This paper presents a dataset for Bluetooth 5.1 direction of arrival (DoA). The dataset was generated with a specifically designed mathematical model of a non-uniform rectangular antenna array. The Python source files that generated the dataset are also provided. The dataset was conceived as a starting point for developing and validating DoA algorithms for real-life scenarios. Unlike other datasets, it contains Bluetooth signals with not only varying intensity of additive white Gaussian noise, but also coherent interfering signals with random DoA coordinates. The dataset is divided into two branches, one consisting of pure sinusoidal tones and the second comprised of baseband Bluetooth signals. Since the codebase which generates the data is included, this dataset has a high reuse potential, and it can be modified to suit also other types of signals or different array topologies.
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http://dx.doi.org/10.1016/j.dib.2021.107576 | DOI Listing |
Sci Rep
December 2024
Department of Electrical and Electronics Engineering, Izmir Democracy University, 35140, Izmir, Turkey.
The rising popularity of wearable activity tracking devices can be attributed to their capacity for gathering and analysing ambient data, which finds utility across numerous applications. In this study, a wearable activity tracking device is developed using the BBC micro:bit development board to identify basic bachata dance steps. Initially, a pair of smart ankle bracelets is crafted, employing the BBC micro:bit board equipped with a built-in accelerometer sensor and a Bluetooth module for transmitting accelerometer data to smartphones.
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August 2024
Institute of Computing, Federal University of Amazonas, Amazonas, Brazil.
This paper describes a data collection experiment focused on researching indoor positioning systems using Bluetooth Low Energy (BLE) devices. The study was conducted in a real-world scenario with 150 test points and collected signals from 11 mobile devices. The dataset contains RSSI values from the mobile devices in relation to 15 fixed anchor nodes in the experimentation scenario.
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June 2024
M. Kandiah Faculty of Medicine and Health Sciences, Universiti Tunku Abdul Rahman, Bandar Sungai Long, 43000, Kajang, Selangor, Malaysia.
With an increasing prevalence of thyroid nodules globally, this study investigates the potential correlation between the use of Bluetooth headsets and the incidence of thyroid nodules, considering the cumulative effects of non-ionizing radiation (NIR) emitted by these devices. In this study, we analyzed 600 valid questionnaires from the WenJuanXing platform using Propensity Score Matching (PSM) and the XGBOOST model, supplemented by SHAP analysis, to assess the risk of thyroid nodules. PSM was utilized to balance baseline characteristic differences, thereby reducing bias.
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April 2024
Institute of Information Science and Technologies, National Research Council, (ISTI-CNR), Via G. Moruzzi, 1, 56124, Pisa, Italy.
This paper describes a data collection experiment and the resulting dataset based on Bluetooth beacon messages collected in an indoor museum. The goal of this dataset is to study algorithms and techniques for proximity detection between people and points of interest (POI). To this purpose, we release the data we collected during 32 museum's visits, in which we vary the adopted smartphones and the visiting paths.
View Article and Find Full Text PDFFront Hum Neurosci
February 2024
Department of Biomedical Engineering, Ulsan National Institute of Science and Technology, Ulsan, Republic of Korea.
Brain-computer interfaces (BCIs) have a potential to revolutionize human-computer interaction by enabling direct links between the brain and computer systems. Recent studies are increasingly focusing on practical applications of BCIs-e.g.
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