Exploration of indoor environment perception and design model based on virtual reality technology
This article combines the received signal strength indication ranging technology with the particle swarm backpropagation algorithm to propose an indoor environment perception and design model based on virtual reality. The highest detection rate of 95.5% was achieved in the static state, while a dete...
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| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2025-04-01
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| Series: | Nonlinear Engineering |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/nleng-2024-0080 |
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| _version_ | 1849314973522591744 |
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| author | Zhang Mingli |
| author_facet | Zhang Mingli |
| author_sort | Zhang Mingli |
| collection | DOAJ |
| description | This article combines the received signal strength indication ranging technology with the particle swarm backpropagation algorithm to propose an indoor environment perception and design model based on virtual reality. The highest detection rate of 95.5% was achieved in the static state, while a detection rate of 90% was maintained in the dynamic state, demonstrating strong robustness. At different distances, the positioning error of the PSO-BP-Adaboost algorithm remains within 0.82 m, indicating its effectiveness and accuracy in real-time indoor positioning. (a) Error changes before applying filtering algorithms. (b) Error changes after applying filtering algorithms. |
| format | Article |
| id | doaj-art-232014a79ac84ccdae69bf601b5859b2 |
| institution | Kabale University |
| issn | 2192-8029 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Nonlinear Engineering |
| spelling | doaj-art-232014a79ac84ccdae69bf601b5859b22025-08-20T03:52:16ZengDe GruyterNonlinear Engineering2192-80292025-04-0114191010.1515/nleng-2024-0080Exploration of indoor environment perception and design model based on virtual reality technologyZhang Mingli0Art and Design Department, Zibo Vocational Institute, Zibo, 255000, ChinaThis article combines the received signal strength indication ranging technology with the particle swarm backpropagation algorithm to propose an indoor environment perception and design model based on virtual reality. The highest detection rate of 95.5% was achieved in the static state, while a detection rate of 90% was maintained in the dynamic state, demonstrating strong robustness. At different distances, the positioning error of the PSO-BP-Adaboost algorithm remains within 0.82 m, indicating its effectiveness and accuracy in real-time indoor positioning. (a) Error changes before applying filtering algorithms. (b) Error changes after applying filtering algorithms.https://doi.org/10.1515/nleng-2024-0080virtual realityindoor environmental perceptionreceiving signal strength indicationparticle swarm backpropagationpositioning accuracy |
| spellingShingle | Zhang Mingli Exploration of indoor environment perception and design model based on virtual reality technology Nonlinear Engineering virtual reality indoor environmental perception receiving signal strength indication particle swarm backpropagation positioning accuracy |
| title | Exploration of indoor environment perception and design model based on virtual reality technology |
| title_full | Exploration of indoor environment perception and design model based on virtual reality technology |
| title_fullStr | Exploration of indoor environment perception and design model based on virtual reality technology |
| title_full_unstemmed | Exploration of indoor environment perception and design model based on virtual reality technology |
| title_short | Exploration of indoor environment perception and design model based on virtual reality technology |
| title_sort | exploration of indoor environment perception and design model based on virtual reality technology |
| topic | virtual reality indoor environmental perception receiving signal strength indication particle swarm backpropagation positioning accuracy |
| url | https://doi.org/10.1515/nleng-2024-0080 |
| work_keys_str_mv | AT zhangmingli explorationofindoorenvironmentperceptionanddesignmodelbasedonvirtualrealitytechnology |