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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2026
License: CC BY
Data sources: Datacite
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Dataset for Radio Frequency Based Device-Free Crowd Size Estimation in Public Transportation Environments

Authors: Janssens, Robin; Berkvens, Rafael; Bellekens, Ben;

Dataset for Radio Frequency Based Device-Free Crowd Size Estimation in Public Transportation Environments

Abstract

This dataset was collected with the aim to evaluate the use of device-free wireless sensing to perform crowd size estimation in public transportation environments. This dataset contains measured Received Signal Strength Indicator (RSSI) data and manual people count data from 2 environments. The first environment is a platform of a subway station in Antwerp, Belgium. We will refer to this environment as the indoor environment. The second environment is an outdoor platform in Barcelona, Spain. We will refer to this environment as the outdoor environment. The measurement RSSI data is gathered using a wireless sensor network performing a measurement cycle every 10 seconds in which the sensor nodes sequentially transmit a message which is received by the other nodes in the network, storing the received signal strength upon reception. The message payload contains the list of last collected RSSI values for each node. This payload is received by the gateway and forwarded to the back-end server for storage and processing. Each of these messages as received by the gateway are repressented by a single line in the raw RSSI data as found in this dataset.The ground truth data has 2 types of values: values greater or equal to zero are people counts, negative values represent a rail vehicle entering (-1) or leaving (-2) the environment. These rail vehicle event values can be used to segment the dataset in counts when the rail vehicle was present or not, or for building a classification model to detect the presence of rail vehicles. Indoor Dataset This dataset is comprised of 4 full days of RSSI data and 3 instances of collected ground truth data. This data was collected at the Groenplaats subway station in the city of Antwerp, Belgium. Dataset file structure: data_platform_indoor ├── rssi_data │ ├── rssi_platform_indoor_2023-05-17.csv │ ├── rssi_platform_indoor_2023-05-18.csv │ ├── rssi_platform_indoor_2023-05-19.csv │ └── rssi_platform_indoor_2023-07-17.csv └── training_data ├── training_platform_indoor_2023-05-17.csv ├── training_platform_indoor_2023-05-19.csv └── training_platform_indoor_2023-07-17.csv Notes on the data:2023-05-17 : training data available, batteries replaced that day -> no calibration possible2023-05-18 : can be used for calibration of 2023-05-172023-05-19 : training data available2023-07-17 : training data available Outdoor Dataset This dataset is comprised of 3 full days of Received Signal Strength Indicator (RSSI) data and 3 instances of collected ground truth data. This data was collected at the Hospital Sant Joan Despí | TV3 tram stop in Barcelona, Spain. Dataset file structure: data_platform_outdoor ├── rssi_data │ ├── rssi_platform_outdoor_2024-06-11.csv │ ├── rssi_platform_outdoor_2024-06-12.csv │ └── rssi_platform_outdoor_2024-07-02.csv └── training_data ├── training_platform_outdoor_2024-06-11.csv ├── training_platform_outdoor_2024-06-12.csv └── training_platform_outdoor_2024-07-02.csv Notes on the data: 2024-06-11 : training data available, batteries replaced that day -> no calibration possible2024-06-12 : training data available2024-07-02 : training data available, training data gathered by other person than previous training data, no people counts during stopped trams

Related Organizations
Keywords

Public Transportation, People Counting, Crowd Management, Sensing, Crowd Counting, Wireless

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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