Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring
Recently, the emergence of low-cost sensors have allowed electronic noses to be considered for densifying the actual air pollution monitoring networks in urban areas. Electronic noses are affected by changes in environmental conditions and sensor drifts over time. Therefore, they need to be calibrat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/18/11/3716 |
| _version_ | 1828136472912330752 |
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| author | Rachid Laref Etienne Losson Alexandre Sava Maryam Siadat |
| author_facet | Rachid Laref Etienne Losson Alexandre Sava Maryam Siadat |
| author_sort | Rachid Laref |
| collection | DOAJ |
| description | Recently, the emergence of low-cost sensors have allowed electronic noses to be considered for densifying the actual air pollution monitoring networks in urban areas. Electronic noses are affected by changes in environmental conditions and sensor drifts over time. Therefore, they need to be calibrated periodically and also individually because the characteristics of identical sensors are slightly different. For these reasons, the calibration process has become very expensive and time consuming. To cope with these drawbacks, calibration transfer between systems constitutes a satisfactory alternative. Among them, direct standardization shows good efficiency for calibration transfer. In this paper, we propose to improve this method by using kernel SPXY (sample set partitioning based on joint x-y distances) for data selection and support vector machine regression to match between electronic noses. The calibration transfer approach introduced in this paper was tested using two identical electronic noses dedicated to monitoring nitrogen dioxide. Experimental results show that our method gave the highest efficiency compared to classical direct standardization. |
| first_indexed | 2024-04-11T18:04:51Z |
| format | Article |
| id | doaj.art-0027f03cf6fb45e69d4b82f6adcfae50 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T18:04:51Z |
| publishDate | 2018-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-0027f03cf6fb45e69d4b82f6adcfae502022-12-22T04:10:22ZengMDPI AGSensors1424-82202018-11-011811371610.3390/s18113716s18113716Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution MonitoringRachid Laref0Etienne Losson1Alexandre Sava2Maryam Siadat3Laboratoire de Conception, Optimisation et Modélisation des Systèmes, LCOMS EA 7306, Université de Lorraine, 57000 Metz, FranceLaboratoire de Conception, Optimisation et Modélisation des Systèmes, LCOMS EA 7306, Université de Lorraine, 57000 Metz, FranceLaboratoire de Conception, Optimisation et Modélisation des Systèmes, LCOMS EA 7306, Université de Lorraine, 57000 Metz, FranceLaboratoire de Conception, Optimisation et Modélisation des Systèmes, LCOMS EA 7306, Université de Lorraine, 57000 Metz, FranceRecently, the emergence of low-cost sensors have allowed electronic noses to be considered for densifying the actual air pollution monitoring networks in urban areas. Electronic noses are affected by changes in environmental conditions and sensor drifts over time. Therefore, they need to be calibrated periodically and also individually because the characteristics of identical sensors are slightly different. For these reasons, the calibration process has become very expensive and time consuming. To cope with these drawbacks, calibration transfer between systems constitutes a satisfactory alternative. Among them, direct standardization shows good efficiency for calibration transfer. In this paper, we propose to improve this method by using kernel SPXY (sample set partitioning based on joint x-y distances) for data selection and support vector machine regression to match between electronic noses. The calibration transfer approach introduced in this paper was tested using two identical electronic noses dedicated to monitoring nitrogen dioxide. Experimental results show that our method gave the highest efficiency compared to classical direct standardization.https://www.mdpi.com/1424-8220/18/11/3716calibration transferdirect standardizationsupport vector machine regressionelectronic noseair pollution monitoringgas sensors |
| spellingShingle | Rachid Laref Etienne Losson Alexandre Sava Maryam Siadat Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring Sensors calibration transfer direct standardization support vector machine regression electronic nose air pollution monitoring gas sensors |
| title | Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring |
| title_full | Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring |
| title_fullStr | Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring |
| title_full_unstemmed | Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring |
| title_short | Support Vector Machine Regression for Calibration Transfer between Electronic Noses Dedicated to Air Pollution Monitoring |
| title_sort | support vector machine regression for calibration transfer between electronic noses dedicated to air pollution monitoring |
| topic | calibration transfer direct standardization support vector machine regression electronic nose air pollution monitoring gas sensors |
| url | https://www.mdpi.com/1424-8220/18/11/3716 |
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