Internet of things-based robust semi-analytical over ubiquitous data for indoor positioning geomagnetic
In the era of the Internet of Things (IoT), there is an increasingly urgent demand for high-precision and ubiquitous indoor positioning. However, robust technical solutions have yet to emerge, with one challenge being the effective use of geomagnetic information to address indoor personnel orientati...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Elsevier
2024-06-01
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| Series: | Measurement: Sensors |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2665917424000837 |
| _version_ | 1827221818932461568 |
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| author | Mohammad Shabaz Mukesh Soni |
| author_facet | Mohammad Shabaz Mukesh Soni |
| author_sort | Mohammad Shabaz |
| collection | DOAJ |
| description | In the era of the Internet of Things (IoT), there is an increasingly urgent demand for high-precision and ubiquitous indoor positioning. However, robust technical solutions have yet to emerge, with one challenge being the effective use of geomagnetic information to address indoor personnel orientation. As known, outdoor environments with open spaces can utilize geomagnetic resolution-based methods for orientation, but indoor environments often suffer from significant magnetic distortions, rendering such methods impractical. To address this issue, this paper proposes a semi-analytical orientation method. The method initially integrates the analytical orientation results with the geometric relationship of corridor structures extracted based on spatial context information, obtaining corrected orientation results. This is achieved by measuring magnetic distortions and determining the fusion coefficient. Furthermore, the paper thoroughly analyzes the impact of different fusion coefficients on the orientation results. Test results indicate that compared to existing methods, the proposed approach exhibits better robustness, effectively improving orientation accuracy, and is widely applicable to path-based or corridor-based positioning and orientation scenarios. |
| first_indexed | 2024-04-24T20:03:01Z |
| format | Article |
| id | doaj.art-f3198a268a154aa693488743206c4d18 |
| institution | Directory Open Access Journal |
| issn | 2665-9174 |
| language | English |
| last_indexed | 2025-03-21T16:28:39Z |
| publishDate | 2024-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Measurement: Sensors |
| spelling | doaj.art-f3198a268a154aa693488743206c4d182024-06-17T05:57:02ZengElsevierMeasurement: Sensors2665-91742024-06-0133101107Internet of things-based robust semi-analytical over ubiquitous data for indoor positioning geomagneticMohammad Shabaz0Mukesh Soni1Model Institute of Engineering and Technology, Jammu, J&K, India; Corresponding author.Dr. D. Y. Patil Vidyapeeth, Pune, Dr. D. Y. Patil School of Science & Technology, Tathawade, Pune, India; Department of CSE, University Centre for Research & Development, Chandigarh University, Mohali, Punjab, 140413, IndiaIn the era of the Internet of Things (IoT), there is an increasingly urgent demand for high-precision and ubiquitous indoor positioning. However, robust technical solutions have yet to emerge, with one challenge being the effective use of geomagnetic information to address indoor personnel orientation. As known, outdoor environments with open spaces can utilize geomagnetic resolution-based methods for orientation, but indoor environments often suffer from significant magnetic distortions, rendering such methods impractical. To address this issue, this paper proposes a semi-analytical orientation method. The method initially integrates the analytical orientation results with the geometric relationship of corridor structures extracted based on spatial context information, obtaining corrected orientation results. This is achieved by measuring magnetic distortions and determining the fusion coefficient. Furthermore, the paper thoroughly analyzes the impact of different fusion coefficients on the orientation results. Test results indicate that compared to existing methods, the proposed approach exhibits better robustness, effectively improving orientation accuracy, and is widely applicable to path-based or corridor-based positioning and orientation scenarios.http://www.sciencedirect.com/science/article/pii/S2665917424000837Ubiquitous dataIndoor positioningIoTGeomagnetic orientationOrientation method |
| spellingShingle | Mohammad Shabaz Mukesh Soni Internet of things-based robust semi-analytical over ubiquitous data for indoor positioning geomagnetic Measurement: Sensors Ubiquitous data Indoor positioning IoT Geomagnetic orientation Orientation method |
| title | Internet of things-based robust semi-analytical over ubiquitous data for indoor positioning geomagnetic |
| title_full | Internet of things-based robust semi-analytical over ubiquitous data for indoor positioning geomagnetic |
| title_fullStr | Internet of things-based robust semi-analytical over ubiquitous data for indoor positioning geomagnetic |
| title_full_unstemmed | Internet of things-based robust semi-analytical over ubiquitous data for indoor positioning geomagnetic |
| title_short | Internet of things-based robust semi-analytical over ubiquitous data for indoor positioning geomagnetic |
| title_sort | internet of things based robust semi analytical over ubiquitous data for indoor positioning geomagnetic |
| topic | Ubiquitous data Indoor positioning IoT Geomagnetic orientation Orientation method |
| url | http://www.sciencedirect.com/science/article/pii/S2665917424000837 |
| work_keys_str_mv | AT mohammadshabaz internetofthingsbasedrobustsemianalyticaloverubiquitousdataforindoorpositioninggeomagnetic AT mukeshsoni internetofthingsbasedrobustsemianalyticaloverubiquitousdataforindoorpositioninggeomagnetic |