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Research on Autonomous and Collaborative Deployment of Massive Mobile Base Stations in High-Rise Building Fire Field
High-rise building fires pose a serious threat to the lives and property safety of people. The lack of reliable and accurate positioning means is one of the main difficulties faced by rescuers. In the absence of prior knowledge of the high-rise building fire environment, the coverage deployment of m...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10534297/ https://www.ncbi.nlm.nih.gov/pubmed/37765722 http://dx.doi.org/10.3390/s23187664 |
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author | Li, Ke Huang, Chen Liang, Jiaping Zou, Yanbin Xu, Biao Yao, Yao Zhang, Yang Liu, Dandan |
author_facet | Li, Ke Huang, Chen Liang, Jiaping Zou, Yanbin Xu, Biao Yao, Yao Zhang, Yang Liu, Dandan |
author_sort | Li, Ke |
collection | PubMed |
description | High-rise building fires pose a serious threat to the lives and property safety of people. The lack of reliable and accurate positioning means is one of the main difficulties faced by rescuers. In the absence of prior knowledge of the high-rise building fire environment, the coverage deployment of mobile base stations is a challenging problem that has not received much attention in the literature. This paper studies the problem of the autonomous optimal deployment of base stations in high-rise building fire environments based on a UAV group. A novel problem formulation is proposed that solves the non-line-of-sight (NLOS) positioning problem in complex and unknown environments. The purpose of this paper is to realize the coverage and deployment of mobile base stations in complex and unknown fire environments. The NLOS positioning problem in the fire field environment is turned into the line-of-sight (LOS) positioning problem through the optimization algorithm. And there are more than three LOS base stations nearby at any point in the fire field. A control law which is formulated in a mathematically precise problem statement is developed that guarantees to meet mobile base stations’ deployment goals and to avoid collision. Finally, the positioning accuracy of our method and that of the common method were compared under many different cases. The simulation result showed that the positioning error of a simulated firefighter in the fire field environment was improved from more than 10 m (the positioning error of the traditional method) to less than 1 m. |
format | Online Article Text |
id | pubmed-10534297 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105342972023-09-29 Research on Autonomous and Collaborative Deployment of Massive Mobile Base Stations in High-Rise Building Fire Field Li, Ke Huang, Chen Liang, Jiaping Zou, Yanbin Xu, Biao Yao, Yao Zhang, Yang Liu, Dandan Sensors (Basel) Article High-rise building fires pose a serious threat to the lives and property safety of people. The lack of reliable and accurate positioning means is one of the main difficulties faced by rescuers. In the absence of prior knowledge of the high-rise building fire environment, the coverage deployment of mobile base stations is a challenging problem that has not received much attention in the literature. This paper studies the problem of the autonomous optimal deployment of base stations in high-rise building fire environments based on a UAV group. A novel problem formulation is proposed that solves the non-line-of-sight (NLOS) positioning problem in complex and unknown environments. The purpose of this paper is to realize the coverage and deployment of mobile base stations in complex and unknown fire environments. The NLOS positioning problem in the fire field environment is turned into the line-of-sight (LOS) positioning problem through the optimization algorithm. And there are more than three LOS base stations nearby at any point in the fire field. A control law which is formulated in a mathematically precise problem statement is developed that guarantees to meet mobile base stations’ deployment goals and to avoid collision. Finally, the positioning accuracy of our method and that of the common method were compared under many different cases. The simulation result showed that the positioning error of a simulated firefighter in the fire field environment was improved from more than 10 m (the positioning error of the traditional method) to less than 1 m. MDPI 2023-09-05 /pmc/articles/PMC10534297/ /pubmed/37765722 http://dx.doi.org/10.3390/s23187664 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Ke Huang, Chen Liang, Jiaping Zou, Yanbin Xu, Biao Yao, Yao Zhang, Yang Liu, Dandan Research on Autonomous and Collaborative Deployment of Massive Mobile Base Stations in High-Rise Building Fire Field |
title | Research on Autonomous and Collaborative Deployment of Massive Mobile Base Stations in High-Rise Building Fire Field |
title_full | Research on Autonomous and Collaborative Deployment of Massive Mobile Base Stations in High-Rise Building Fire Field |
title_fullStr | Research on Autonomous and Collaborative Deployment of Massive Mobile Base Stations in High-Rise Building Fire Field |
title_full_unstemmed | Research on Autonomous and Collaborative Deployment of Massive Mobile Base Stations in High-Rise Building Fire Field |
title_short | Research on Autonomous and Collaborative Deployment of Massive Mobile Base Stations in High-Rise Building Fire Field |
title_sort | research on autonomous and collaborative deployment of massive mobile base stations in high-rise building fire field |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10534297/ https://www.ncbi.nlm.nih.gov/pubmed/37765722 http://dx.doi.org/10.3390/s23187664 |
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