5 Works

CRAWDAD dataset hasselt/EDM (v. 2017-06-09)

Pieter Robyns, Bram Bonné, Peter Quax & Wim Lamotte
A complete collection of all management and control frames (including Radiotap headers) observed at our research lab from 28 January to 8 Febuary 2016. This dataset was used to calculate the "stability" and "variability" of Probe Request IEs (see our paper for more details on these metrics).

CRAWDAD dataset hasselt/EDM (v. 2017-06-09)

Pieter Robyns, Bram Bonné, Peter Quax & Wim Lamotte
A complete collection of all management and control frames (including Radiotap headers) observed at our research lab from 28 January to 8 Febuary 2016. This dataset was used to calculate the "stability" and "variability" of Probe Request IEs (see our paper for more details on these metrics).

CRAWDAD dataset hasselt/EDM (v. 2017-06-09)

Pieter Robyns, Bram Bonné, Peter Quax & Wim Lamotte
A complete collection of all management and control frames (including Radiotap headers) observed at our research lab from 28 January to 8 Febuary 2016. This dataset was used to calculate the "stability" and "variability" of Probe Request IEs (see our paper for more details on these metrics).

CRAWDAD dataset copelabs/usense (v. 2017-01-27)

S. Firdose, L. Lopes, W. Moreira, R. Sofia & P. Mendes
This dataset comprises experiments carried out with the open-source middleware NSense (fomerly named as USense), available at https://github.com/COPELABS-SITI/NSense. The data has been collected based on four sensors: bluetooth; Wi-Fi; microphone; accelerometer. NSense then relies on four different pipelines to compute aspects such as relative distance (Wi-Fi); social strength (based on bluetooth contact duration); sound activity level; motion. We set up experiments making use of Samsung Galaxy S3 devices. For each experiment, there is the following...

CRAWDAD dataset copelabs/usense (v. 2017-01-27)

S. Firdose, L. Lopes, W. Moreira, R. Sofia & P. Mendes
This dataset comprises experiments carried out with the open-source middleware NSense (fomerly named as USense), available at https://github.com/COPELABS-SITI/NSense. The data has been collected based on four sensors: bluetooth; Wi-Fi; microphone; accelerometer. NSense then relies on four different pipelines to compute aspects such as relative distance (Wi-Fi); social strength (based on bluetooth contact duration); sound activity level; motion. We set up experiments making use of Samsung Galaxy S3 devices. For each experiment, there is the following...

Registration Year

  • 2017
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Resource Types

  • Dataset
    5