{"title":"迈向健康评估的物联网框架","authors":"Katherine McLeod, P. Spachos","doi":"10.1109/CAMAD55695.2022.9966893","DOIUrl":null,"url":null,"abstract":"Wellness assessment can provide important data to improve the health of an individual. However, constantly monitoring individual wellness has challenges due to the different and several activities people participate in throughout the day. The availability and popularity of low-cost and inexpensive Internet of Things (IoT) devices can alleviate this issue. In this work, an IoT framework is presented to examine the relationship between an individual's wellness and their surrounding environment. It uses an IoT device to collect data and forwards them using WiFi and Bluetooth Low Energy (BLE). The participants in this study are two groups of ten undergraduate students at the University of Guelph. Each group took the experiment at different times of the year. Each participant is given an Android smartphone equipped with an application, in order to complete a brief psychological survey three times per day. During the periods of completion, an IoT device in their possession is reading environmental data. The five environmental variables collected are temperature, humidity, air pressure, luminosity, and noise level. Upon submission of the survey, the results of the survey and the environmental data are sent to a server via WiFi. According to experimental results, the first group to complete the experiment indicated a correlation between stress and noise, while the second group indicated a correlation between distress and light.","PeriodicalId":166029,"journal":{"name":"2022 IEEE 27th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Towards an IoT Framework for Wellness Assessment\",\"authors\":\"Katherine McLeod, P. Spachos\",\"doi\":\"10.1109/CAMAD55695.2022.9966893\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Wellness assessment can provide important data to improve the health of an individual. However, constantly monitoring individual wellness has challenges due to the different and several activities people participate in throughout the day. The availability and popularity of low-cost and inexpensive Internet of Things (IoT) devices can alleviate this issue. In this work, an IoT framework is presented to examine the relationship between an individual's wellness and their surrounding environment. It uses an IoT device to collect data and forwards them using WiFi and Bluetooth Low Energy (BLE). The participants in this study are two groups of ten undergraduate students at the University of Guelph. Each group took the experiment at different times of the year. Each participant is given an Android smartphone equipped with an application, in order to complete a brief psychological survey three times per day. During the periods of completion, an IoT device in their possession is reading environmental data. The five environmental variables collected are temperature, humidity, air pressure, luminosity, and noise level. Upon submission of the survey, the results of the survey and the environmental data are sent to a server via WiFi. According to experimental results, the first group to complete the experiment indicated a correlation between stress and noise, while the second group indicated a correlation between distress and light.\",\"PeriodicalId\":166029,\"journal\":{\"name\":\"2022 IEEE 27th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)\",\"volume\":\"5 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 27th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CAMAD55695.2022.9966893\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 27th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAMAD55695.2022.9966893","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wellness assessment can provide important data to improve the health of an individual. However, constantly monitoring individual wellness has challenges due to the different and several activities people participate in throughout the day. The availability and popularity of low-cost and inexpensive Internet of Things (IoT) devices can alleviate this issue. In this work, an IoT framework is presented to examine the relationship between an individual's wellness and their surrounding environment. It uses an IoT device to collect data and forwards them using WiFi and Bluetooth Low Energy (BLE). The participants in this study are two groups of ten undergraduate students at the University of Guelph. Each group took the experiment at different times of the year. Each participant is given an Android smartphone equipped with an application, in order to complete a brief psychological survey three times per day. During the periods of completion, an IoT device in their possession is reading environmental data. The five environmental variables collected are temperature, humidity, air pressure, luminosity, and noise level. Upon submission of the survey, the results of the survey and the environmental data are sent to a server via WiFi. According to experimental results, the first group to complete the experiment indicated a correlation between stress and noise, while the second group indicated a correlation between distress and light.