{"title":"利用测量路径损耗指数和加权质心定位方法测试低功耗蓝牙室内定位技术","authors":"B. Hantono, Albert Suryanto, Norman Prastianto","doi":"10.1109/ICITEE56407.2022.9954072","DOIUrl":null,"url":null,"abstract":"Positioning technology as part of the Internet-of-things (IoT) ensures communication between devices while sharing each other’s positions. GPS is the most used positioning technology but has terrible accuracy in indoor environments. Therefore, Bluetooth Low Energy (BLE) rose to become GPS’s popular substitute in indoor locations that we will study in this research. We will utilize BLE beacons as transmitters of BLE signals and smartphones as receivers of BLE signals. The test will then produce RSSI data (signal strength) that can be converted to distance using various methods. The method always contains a constant called path loss exponent (n). We will look for the best n through several tests. Evidently, through the study, we learn BLE has good accuracy in an indoor location to replace GPS. Moreover, this research will determine the accuracy of manually generated n, the BLE beacon’s effective distance, and the Kalman Filter’s side effects as data filtration.","PeriodicalId":246279,"journal":{"name":"2022 14th International Conference on Information Technology and Electrical Engineering (ICITEE)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Testing Bluetooth Low Energy as Indoor Positioning Technology Using Measured Path Loss Exponent and Weighted Centroid Localization Methods\",\"authors\":\"B. Hantono, Albert Suryanto, Norman Prastianto\",\"doi\":\"10.1109/ICITEE56407.2022.9954072\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Positioning technology as part of the Internet-of-things (IoT) ensures communication between devices while sharing each other’s positions. GPS is the most used positioning technology but has terrible accuracy in indoor environments. Therefore, Bluetooth Low Energy (BLE) rose to become GPS’s popular substitute in indoor locations that we will study in this research. We will utilize BLE beacons as transmitters of BLE signals and smartphones as receivers of BLE signals. The test will then produce RSSI data (signal strength) that can be converted to distance using various methods. The method always contains a constant called path loss exponent (n). We will look for the best n through several tests. Evidently, through the study, we learn BLE has good accuracy in an indoor location to replace GPS. Moreover, this research will determine the accuracy of manually generated n, the BLE beacon’s effective distance, and the Kalman Filter’s side effects as data filtration.\",\"PeriodicalId\":246279,\"journal\":{\"name\":\"2022 14th International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 14th International Conference on Information Technology and Electrical Engineering (ICITEE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICITEE56407.2022.9954072\",\"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 14th International Conference on Information Technology and Electrical Engineering (ICITEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICITEE56407.2022.9954072","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Testing Bluetooth Low Energy as Indoor Positioning Technology Using Measured Path Loss Exponent and Weighted Centroid Localization Methods
Positioning technology as part of the Internet-of-things (IoT) ensures communication between devices while sharing each other’s positions. GPS is the most used positioning technology but has terrible accuracy in indoor environments. Therefore, Bluetooth Low Energy (BLE) rose to become GPS’s popular substitute in indoor locations that we will study in this research. We will utilize BLE beacons as transmitters of BLE signals and smartphones as receivers of BLE signals. The test will then produce RSSI data (signal strength) that can be converted to distance using various methods. The method always contains a constant called path loss exponent (n). We will look for the best n through several tests. Evidently, through the study, we learn BLE has good accuracy in an indoor location to replace GPS. Moreover, this research will determine the accuracy of manually generated n, the BLE beacon’s effective distance, and the Kalman Filter’s side effects as data filtration.