{"title":"Advanced EHR system in homes-in-schools’ automation using internet of things and machine learning","authors":"N. Duodu, Warish D. Patel","doi":"10.1080/02522667.2022.2094079","DOIUrl":null,"url":null,"abstract":"Abstract Electronic Health Records (EHRs) are the health data collected and stored electronically for informative purposes in today’s healthcare to handle healthcare in patients’ hands, thereby reducing physical contact between healthcare seekers and providers. This paper reviews a complete health monitoring and health status reporting system using IoT technology to gather vital health statistics and machine learning to design an intelligent system. The proposed system will adopt IoT technology to collect health information from students in their residence and use a machine learning method to predict students’ health status from the institution’s Electronic Health Records before rendering health counselling services to students. It will also allow students to report health conditions to educational authorities on a complex Wireless Body Area Network to deploy Raspberry Pi 4B, sensors, cameras.","PeriodicalId":46518,"journal":{"name":"JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2022-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/02522667.2022.2094079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract Electronic Health Records (EHRs) are the health data collected and stored electronically for informative purposes in today’s healthcare to handle healthcare in patients’ hands, thereby reducing physical contact between healthcare seekers and providers. This paper reviews a complete health monitoring and health status reporting system using IoT technology to gather vital health statistics and machine learning to design an intelligent system. The proposed system will adopt IoT technology to collect health information from students in their residence and use a machine learning method to predict students’ health status from the institution’s Electronic Health Records before rendering health counselling services to students. It will also allow students to report health conditions to educational authorities on a complex Wireless Body Area Network to deploy Raspberry Pi 4B, sensors, cameras.