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Author/Affiliation: Kazuhiro KondoOpen AccessArticle
10 Pages, 2,406 KB 
Indoor Position and Movement Direction Estimation System Using DNN on BLE Beacon RSSI Fingerprints
Abstract:
In this paper, we propose a highly accurate indoor position and direction estimation system using a simple fully connected deep neural network (DNN) model on Bluetooth Low Energy (BLE) Received Signal Strength Indicators (RSSIs). Since the system’s ultimate goal is to function as an indoor navigation system, the system estimates the indoor position simultaneously as…
Read More(This article belongs to the Special Issue on Innovation in Computing, Engineering Science & Technology 2022 & Section Hardware & Architecture in Computer Science (CHA))