Dataset Open Access

Benzene Concentration Dataset

Chang Wei Tan; Christoph Bergmeir; Francois Petitjean; Geoffrey I Webb


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    <subfield code="u">Monash University</subfield>
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    <subfield code="a">Chang Wei Tan</subfield>
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    <subfield code="a">Benzene Concentration Dataset</subfield>
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    <subfield code="a">&lt;p&gt;This dataset is part of the Monash, UEA &amp;amp;&amp;nbsp;UCR time series regression repository.&amp;nbsp;&lt;a href="http://tseregression.org/"&gt;http://tseregression.org/&lt;/a&gt;&lt;/p&gt;

&lt;p&gt;This goal of this dataset is to predict benzene concentration in an Italian city. This dataset contains 8878 time series obtained from the Air Quality dataset from the UCI repository.&amp;nbsp;The time series has 8 dimensions which consists of hourly averaged responses from an array of 5 metal oxide chemical sensors embedded in an Air Quality Chemical Multisensor Device, as well as temperature, relative humidity and absolute humidity.&amp;nbsp;The Air Quality Chemical Multisensor device was located on the field in a significantly polluted area, at road level, within an Italian city.&amp;nbsp;Data were recorded from March 2004 to February 2005 (one year) representing the longest freely available recordings of on field deployed air quality chemical sensor devices responses.&amp;nbsp;Ground Truth hourly averaged concentrations for CO, Non Metanic Hydrocarbons, Benzene, Total Nitrogen Oxides (NOx) and Nitrogen Dioxide (NO2) and were provided by a co-located reference certified analyzer.&lt;br&gt;
&lt;br&gt;
Please refer to &lt;a href="https://archive.ics.uci.edu/ml/datasets/Air+Quality"&gt;https://archive.ics.uci.edu/ml/datasets/Air+Quality&lt;/a&gt;&amp;nbsp;for more details.&lt;/p&gt;

&lt;p&gt;Relevant papers&lt;br&gt;
S. De Vito, E. Massera, M. Piga, L. Martinotto, G. Di Francia, On field calibration of an electronic nose for benzene estimation in an urban pollution monitoring scenario, Sensors and Actuators B: Chemical, Volume 129, Issue 2, 22 February 2008, Pages 750-757, ISSN 0925-4005.&lt;br&gt;
Saverio De Vito, Marco Piga, Luca Martinotto, Girolamo Di Francia, CO, NO2 and NOx urban pollution monitoring with on-field calibrated electronic nose by automatic bayesian regularization, Sensors and Actuators B: Chemical, Volume 143, Issue 1, 4 December 2009, Pages 182-191, ISSN 0925-4005.&lt;br&gt;
S. De Vito, G. Fattoruso, M. Pardo, F. Tortorella and G. Di Francia, Semi-Supervised Learning Techniques in Artificial Olfaction: A Novel Approach to Classification Problems and Drift Counteraction, in IEEE Sensors Journal, vol. 12, no. 11, pp. 3215-3224, Nov. 2012. doi: 10.1109/JSEN.2012.2192425&lt;/p&gt;

&lt;p&gt;&lt;br&gt;
Citation request&lt;br&gt;
S. De Vito, E. Massera, M. Piga, L. Martinotto, G. Di Francia, On field calibration of an electronic nose for benzene estimation in an urban pollution monitoring scenario, Sensors and Actuators B: Chemical, Volume 129, Issue 2, 22 February 2008, Pages 750-757, ISSN 0925-4005&lt;/p&gt;</subfield>
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