In this chapter we discuss some basic approaches for indoor positioning system definition and, in particular, those based on the electromagnetic properties of the received signal, the so-called geometric radiolocation techniques. A brief reference to the localization history, actors, and architectures, along of a taxonomy of the different concepts of localization, introduces the chapter, before presenting a detailed discussion of the most common techniques. The chapter also evidences the issues associated to the indoor propagation environment, in order to understand the efforts made by the scientific community on mitigating the artifacts of indoor localization systems. To complete this discussion, we analyze the role that machine learning and artificial intelligence play in the indoor positioning problem solution.

Geometric Indoor Radiolocation: History, Trends and Open Issues / Florio, Antonello; Avitabile, Gianfranco; Coviello, Giuseppe - In: Machine Learning for Indoor Localization and Navigation[s.l] : Springer International Publishing, 2023. - ISBN 9783031267116. - pp. 49-69 [10.1007/978-3-031-26712-3_3]

Geometric Indoor Radiolocation: History, Trends and Open Issues

Florio, Antonello;Avitabile, Gianfranco;Coviello, Giuseppe
2023

Abstract

In this chapter we discuss some basic approaches for indoor positioning system definition and, in particular, those based on the electromagnetic properties of the received signal, the so-called geometric radiolocation techniques. A brief reference to the localization history, actors, and architectures, along of a taxonomy of the different concepts of localization, introduces the chapter, before presenting a detailed discussion of the most common techniques. The chapter also evidences the issues associated to the indoor propagation environment, in order to understand the efforts made by the scientific community on mitigating the artifacts of indoor localization systems. To complete this discussion, we analyze the role that machine learning and artificial intelligence play in the indoor positioning problem solution.
2023
Machine Learning for Indoor Localization and Navigation
9783031267116
9783031267123
Springer International Publishing
Geometric Indoor Radiolocation: History, Trends and Open Issues / Florio, Antonello; Avitabile, Gianfranco; Coviello, Giuseppe - In: Machine Learning for Indoor Localization and Navigation[s.l] : Springer International Publishing, 2023. - ISBN 9783031267116. - pp. 49-69 [10.1007/978-3-031-26712-3_3]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/288992
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