Development of real-time monitoring BLE-LoRa positioning system based on RSSI for non-line-of-sight condition
Indoor positioning has become popular in this decade and is used to locate users or objects in indoor environments. This is because global positioning system (GPS) is not efficient for indoor use due to the multipath fading effect. This research is about development bluetooth low energy (BLE) indoor...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Institute Of Advanced Engineering And Science (IAES)
2023
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| Online Access: | http://eprints.utem.edu.my/id/eprint/28664/2/026021205202387.pdf http://eprints.utem.edu.my/id/eprint/28664/ https://ijeecs.iaescore.com/index.php/IJEECS/article/view/29297 http://doi.org/10.11591/ijeecs.v30.i2.pp972-981 |
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| Summary: | Indoor positioning has become popular in this decade and is used to locate users or objects in indoor environments. This is because global positioning system (GPS) is not efficient for indoor use due to the multipath fading effect. This research is about development bluetooth low energy (BLE) indoor
positioning system with the aid of long range (LoRa) network and guideline on selection of the BLE beacons. Next, positioning systems are developed consisting of BLE beacons, a transceiver of hybrid BLE-LoRa module, a LoRa receiver and Raspberry Pi as real-time monitoring. The received signal strength indicator (RSSI) and BLE Mac address from BLE beacons received via LoRa network are analyzed using the positioning algorithm designed in
MATLAB. The positioning algorithm incorporates distance estimation, filter implementation and trilateration technique. The estimated location is analyzed with the root mean square error (RMSE) and cumulative distribution function (CDF). According to the results, implementing the filter reduces the
positioning accuracy error, achieving 90% accuracy of positioning error less than 1.20 meters for the whole testbed. Finally, the algorithm is embedded into Raspberry Pi to view the location via desktop. |
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