{"title":"An IoT-LoRa System for Tracking a Patient with a Mental Disorder: Correlation between Battery Capacity and Speed of Movement","authors":"A. Nugraha, R. Wibowo, M. Suryanegara, Nur Hayati","doi":"10.1109/ICCCE.2018.8539316","DOIUrl":null,"url":null,"abstract":"This paper investigates the performance of battery capacity in the proposed IoT-LoRa device to track and monitor a patient with a mental disorder. Reduction of battery capacity was correlated against the movement speed of users. Three experimental scenarios were conducted for a patient moving at 1–3 km/h, 5–8 km/h, and 1–30 km/h. The real time data were taken from two multinode LoRa units at 10 different locational points with a time interval of 30 minutes. The experiment had 113 data iterations to determine percentage of battery capacity and RSSI level. It was found that the faster a patient is moving, the greater the capacity of the battery reduces.","PeriodicalId":260264,"journal":{"name":"2018 7th International Conference on Computer and Communication Engineering (ICCCE)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 7th International Conference on Computer and Communication Engineering (ICCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCE.2018.8539316","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
This paper investigates the performance of battery capacity in the proposed IoT-LoRa device to track and monitor a patient with a mental disorder. Reduction of battery capacity was correlated against the movement speed of users. Three experimental scenarios were conducted for a patient moving at 1–3 km/h, 5–8 km/h, and 1–30 km/h. The real time data were taken from two multinode LoRa units at 10 different locational points with a time interval of 30 minutes. The experiment had 113 data iterations to determine percentage of battery capacity and RSSI level. It was found that the faster a patient is moving, the greater the capacity of the battery reduces.