We conducted a study with 126 subjects, over three months, collecting data from various sensors, that resulted in a multimodal dataset for co-presence detection. We publish a subset of the original data set in the period between 01.06.2018 and 15.06.2018 including Wi-Fi scans as proximity verification set, magnetometer as sensor data, the positions of Wi-Fi access points, and magnetometer's sensor hardware. This study has been published at IEEE PerCrowd 2020, M. Haus, A. Y. Ding,...
We measured from VanLAN, a modest-size testbed that we have deployed, to analyze the fundamental characteristics of WiFi-based connectivity between basestations and vehicles in urban settings.
The Wifidelity package consists of two tools to identify the completeness and accuracy of 802.11 packet traces. "tracestats" uses 802.11 sequence numbers to quantify completeness, and the "plotscore" script generates a T-Fi plot: an at-a-glance, heatmap visualization of completeness versus load. "tracetiming" uses AP Beacon intervals to quantify packet timestamp accuracy and "plottiming" produces a line plot of timestamp accuracy.
This dataset contains mobility traces of taxi cabs in Rome, Italy. It contains GPS coordinates of approximately 320 taxis collected over 30 days.
AnonTool, an open-source implementation of Anonymization API, provides an easy to use, flexible and efficient library of functions that can be used to anonymize live traffic, or packet traces in libpcap file format. Currently, IP, TCP/UDP, HTTP, FTP and Netflow v5 and v9 are supported. Three ready-to-use applications have been implemented on top of this library; one provides basic anonymization functionality for the IP/TCP/UDP protocols, and two more which can perform anonymization on every field...
Measurement of the channel gain for multiple distances within a factory environment
This dataset includes syslog, SNMP, and tcpdump data for 3 years or more, for over 450 access points and several thousand users at dartmouth college.
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...
This data set comprises experiments carried out considering four Android devices, each named Usense 2, 3, 4, and 5, respectively. These devices were carried by people sharing the same affiliation during their daily routines (commuting between home and office, going to leisure activities, attending meetings in the office). All the data was collected each and every one minute.
This data includes a number of traces of Bluetooth sightings by groups of users carrying small devices (iMotes) for a number of days - in office environments and conference environments.
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...
This dataset includes the traces collected by wireless monitoring at the 62nd Internet Engineering Task Force (IETF) meeting held in Minneapolis, MN, March, 2005.
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...
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).
This dataset includes radiant light energy measurements from a study by Columbia University's EnHANTs (Energy Harvesting Active Networked Tags) project.
Mobile devices try to automatically switch to WiFi connectivity whenever possible. To facilitate this automatic process, they store the list of the names (SSID) of the networks the user typically connects to and, periodically, these SSIDs are sent in broadcast in the form of Probe Request to search for available networks. The following questions then rise naturally: "What do your smartphone probes say about you?"; "Is it possible to infer meaningful relationships among a group...
This data includes a number of traces of Bluetooth sightings by groups of users carrying small devices (iMotes) for a number of days - in office environments, conference environments, and city environments.
We conduct measurement using two mesh network testbeds in two diﬀerent frequency bands – 802.11g in 2.4GHz band and 802.11a in 5GHz band.
Dataset of network performance data collected with WiScape framework from three commercial cellular wireless networks.
Dataset of BitTorrent traffic from Korea Telecom's mobile WiMAX network, collected in March 2010.
The authors gathered a detailed trace of network activity at OSDI 2006 to enable analysis of the behavior of a wireless LAN that is (presumably) heavily used.
Dataset gathered by Nodobo, a suite of social sensor software for Android phones, during a study of the mobile phone usage at University of Strathclyde.
This dataset is to be used in conjunction with the roma/taxi dataset and provides the outdoor temperature of the areas in Rome where the taxis were located (289 taxicabs over 4 days).
To help us better understand the properties of various energy sources and their impact on energy harvesting adaptive algorithms, we collected acceleration traces from different participants. The volunteers were asked to perform normal daily routines while comfortably carrying SparkFun Electronics ADXL345 accelerometer boards. For our long-term studies, we collected over 200 hours of acceleration information in 25 days from 5 participants. The data simulates the natural motions that participants' belongings (keys, phone, or wallet) experience...
This dataset includes SNMP and tcpdump records from 4 access points at a three-day computer-science conference.