Abstract
Future communications technologies will radically transform the way we communicate, by introducing a vast array of capabilities and services. In current 5G networks, key elements such as increased bandwidth, smaller cells, high density, multiple radio access technologies and device-to-device (D2D) communication can offer great benefit in localization services. Telecom operators and ICT companies have accepted the challenge to develop and integrate mobile localization technologies, powered by AI algorithms and machine-learning techniques, which will exploit the location information while, at the same time, preserve end-users’ privacy. The use of these technologies will enhance location-based communication and network management techniques as well as mobility and radio resource management. In this paper, we present the ambition coming from the framework of the LOCUS EU-funded project [1]. LOCUS aims to design and implement an innovative location management layered platform which will be able to improve localization accuracy, taking into consideration localization security and privacy concerns, to extend localization with physical analytics and finally to extract value out from the combined interaction of localization and analytics, while guaranteeing users’ privacy.
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Acknowledgments
This paper has been based on the context of the LOCUS (“LOCalization and analytics on-demand embedded in the 5G ecosystem, for Ubiquitous vertical applicationS”) Project, and has been supported by the Commission of the European Communities / H2020, Grant Agreement No.871249.
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Belesioti, M., Tsagkaris, K., Margaris, A., Chochliouros, I.P. (2022). A 5G-Based Architecture for Localization Accuracy. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds) Artificial Intelligence Applications and Innovations. AIAI 2022 IFIP WG 12.5 International Workshops. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 652. Springer, Cham. https://doi.org/10.1007/978-3-031-08341-9_2
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