Non-invasive Localization using Software-Defined Radios

Khan, M. Z., Taha, A. , Taylor, W., Imran, M. and Abbasi, Q. (2022) Non-invasive Localization using Software-Defined Radios. [Data Collection]

Collection description

The dataset is about locating human activities in an office environment. Radio frequency (RF) sensing was employed in particular to collect unique channel fluctuations induced by multiple activities. The data collection hardware consists of two USRP devices that communicate with each other when activity takes place inside their coverage region. The USRPs are based on the National Instrument (NI) X310/X300 models, which are connected to two PCs by 1G Ethernet connections and have extended bandwidth daughterboard slots that cover DC–6 GHz and up to 120 MHz of baseband bandwidth. The two PCs were equipped with Intel(R) Core (TM) i7 7700.360 GHz processors, 16 GB RAM, and the Ubuntu 16.04 virtual operating system. For wireless communication, the USRPs were equipped with VERT2450 omnidirectional antennae. One participant performed in a room environment for the duration of the experiment, collecting 4300 samples for seven different activities in three zones and locations.

Funding:
College / School: College of Science and Engineering
Date Deposited: 09 Jun 2022 09:10
URI: http://researchdata.gla.ac.uk/id/eprint/1283

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Khan, M. Z., Taha, A. , Taylor, W., Imran, M. and Abbasi, Q. (2022); Non-invasive Localization using Software-Defined Radios

University of Glasgow

DOI: 10.5525/gla.researchdata.1283

Retrieved: 2022-09-30

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