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issai/IMUWiFine

IMUWiFine: End-to-End Sequential Indoor Localization Paper: End-to-End Sequential Indoor Localization Using Smartphone Inertial Sensors and WiFi GitHub: https://github.com/IS2AI/IMUWiFine Description: The IMUWiFine dataset comprises IMU and WiFi RSSI data readings recorded in sequential order with a fine spatiotemporal resolution. The dataset was collected on the fourth, fifth, and sixth floors of the C4 building at the Nazarbayev University campus. The total covered area is… See the full description on the dataset page: https://huggingface.co/datasets/issai/IMUWiFine.

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IMUWiFine: End-to-End Sequential Indoor Localization

Paper: End-to-End Sequential Indoor Localization Using Smartphone Inertial Sensors and WiFi

GitHub: https://github.com/IS2AI/IMUWiFine

Description: The IMUWiFine dataset comprises IMU and WiFi RSSI data readings recorded in sequential order with a fine spatiotemporal resolution. The dataset was collected on the fourth, fifth, and sixth floors of the C4 building at the Nazarbayev University campus. The total covered area is over 9, 000 m2 throughout the three floors.

SpecificationsTrainValidTestTotal
Number of trajectories603030120
Number of samples3.1M1.2M1.1M5.4M
Total length (km)8.03.13.014.2
Total duration (hours)5.52.52.410.4

Citation:

bibtex
@INPROCEEDINGS{9708854,
  author={Nurpeiissov, Mukhamet and Kuzdeuov, Askat and Assylkhanov, Aslan and Khassanov, Yerbolat and Varol, Huseyin Atakan},
  booktitle={2022 IEEE/SICE International Symposium on System Integration (SII)}, 
  title={End-to-End Sequential Indoor Localization Using Smartphone Inertial Sensors and WiFi}, 
  year={2022},
  pages={566-571},
  doi={10.1109/SII52469.2022.9708854}}