Welcome to CRAWDAD CRAWDAD is the Community Resource for Archiving Wireless Data At Dartmouth, a wireless network data resource for the research community. This archive has the capacity to store wireless trace data from many contributing locations, and staff to develop better tools for collecting, anonymizing, and analyzing the data. We work with community leaders to ensure that the archive meets the needs of the research community. CRAWDAD is grateful to its current and past sponsors. Latest News New CRAWDAD Data Set - Captured Zigbee packets from commercial smart home devices - May 26, 2020 A new data set has been added to CRAWDAD: cmu/zigbee-smarthome/20200526 This Carnegie Mellon University dataset contains Zigbee packets that were captured using a software-defined radio (USRP N210). You can use DOI 10.15783/c7-nvc6-4q28 to cite. DOI 10.15783/c7-nvc6-4q28 http://doi.org/10.15783/c7-nvc6-4q28 New CRAWDAD Data Set - Dataset of diverse context information (e.g., ambient audio) collected by multiple devices in different environments (e.g., office). - April 8, 2020 A new data set has been added to CRAWDAD: tuda/ubicompzis The dataset contains 10 types of context information (i.e., audio restricted access, Wi-Fi and Bluetooth Low Energy (BLE) beacons, barometric pressure, humidity, luminosity, temperature, accelerometer, gyroscope, and magnetometer) collected by multiple devices in three scenarios: car, office, and mobile. You can use DOI 10.15783/c7-n3q8-xr73 to cite. DOI 10.15783/c7-n3q8-xr73 http://doi.org/10.15783/c7-n3q8-xr73 New CRAWDAD Data Set - Dataset for evaluation of co-presence detection - February 18th, 2020 A new data set has been added to CRAWDAD: tum/proximityness 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 DOI 10.15783/c7-x43g-h794 http://doi.org/10.15783/c7-x43g-h794 New CRAWDAD Data Set - Community RF Sensing via iPhones for Source Localization and Coverage Maps - November 14, 2019 A new data set has been added to CRAWDAD: tuc/mysignals MySignals dataset was collected by a network of approx. 10 mobile smartphone (iPhones) users via the MySignals iPhone App (www.mysignals.gr) for a period of approximately 8 months. DOI 10.15783/c7-3bk9-9t96 http://doi.org/10.15783/c7-3bk9-9t96 New CRAWDAD Data Set - GPS traces collected from a team of firefighters during a forest fire exercise - September 16, 2019 A new data set has been added to CRAWDAD: it/vr2marketbaiaotrial GPS traces collected from a team of firefighters during a forest fire exercise Contibuted by Ana Aguiar If you use these data, please let us know, and you can use https://crawdad.org/it/vr2marketbaiaotrial/20190916 or http://doi.org/10.15783/c7-hpaw-8b51 BibTeX and RIS are providBibTeX and RIS are provided on the website New CRAWDAD Data Set - Dataset of 4G and 5G RAN monitoring data collected using ElasticMon 5G monitoring framework over FlexRan - August 89, 2019 A new data set has been added to CRAWDAD: eurecom/elasticmon5G2019 Dataset of 4G and 5G RAN monitoring data collected with ElasticMon 5G monitoring framework over FlexRan Contributed by Berkay Koksal, Robert Schmidt, Xenofon Vasilakos, Navid Nikaien Ten dataset files containing 4G and 5G MAC, RRC and PDCP statistics and monitoring data, grouped into two versions of 5 datasets each: raw statistics and processed monitoring data. Raw datasets are recorded using ElasticMon v0.1, a prototype version of a monitoring framework extension of the FlexRAN 5G programmable platform for Software-Defined Radio Access Networks New CRAWDAD Data Set - Measurements for PhD: Surface density of radiation energy as an integral measure for the characterization of exposure to electromagnetic emissions - August 6, 2019 A new data set has been added to CRAWDAD: ues/emespy The measurement results provided here are part of work on PhD thesis connected with measurement results variability reduction (main focus was on GSM/UMTS system Contributed by Darko S. Suka, Predrag V. Pejovic, Mirjana I. Simic-Pejovic Equipment used is the dosimeter (or exposimeter) EME Spy 140 (manufactured by Satimo). Similar to the procedure described in (Vermeeren, 2013; Markakis et al., 2013), the exposimeter was placed at available position in the investigated rooms and were standing alone. It was, thus, not worn by adults. Also, no influence due to shielding occured, like when exposimeters are carried on the body (where underestimations up to 6.5 dB are possible according to Iskra et al. (2010)). During measurement period, all location were secured, and only authorized technical personnel that performed measurements had access to such places in order to provide measurement conditions of unperturbed field, according to EN 50492:2010 and EN 50413:2010 If you use these data, please let us know, and you can use https://crawdad.org/ues/emespy/20190806/ or DOI 10.15783/c7-ry9z-m812 https://doi.org/10.15783/c7-ry9z-m812. BibTeX and RIS are provided on the website New CRAWDAD Data Set - Dataset of wireless network measurements at the