indoor positioning


Dataset used for "A Machine Learning Approach for Wi-Fi RTT Ranging" paper (ION ITM 2019). The dataset includes almost 30,000 Wi-Fi RTT (FTM) raw channel measurements from real-life client and access points, from an office environment. This data can be used for Time of Arrival (ToA), ranging, positioning, navigation and other types of research in Wi-Fi indoor location. The zip file includes a README file, a CSV file with the dataset and several Matlab functions to help the user plot the data and demonstrate how to estimate the range.

  • Artificial Intelligence
  • Last Updated On: 
    Mon, 06/08/2020 - 03:50

    This RSSI Dataset is a comprehensive set of Received Signal Strength Indicator (RSSI) readings gathered from three different types of scenarios. Three wireless technologies were used which consisted of:

    • Zigbee (IEEE 802.15.4),
    • Bluetooth Low Energy (BLE), and
    • WiFi (IEEE 802.11n 2.4GHz band).

    The scenarios took place in three rooms with different sizes and inteference levels. For the experimentation, the equipment utilized consisted of Raspberry Pi 3 Model Bs, Gimbal Series 10 Beacons, and Series 2 Xbees with Arduino Uno microcontrollers.

  • IoT
  • Last Updated On: 
    Sat, 05/02/2020 - 23:40

    This dataset includes UWB range measurements performed with Pozyx devices. The measurements were collected between two tags placed at several distances and in two different conditions: with Line of Sight (LOS) and Non-Line of Sight (NLOS). The measurements include the range estimated by the Pozyx tag, the actual distance between devices, the timestamp of each measurement and the values corresponding to the samples of the Channel Impulse Response (CIR) after each transmission.

  • Digital signal processing
  • Last Updated On: 
    Mon, 02/10/2020 - 05:36

    The Geomagnetic field can be used for classifying different landmark locations inside a big building.

  • Computational Intelligence
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34

    The file contains raw data collected from 9 pedestrians. Three of them walked in Track 1, another three walked in Track 2 and the last three walked in Track 3. All the pedestrians ended their walks at the starting point. Track 1 and Track 3 cover a distance of 150.3m. While, the Track covers a distance of 111.4m.

  • Wearable Sensing
  • Last Updated On: 
    Thu, 11/08/2018 - 10:34