementation of IoT sectors, mainly an Arduino-UNO health observation scheme. Patient's cardiac rates and body temperature is monitor in the proposed work. Arduino-UNO is used as the 8-bit microcontroller, ATMEGA 328. LM 35 is used for body temperature sensing, and XD-58C for cardiac beat rate measurement is used for DIY pulse tracker. Wi-Fi module EP8266 is used to move the data of the patient from the Arduino uno node. For IoT purposes, the BLYNK programmer is used. A new algorithm is proposed which is named as CBHA (Sensor clustering based Human Activities Recognition) that analyze state of the Patient. The data transferred from the WiFi module can be used from anywhere in the app, meaning that doctors can watch patients remotely and take prompt decisions if something goes wrong with the information that has been detected.
DOI:10.1109/ICAIS53314.2022.9742828