KTH campuses, collected during 2014-2015. - July 1, 2019 A new data set has been added to CRAWDAD: kth/campus Dataset of wireless network measurements at the KTH campuses collected during 2014-2015. Contributed by Ljubica Pajevic, Gunnar Karlsson, Viktoria Fodor. The dataset contains records of authenticated user associations to the wireless network of the KTH Royal Institute of Technology in Stockholm. The dataset also includes scan results and mapping information of Wi-Fi networks, collected by means of war-walking at the university's two largest campuses. If you use these data, please let us know, and you can use the DOI 10.15783/c7-5r6x-4b46 to cite. BibTeX and RIS are provided on the website. New CRAWDAD Data Set - Cause-Specific Episodes of Active Scanning. - June 5, 2019 A new data set has been added to CRAWDAD: iiitd/wifiactivescanning Cause-Specific Episodes of Active Scanning. Contributed by Gursimran Singh, Harish Fulara, Dheryta Jaisinghani, Mukulika Maity, Tanmoy Chakraborty, Vinayak Naik. The dataset includes packet captures collected from controlled experiments with various devices. The dataset captures active scanning behavior of the devices. Name of each folder represents the name of the cause of active scanning. For details please refer to our papers - Learning to Rescue WiFi Networks from Unnecessary Active Scans, WoWMoM 2019. If you use these data, please let us know, and you can use https://crawdad.org/iiitd/wifiactivescanning/20190605 or DOI 10.15783/c7-kybd-ys55. BibTeX and RIS are provided on the website. New CRAWDAD Data Set - Dataset of mobility traces of buses in Rio de Janeiro, Brasil - February 20, 2018 - February 23, 2018 A new data set has been added to CRAWDAD: coppe-ufrj/RioBusesorg/coppe-ufrj20180219/> Dataset of mobility traces of buses in Rio de Janeiro, Brasil. Contributed by Daniel Dias, Luis 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. If you use these data, please let us know, and you can use the DOI 10.15783/C7MP7S to cite. BibTeX and RIS are provided on the website. New CRAWDAD Data Set - Data concerning social interaction and propinquity based on wireless and bluetooth. - March 10, 2017 A new data set has been added to CRAWDAD: copelabs/usense 2017-01-27 Data concerning social interaction and propinquity based on wireless and bluetooth. Contributed by 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 set of data files: - SocialProximity.dat has three columns: Timestamp, DeviceName, Encounter Duration, Average Encounter Duration, Social Strength (Per hour) and Social Strength(Per minute) towards DeviceName - DistanceOutput.dat has three columns: Timestamp, DeviceName, and Distance towards DeviceName - Microphone.dat has two columns: Timestamp, and Soundlevel(QUIET, NORMAL, ALERT and NOISY) - PhysicalActivity.dat has two columns: Timestamp, and Activity as STATIONARY, WALKING and RUNNING There are two tracesets. A first traceset has been collected relying on a first NSense version in 2015. Then, a second traceset has been collected in 2016, with a refined version of NSense. In all tracesets, devices have been carried around by people that share the same affiliation during their individual daily routines (24 hour periods). If you use these data, please let us know, and you can use the DOI 10.15783/C7D885 to cite. BibTeX and RIS are provided on the website. new CRAWDAD dataset - wireless contacts traces from Android smartphones - October 30, 2016 A new dataset has been added to CRAWDAD. org/upb Trace of wireless contacts, social connections, and user interests, performed in an academic environment for 63 days, with 72 participants Contributed by Radu I. Ciobanu, Ciprian Dobre. Wireless contacts trace collected at the University Politehnica of Bucharest in the spring of 2012, using an application entitled HYCCUPS Tracer (http://hyccups.hpc.pub.ro), with the purpose of collecting contextual data from Android smartphones. It was run in the background and collected availability and mobile interaction information such as usage statistics, user activity, battery statistics, or sensor data, but it also gathered information about a device's encounters with other nodes or with wireless access points. Encounter collection was performed using AllJoyn. The data was collected by constructing and deleting wireless sessions using the AllJoyn framework based on WiFi. Tracing was executed asynchronously. The duration of the tracing experiment was 63 days, between March and May 2012, and had 72 participants, out of which only 42 had at least one contact. By analyzing the participants' Facebook profiles, the social connections matrix was extracted, as well as the users' interests. The trace (and others from the CRAWDAD collection) is parsed within the MobEmu simulator (used in all UPB's papers), publicly available at https://github.com/raduciobanu/mobemu. If you use these data, please let us know, and you can use the DOI 10.15783/C7TG7K to cite. BibTeX and RIS are provided on the website.