TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Intelligent LoRa-Based Positioning System |
| 영문제목(English Title) |
Intelligent LoRa-Based Positioning System |
| 저자(Author) |
Jiann-Liang Chen
Hsin-Yun Chen
Yi-Wei Ma
|
| 원문수록처(Citation) |
VOL 16 NO. 09 PP. 2961 ~ 2975 (2022. 09) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
The Location-Based Service (LBS) is one of the most well-known services on the Internet. Positioning is the primary association with LBS services. This study proposes an intelligent LoRa-based positioning system, called AI@LBS, to provide accurate location data. The fingerprint mechanism with the clustering algorithm in unsupervised learning filters out signal noise and improves computing stability and accuracy. In this study, data noise is filtered using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm, increasing the positioning accuracy from 95.37% to 97.38%. The problem of data imbalance is addressed using the SMOTE (Synthetic Minority Over-sampling Technique) technique, increasing the positioning accuracy from 97.38% to 99.17%. A field test in the NTUST campus (www.ntust.edu.tw) revealed that AI@LBS system can reduce average distance error to 0.48m. |
| 키워드(Keyword) |
Location-Based Service
LoRa
Fingerprint Mechanism
Machine Learning Algorithm
Synthetic Minority Over-sampling Technique (SMOTE)
DBSCAB
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| 파일첨부 |
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