180 Works

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 istanbul_technical/rssi (v. 2015-12-02)

Metin Vural, Saliha Buyukcorak & Gunes Karabulut Kurt
Our measurement is performed in an urban macrocell environment in the GSM 900 downlink band based on real-life data. By a spectrum analyzer, 5 individual tracks with 10000 measurement data points are obtained. Channel sounding is carried out at a GSM base station located at a height of 6 meters. At every track point measurements are taken in a stationary fashion with 17ms sweep time on the ground level. GPS information is also saved. the...

CRAWDAD dataset init/factory (v. 2015-09-18)

Dimitri Block, Niels Hendrik Fliedner & Uwe Meier
Measurement of the channel gain for multiple distances within a factory environment

CRAWDAD dataset coppe-ufrj/RioBuses (v. 2018-02-20)

Daniel Dias & Luís Henrique Maciel Kosmalski Costa
Real-time position data reported by buses, updated every minute, from the city of Rio de Janeiro, Brazil. The file is CSV, containing the date, time(24h format), bus ID, bus line, latitude, longitude and speed of more than 12,000 buses.

CRAWDAD dataset unm/blebeacon (v. 2019-03-12)

Dimitrios Sikeridis, Ioannis Papapanagiotou & Michael Devetsikiotis
The BLEBeacon dataset is a collection of Bluetooth Low Energy (BLE) advertisement packets\/traces generated from BLE beacons carried by people following their daily routine inside a university building for a whole month. A network of Raspberry Pi 3 (RPi)-based edge devices were deployed inside a multi-floor facility continuously gathering BLE advertisement packets and storing them in a cloud-based environment. The focus is on presenting a real-life realization of a location-aware sensing infrastructure, that can provide...

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