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Erschienen in:
Dynamic Response Surface Method Combined with Genetic Algorithm to Optimize Extraction Process Problem Kapitel lesen Erstes Kapitel lesen

2021 | OriginalPaper | Buchkapitel

Indoor Location Estimation Based on Diffused Beacon Network

verfasst von : André Mendes, Miguel Diaz-Cacho

Erschienen in: Optimization, Learning Algorithms and Applications

Verlag: 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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Vorheriges Kapitel Optimizing Data Transmission in a Wireless Sensor Network Based on LoRaWAN Protocol
Nächstes Kapitel SMACovid-19 – Autonomous Monitoring System for Covid-19
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Metadaten
Titel
Indoor Location Estimation Based on Diffused Beacon Network
verfasst von
André Mendes
Miguel Diaz-Cacho
Copyright-Jahr
2021
Buch
Optimization, Learning Algorithms and Applications

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

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

Copyright-Jahr: 2021

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

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