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| Format: | Recurso digital |
| Language: | English |
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2021
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| Online Access: | https://doi.org/10.5281/zenodo.5457591 |
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| _version_ | 1866902281418440704 |
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| author | Kolakowski, Marcin |
| author_facet | Kolakowski, Marcin |
| contents | <p>The dataset contains Bluetooth Low Energy signal strengths measured in a fully furnished flat. The dataset was originally used in the study concerning RSS-fingerprinting based indoor positioning systems. The data were gathered using a hybrid BLE-UWB localization system, which was installed in the apartment and a mobile robotic platform equipped for a LiDAR. The dataset comprises power measurement results and LiDAR scans performed in 4104 points. The scans used for initial environment mapping and power levels registered in two test scenarios are also attached.</p> <p>The set contains both raw and preprocessed measurement data. The Python code for raw data loading is supplied.</p> <p>The detailed dataset description can be found in the <em>dataset_description.pdf</em> file.</p> <p>When using the dataset, please consider citing the original paper, in which the data were used:</p> <p>M. Kolakowski,<strong> “Automated Calibration of RSS Fingerprinting Based Systems Using a Mobile Robot and Machine Learning”</strong>, <em>Sensors</em> , vol. <em>21</em>, 6270, Sep. 2021 <a href="https://doi.org/10.3390/s21186270">https://doi.org/10.3390/s21186270</a></p> <p> </p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_5457591 |
| institution | Zenodo |
| language | eng |
| publishDate | 2021 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | BLE RSS dataset for fingerprinting radio map calibration Kolakowski, Marcin positioning machine learning Bluetooth Low Energy SLAM <p>The dataset contains Bluetooth Low Energy signal strengths measured in a fully furnished flat. The dataset was originally used in the study concerning RSS-fingerprinting based indoor positioning systems. The data were gathered using a hybrid BLE-UWB localization system, which was installed in the apartment and a mobile robotic platform equipped for a LiDAR. The dataset comprises power measurement results and LiDAR scans performed in 4104 points. The scans used for initial environment mapping and power levels registered in two test scenarios are also attached.</p> <p>The set contains both raw and preprocessed measurement data. The Python code for raw data loading is supplied.</p> <p>The detailed dataset description can be found in the <em>dataset_description.pdf</em> file.</p> <p>When using the dataset, please consider citing the original paper, in which the data were used:</p> <p>M. Kolakowski,<strong> “Automated Calibration of RSS Fingerprinting Based Systems Using a Mobile Robot and Machine Learning”</strong>, <em>Sensors</em> , vol. <em>21</em>, 6270, Sep. 2021 <a href="https://doi.org/10.3390/s21186270">https://doi.org/10.3390/s21186270</a></p> <p> </p> |
| title | BLE RSS dataset for fingerprinting radio map calibration |
| topic | positioning machine learning Bluetooth Low Energy SLAM |
| url | https://doi.org/10.5281/zenodo.5457591 |