Decentralized Collaborative Inertial Tracking
Détails
ID Serval
serval:BIB_613B3650219A
Type
Partie de livre
Sous-type
Chapitre: chapitre ou section
Collection
Publications
Institution
Titre
Decentralized Collaborative Inertial Tracking
Titre du livre
Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
Editeur
Springer Nature Switzerland
ISBN
9783031639883
9783031639890
9783031639890
ISSN
1867-8211
1867-822X
1867-822X
Statut éditorial
Publié
Date de publication
2024
Pages
26-45
Langue
anglais
Résumé
Although people spend most of their time indoors, outdoor tracking systems, such as the Global Positioning System (GPS), are predominantly used for location-based services. These systems are accurate outdoors, easy to use, and operate autonomously on each mobile device. In contrast, Indoor Tracking Systems (ITS) lack standardization and are often difficult to operate because they require costly infrastructure. In this paper, we propose an indoor tracking algorithm that uses collected data from inertial sensors embedded in most mobile devices. In this setting, mobile devices autonomously estimate their location, hence removing the burden of deploying and maintaining complex and scattered hardware infrastructure. In addition, these devices collaborate by anonymously exchanging data with other nearby devices, using wireless communication, such as Bluetooth, to correct errors in their location estimates. Our collaborative algorithm relies on low-complexity geometry operations and can be deployed on any recent mobile device with commercial-grade sensors. We evaluate our solution on real-life data collected by different devices. Experimentation with 16 simultaneously moving and collaborating devices shows an average accuracy improvement of 44% compared to the standalone Pedestrian Dead Reckoning algorithm.
Création de la notice
22/07/2024 22:20
Dernière modification de la notice
23/07/2024 6:56