TY - DATA
T1 - Data underlying the publication: A zone-based Wi-Fi fingerprinting indoor positioning system for factory noise mapping
PY - 2025/05/16
AU - Leicai Xiao
AU - Poorya Ghafoorpoor Yazdi
AU - Sebastian Thiede
UR - 
DO - 10.4121/fcdca0e0-8e96-410d-9601-3d7883827047.v2
KW - Wi-Fi fingerprint
KW - factory, noise map
KW - Machine Learning
KW - Indoor positioning system (IPS).
N2 - <p><strong># Dataset and scripts: A zone-based Wi-Fi fingerprinting indoor positioning system for factory noise mapping</strong></p><p><br></p><p><strong>## Overview</strong></p><p>This dataset supports research on zone-based Wi-Fi fingerprinting indoor positioning systems and factory noise mapping. It includes Wi-Fi RSSI (Received Signal Strength Indicator) data, noise levels, zone information, and timestamps, which can be used to develop models for indoor positioning, zone classification, and noise mapping within factory environments.</p><p><br></p><p><strong>## Dataset</strong></p><p>1. RSSI_rawdata_4days_sample200_37zone.csv</p><p>Raw RSSI measurements collected across 37 zones over four days. Each row contains RSSI values from six access points (AP1-AP6) and the corresponding zone label.</p><p><br></p><p>Columns:</p><p><br></p><p>AP1-AP6: RSSI values (in dBm) for six Wi-Fi access points.</p><p>label: Zone ID (integer) where the data was collected.</p><p>Purpose:</p><p>Used for training and evaluating machine learning models for indoor positioning and zone classification.</p><p><br></p><p>2. RSSI_fluctuate_6AP_Sample400.csv</p><p>Wi-Fi RSSI fluctuations collected from six access points (AP1-AP6) at the same location, with 400 samples to analyze signal stability.</p><p><br></p><p>Columns:</p><p><br></p><p>AP1-AP6: RSSI values (in dBm) for six access points.</p><p>Purpose:</p><p>Analyzed for signal stability and noise mapping, supporting indoor positioning and signal fluctuation evaluation in factory environments.</p><p><br></p><p><strong>## Scripts</strong></p><p>1. model.py</p><p>Processes the RSSI_rawdata_4days_sample200_37zone.csv file and evaluates machine learning model performance for indoor positioning and zone classification.</p><p>This script evaluates machine learning model performance as discussed in<em> Section 4.3</em> ("ML Model Performance Evaluation"). </p><p><br></p><p>2. logic.py</p><p>Processes the RSSI_fluctuate_6AP_Sample400.csv file to evaluate Wi-Fi signal fluctuations, supporting signal stability analysis for noise mapping and positioning.</p><p>This script analyzes Wi-Fi signal fluctuations as discussed in <em>Section 4.2</em> ("Wi-Fi Signal Analysis") of the paper.</p><p><br></p><p><strong>## Citation</strong></p><p>If you use this dataset, please cite:</p><p>"A zone-based Wi-Fi fingerprinting indoor positioning system for factory noise mapping," Journal of Intelligent Manufacturing, 2025.</p><p><br></p><p><strong>## License</strong></p><p>This project is licensed under the MIT License. See the LICENSE file for details.</p><p><br></p>
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