indoor Localization

Visible Light Positioning is an indoor localization technology that uses wireless transmission of visible light signals to obtain a location estimate of a mobile receiver. 

This dataset can be used to validate supervised machine learning approaches in the context of Received Signal Strength Based Visible Light Positioning. 

The set is acquired in an experimental setup that consists of 4 LED transmitter beacons and a photodiode as receiving element that can move in 2D.

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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).
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5596 Views

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.

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2428 Views

We introduce a new robotic RGBD dataset with difficult luminosity conditions: ONERA.ROOM. It comprises RGB-D data (as pairs of images) and corresponding annotations in PASCAL VOC format (xml files)

It aims at People detection, in (mostly) indoor and outdoor environments. People in the field of view can be standing, but also lying on the ground as after a fall.

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429 Views

7200 .csv files, each containing a 10 kHz recording of a 1 ms lasting 100 hz sound, recorded centimeterwise in a 20 cm x 60 cm locating range on a table. 3600 files (3 at each of the 1200 different positions) are without an obstacle between the loudspeaker and the microphone, 3600 RIR recordings are affected by the changes of the object (a book). The OOLA is initially trained offline in batch mode by the first instance of the RIR recordings without the book. Then it learns online in an incremental mode how the RIR changes by the book.

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673 Views

The system obtained interference information from the measurement signal, solved the problem of phase wrapping, and got the accurate coordinates of target. The tags and tag-free items including shrimp chips, cola and instant noodles were taken as target respectively in experiment.

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546 Views

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