DOI: 10.5281/zenodo.3355208
title: Ozone and Carbon Monoxide Dataset Collected by the OpenSense Zurich Mobile Sensor Network

description: <strong>Ozone and Carbon Monoxide Dataset Collected by the OpenSense Zurich Mobile Sensor Network</strong> This dataset contains ozone (O3) and carbon monoxide (CO) concentration measurements collected by the OpenSense (http://www.opensense.ethz.ch) mobile senor network over the course of 4.5 years (2012/02-2016/09). The sensors are mounted on top of 10 streetcars in the city of Zurich, Switzerland. <br> In particular, the dataset contains: Ozone (O3) data: 2012/02 - 2016/09 (19.9 Mio samples) Carbonmonoxide (CO) data: 2014/03 - 2016/09 (49.7Mio samples) <strong>Hardware:</strong><br> -------------- Ozone sensor: SGX (former e2V) MiCS-OZ-47 Ozone Sensing Head with Smart Transmitter PCB Carbon monoxide sensor: Alphasense CO-B4 GPS receiver: u-blox EVK-6p <strong>Data files format: </strong><br> -------------------------<br> co_data_*: Time of day: yyyy.mm.dd HH:MM Latitude WGS84 Longitude WGS84 HDOP: horizontal dilution of precision, uncertainty of the GPS position Tram ID WE_CHANNEL_SENSOR_1_MV: The voltage [in mV] at the working electrode of the electrochemical sensor (see Alphasense CO-B4 datasheet for more details) o3_data_*: Time of day: yyyy.mm.dd HH:MM Latitude WGS84 Longitude WGS84 HDOP: horizontal dilution of precision, uncertainty of the GPS position Tram ID Ozone [ppb]: On-device calibrated (according to manufacturer) ozone measurement [in parts-per-billion] Temperature [in °C] Relative Humidity [in %] <strong>Data quality:</strong><br> ------------------<br> The data has NOT been post-processed!<br> In order to achieve high data quality, the data needs to be cleaned (e.g. outlier filtering) and, most importantly, the sensors need to be individually calibrated.<br> Reference data can be obtained from www.ostluft.ch, the official air quality monitoring network in eastern Switzerland, which operates multiple monitoring stations in the city of Zurich. <strong>Plot Coverage Map (MATLAB):</strong><br> --------------------------------------------<br> The provided MATLAB script plot_data_coverage.m plots the locations of the collected samples onto the map of Zurich (map_zurich.png). <strong>References:</strong><br> -----------------<br> The dataset (and related aspects) has partly been used and is described in more detail in the following publications: Balz Maag et al. <strong>SCAN: Multi-Hop Calibration for Mobile Sensor Arrays</strong>. In Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, Vol.1, No.2 (IMWUT), 2017. Olga Saukh et al. <strong>Reducing Multi-Hop Calibration Errors in Mobile Sensor Networks</strong>. In IEEE/ACM International Conference on Information Processing in Sensor Networks (IPSN), 2015. Best Paper Award! Olga Saukh et al. <strong>Route Selection for Mobile Sensor Nodes on Public Transport Networks</strong>. In Journal of Ambient Intelligence and Humanized Computing, 5(3), Springer, 2014. Olga Saukh et al. <strong>On Rendezvous in Mobile Sensing Networks</strong>. In Proceedings of the 5th Workshop on Real-World Wireless Sensor Networks (RealWSN), 2013. Jason Jingshi Li et al. <strong>Sensing the Air we Breathe – The OpenSense Zurich Dataset</strong>. In Proceedings of the 26th International Conference on Artificial Intelligence (AAAI), 2012. Olga Saukh et al. <strong>Route Selection for Mobile Sensors with Checkpointing Constraints</strong>. In Proceedings of the 8th International Workshop on Sensor Networks and Systems for Pervasive Computing (PerSeNS, in conjunction with IEEE PerCom), March 2012. David Hasenfratz et al. <strong>On-the-fly Calibration of Low-Cost Gas Sensors</strong>. In Proceedings of the 9th European Conference on Wireless Sensor Networks (EWSN), 2012. <br> For further information, visit: http://www.opensense.ethz.ch