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2021 | OriginalPaper | Chapter

Indoor Location Estimation Based on Diffused Beacon Network

Authors : André Mendes, Miguel Diaz-Cacho

Published in: Optimization, Learning Algorithms and Applications

Publisher: Springer International Publishing

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Abstract

This work investigates the problem of location estimation in indoor Wireless Sensor Networks (WSN) where precise, discrete and low-cost independent self-location is a critical requirement. The indoor scenario makes explicit measurements based on specialised location hardware, such as the Global Navigation Satellite System (GNSS), difficult and not practical, because RF signals are subjected to many propagation issues (reflections, absorption, etc.). In this paper, we propose a low-cost effective WSN location solution. Its design uses received signal strength for ranging, lightweight distributed algorithms for location computation, and the collaborative approach to delivering accurate location estimations with a low number of nodes in predefined locations. Through real experiments, our proposal was evaluated and its performance compared with other related mechanisms from literature, which shows its suitability and its lower average location error almost of the time.

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Metadata
Title
Indoor Location Estimation Based on Diffused Beacon Network
Authors
André Mendes
Miguel Diaz-Cacho
Copyright Year
2021
Book
Optimization, Learning Algorithms and Applications

Print ISBN: 978-3-030-91884-2

Electronic ISBN: 978-3-030-91885-9

Copyright Year: 2021

DOI
https://doi.org/10.1007/978-3-030-91885-9_21

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