The sharp rise in popularity of micro-mobility poses significant challenges in terms of
ensuring its safety, addressing its social impacts, mitigating its environmental effects, and …

The performance of fingerprint-based indoor wireless localization systems (IWL-Ss) can be
enhanced using fingerprint clustering. The localization performance of clustered fingerprint …

Fingerprint database clustering is one of the methods used to reduce localization time and
improve localization accuracy in a fingerprint-based localization system. However, optimal …

This paper provides an analysis of two machine learning algorithms, density-based spatial
clustering of applications with noise (DBSCAN) and the local outlier factor (LOF), applied in …

The proliferation of smartphones has accelerated mobility studies by largely increasing the
type and volume of mobility data available. One such source of mobility data is from GPS …

The demand for indoor localization is increasing with ubiquitous computing and the Internet
of Things (IoT) emergence. Location awareness is crucial to intelligent systems in large …

With the rapid development and widespread adoption of wearable technology, a new type of
lifelog data is being collected and used in numerous studies. We refer to these data as …

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 …