Room-Level Localization System Based on LoRa Backscatters
The aim of this paper is to propose a novel room-level localization approach to locate LoRa backscatter devices, which can be easily embedded into wearable devices or smartphones. The advantages of this system lie in its series of low-cost, low-power, low-complexity and long-range features. LoRa bac...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2021-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9328764/ |
| _version_ | 1819276893069770752 |
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| author | Antonio Lazaro Marc Lazaro Ramon Villarino |
| author_facet | Antonio Lazaro Marc Lazaro Ramon Villarino |
| author_sort | Antonio Lazaro |
| collection | DOAJ |
| description | The aim of this paper is to propose a novel room-level localization approach to locate LoRa backscatter devices, which can be easily embedded into wearable devices or smartphones. The advantages of this system lie in its series of low-cost, low-power, low-complexity and long-range features. LoRa backscattering operates by alternatively connecting an antenna, through a switch, to two loads with high reflection coefficients and opposite phase. The result is a frequency shift of the LoRa incident signal equal to the backscatter switching frequency. The localization system comprises several LoRa receivers distributed among the rooms, a LoRa transmitter located at a central point and the backscatter device, which is carried or worn by a subject. The position of the LoRa backscatter device can be determined by comparing the received signal strength between all receivers. In order to improve the accuracy of the system, different machine learning classifiers were compared. System performance was tested in a real-life scenario, achieving an accuracy up to 89.7% using linear discriminant analysis (LDA). |
| first_indexed | 2024-12-23T23:47:27Z |
| format | Article |
| id | doaj.art-860fe5c6eede4267abcea93dfa74855e |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-23T23:47:27Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-860fe5c6eede4267abcea93dfa74855e2022-12-21T17:25:29ZengIEEEIEEE Access2169-35362021-01-019160041601810.1109/ACCESS.2021.30531449328764Room-Level Localization System Based on LoRa BackscattersAntonio Lazaro0https://orcid.org/0000-0003-3160-5777Marc Lazaro1https://orcid.org/0000-0002-8930-1170Ramon Villarino2https://orcid.org/0000-0001-9692-8943Department of Electronic, Electric, and Automatic Engineering, Rovira i Virgili University, Tarragona, SpainDepartment of Electronic, Electric, and Automatic Engineering, Rovira i Virgili University, Tarragona, SpainDepartment of Electronic, Electric, and Automatic Engineering, Rovira i Virgili University, Tarragona, SpainThe aim of this paper is to propose a novel room-level localization approach to locate LoRa backscatter devices, which can be easily embedded into wearable devices or smartphones. The advantages of this system lie in its series of low-cost, low-power, low-complexity and long-range features. LoRa backscattering operates by alternatively connecting an antenna, through a switch, to two loads with high reflection coefficients and opposite phase. The result is a frequency shift of the LoRa incident signal equal to the backscatter switching frequency. The localization system comprises several LoRa receivers distributed among the rooms, a LoRa transmitter located at a central point and the backscatter device, which is carried or worn by a subject. The position of the LoRa backscatter device can be determined by comparing the received signal strength between all receivers. In order to improve the accuracy of the system, different machine learning classifiers were compared. System performance was tested in a real-life scenario, achieving an accuracy up to 89.7% using linear discriminant analysis (LDA).https://ieeexplore.ieee.org/document/9328764/Backscatter communicationsLoRalocalizationwireless sensor networksRFIDzero-power sensor |
| spellingShingle | Antonio Lazaro Marc Lazaro Ramon Villarino Room-Level Localization System Based on LoRa Backscatters IEEE Access Backscatter communications LoRa localization wireless sensor networks RFID zero-power sensor |
| title | Room-Level Localization System Based on LoRa Backscatters |
| title_full | Room-Level Localization System Based on LoRa Backscatters |
| title_fullStr | Room-Level Localization System Based on LoRa Backscatters |
| title_full_unstemmed | Room-Level Localization System Based on LoRa Backscatters |
| title_short | Room-Level Localization System Based on LoRa Backscatters |
| title_sort | room level localization system based on lora backscatters |
| topic | Backscatter communications LoRa localization wireless sensor networks RFID zero-power sensor |
| url | https://ieeexplore.ieee.org/document/9328764/ |
| work_keys_str_mv | AT antoniolazaro roomlevellocalizationsystembasedonlorabackscatters AT marclazaro roomlevellocalizationsystembasedonlorabackscatters AT ramonvillarino roomlevellocalizationsystembasedonlorabackscatters |