An Inductive System Monitoring Approach for GNSS Activation
2022 (English)In: IFIP Advances in Information and Communication Technology / [ed] Maglogiannis, I, Iliadis, L, Macintyre, J, Cortez, P, Springer Science+Business Media B.V., 2022, Vol. 647, p. 437-449Conference paper, Published paper (Refereed)
Abstract [en]
In this paper, we propose a Global Navigation Satellite System (GNSS) component activation model for mobile tracking devices that automatically detects indoor/outdoor environments using the radio signals received from Long-Term Evolution (LTE) base stations. We use an Inductive System Monitoring (ISM) technique to model environmental scenarios captured by a smart tracker via extracting clusters of corresponding value ranges from LTE base stations’ signal strength. The ISM-based model is built by using the tracker’s historical data labeled with GPS coordinates. The built model is further refined by applying it to additional data without GPS location collected by the same device. This procedure allows us to identify the clusters that describe semi-outdoor scenarios. In that way, the model discriminates between two outdoor environmental categories: open outdoor and semi-outdoor. The proposed ISM-based GNSS activation approach is studied and evaluated on a real-world dataset contains radio signal measurements collected by five smart trackers and their geographical location in various environmental scenarios.
Place, publisher, year, edition, pages
Springer Science+Business Media B.V., 2022. Vol. 647, p. 437-449
Series
IFIP Advances in Information and Communication Technology, ISSN 1868-4238, E-ISSN 1868422X ; 647
Keywords [en]
Activation analysis, Chemical activation, Global positioning system, Long Term Evolution (LTE), Monitoring, Radio navigation, Clustering analysis, Context detection, Environmental context detection, Environmental contexts, Global navigation satellite system signal, Global Navigation Satellite Systems, Inductive system, Inductive system monitoring, System monitoring, System signals, Base stations, GNSS signal
National Category
Other Computer and Information Science
Identifiers
URN: urn:nbn:se:bth-23550DOI: 10.1007/978-3-031-08337-2_36ISI: 000927893200036Scopus ID: 2-s2.0-85133294290ISBN: 9783031083365 (print)OAI: oai:DiVA.org:bth-23550DiVA, id: diva2:1687365
Conference
18th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations, AIAI 2022, Hersonissos, 17 June 2022 - 20 June 2022
2022-08-152022-08-152023-03-09Bibliographically approved