R. Priya, A. Vaidya, Mohit Thorat, Vinit Motwani, Chetas Shinde
{"title":"SAARTHI : Real-Time Monitoring of Patients by Wearable Device","authors":"R. Priya, A. Vaidya, Mohit Thorat, Vinit Motwani, Chetas Shinde","doi":"10.1109/ACCTHPA49271.2020.9213239","DOIUrl":null,"url":null,"abstract":"The proposal comprises using cutting edge technology of Internet of Things (IoT), Cloud and AI-based analytics to monitor and provide timely and proactive alerts to not only patients but also healthcare workers such as doctors, nursing homes and even remotely located family members about patient’s critical health parameters. The measured raw data will record live location and calculate heart rate, pulse, temperature and detect fall through wireless devices and connect to cloud servers. Also, this data will then be merged with the patient’s historical medical data and analyzed using machine learning techniques for disease prediction at an early stage. It helps the family members and health workers to monitor and manage the health parameters of patients in an efficient way.","PeriodicalId":191794,"journal":{"name":"2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 Advanced Computing and Communication Technologies for High Performance Applications (ACCTHPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACCTHPA49271.2020.9213239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
The proposal comprises using cutting edge technology of Internet of Things (IoT), Cloud and AI-based analytics to monitor and provide timely and proactive alerts to not only patients but also healthcare workers such as doctors, nursing homes and even remotely located family members about patient’s critical health parameters. The measured raw data will record live location and calculate heart rate, pulse, temperature and detect fall through wireless devices and connect to cloud servers. Also, this data will then be merged with the patient’s historical medical data and analyzed using machine learning techniques for disease prediction at an early stage. It helps the family members and health workers to monitor and manage the health parameters of patients in an efficient way.
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