Optimization of Classification Prediction Performances of an Instrumental Odour Monitoring System by Using Temperature Correction Approach
Odour emissions generated by industrial and environmental protection plants are often a cause of nuisances and consequent conflicts in exposed populations. Their control is a key action to avoid complaints. Among the odour measurement techniques, the sensory-instrumental method with the application...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-06-01
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| Series: | Chemosensors |
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| Online Access: | https://www.mdpi.com/2227-9040/9/6/147 |
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| author | Giuseppina Oliva Tiziano Zarra Raffaele Massimo Vincenzo Senatore Antonio Buonerba Vincenzo Belgiorno Vincenzo Naddeo |
| author_facet | Giuseppina Oliva Tiziano Zarra Raffaele Massimo Vincenzo Senatore Antonio Buonerba Vincenzo Belgiorno Vincenzo Naddeo |
| author_sort | Giuseppina Oliva |
| collection | DOAJ |
| description | Odour emissions generated by industrial and environmental protection plants are often a cause of nuisances and consequent conflicts in exposed populations. Their control is a key action to avoid complaints. Among the odour measurement techniques, the sensory-instrumental method with the application of Instrumental Odour Monitoring Systems (IOMSs) currently represents an effective solution to allow a continuous classification and quantification of odours in real time, combining the advantages of conventional analytical and sensorial techniques. However, some aspects still need to be improved. The study presents and discusses the investigation and optimization of the operational phases of an advanced IOMS, applied for monitoring of environmental odours, with the aim of increasing their performances and reliability of the measures. Accuracy rates of over 98% were reached in terms of classification performances. The implementation of automatic correction systems for the resistance values of the measurement sensors, by considering the influence of the temperature, has been proven to be a solution to further improve the reliability of IOMS. The proposed approach was based on the application of corrective coefficients experimentally determined by analyzing the correlation between resistance values and operating conditions. The paper provides useful information for the implementation of real-time management activities by using a tailor-made software, able to increase and enlarge the IOMS fields of application. |
| first_indexed | 2024-03-10T10:21:37Z |
| format | Article |
| id | doaj.art-8ec2242adf364c1891a8462c232f4ebf |
| institution | Directory Open Access Journal |
| issn | 2227-9040 |
| language | English |
| last_indexed | 2024-03-10T10:21:37Z |
| publishDate | 2021-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Chemosensors |
| spelling | doaj.art-8ec2242adf364c1891a8462c232f4ebf2023-11-22T00:22:51ZengMDPI AGChemosensors2227-90402021-06-019614710.3390/chemosensors9060147Optimization of Classification Prediction Performances of an Instrumental Odour Monitoring System by Using Temperature Correction ApproachGiuseppina Oliva0Tiziano Zarra1Raffaele Massimo2Vincenzo Senatore3Antonio Buonerba4Vincenzo Belgiorno5Vincenzo Naddeo6Department of Civil Engineering, Sanitary Environmental Engineering Division (SEED), University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, SA, ItalyDepartment of Civil Engineering, Sanitary Environmental Engineering Division (SEED), University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, SA, ItalyDepartment of Civil Engineering, Sanitary Environmental Engineering Division (SEED), University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, SA, ItalyDepartment of Civil Engineering, Sanitary Environmental Engineering Division (SEED), University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, SA, ItalyInter-University Centre for Prediction and Prevention of Relevant Hazards (Centro Universitario per La Previsione e Prevenzione Grandi Rischi, C.U.G.RI.), Fisciano Campus, University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, SA, ItalyDepartment of Civil Engineering, Sanitary Environmental Engineering Division (SEED), University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, SA, ItalyDepartment of Civil Engineering, Sanitary Environmental Engineering Division (SEED), University of Salerno, Via Giovanni Paolo II 132, 84084 Fisciano, SA, ItalyOdour emissions generated by industrial and environmental protection plants are often a cause of nuisances and consequent conflicts in exposed populations. Their control is a key action to avoid complaints. Among the odour measurement techniques, the sensory-instrumental method with the application of Instrumental Odour Monitoring Systems (IOMSs) currently represents an effective solution to allow a continuous classification and quantification of odours in real time, combining the advantages of conventional analytical and sensorial techniques. However, some aspects still need to be improved. The study presents and discusses the investigation and optimization of the operational phases of an advanced IOMS, applied for monitoring of environmental odours, with the aim of increasing their performances and reliability of the measures. Accuracy rates of over 98% were reached in terms of classification performances. The implementation of automatic correction systems for the resistance values of the measurement sensors, by considering the influence of the temperature, has been proven to be a solution to further improve the reliability of IOMS. The proposed approach was based on the application of corrective coefficients experimentally determined by analyzing the correlation between resistance values and operating conditions. The paper provides useful information for the implementation of real-time management activities by using a tailor-made software, able to increase and enlarge the IOMS fields of application.https://www.mdpi.com/2227-9040/9/6/147air qualitycontinuous monitoringlinear discriminant analysisMOS sensorodour emissions |
| spellingShingle | Giuseppina Oliva Tiziano Zarra Raffaele Massimo Vincenzo Senatore Antonio Buonerba Vincenzo Belgiorno Vincenzo Naddeo Optimization of Classification Prediction Performances of an Instrumental Odour Monitoring System by Using Temperature Correction Approach Chemosensors air quality continuous monitoring linear discriminant analysis MOS sensor odour emissions |
| title | Optimization of Classification Prediction Performances of an Instrumental Odour Monitoring System by Using Temperature Correction Approach |
| title_full | Optimization of Classification Prediction Performances of an Instrumental Odour Monitoring System by Using Temperature Correction Approach |
| title_fullStr | Optimization of Classification Prediction Performances of an Instrumental Odour Monitoring System by Using Temperature Correction Approach |
| title_full_unstemmed | Optimization of Classification Prediction Performances of an Instrumental Odour Monitoring System by Using Temperature Correction Approach |
| title_short | Optimization of Classification Prediction Performances of an Instrumental Odour Monitoring System by Using Temperature Correction Approach |
| title_sort | optimization of classification prediction performances of an instrumental odour monitoring system by using temperature correction approach |
| topic | air quality continuous monitoring linear discriminant analysis MOS sensor odour emissions |
| url | https://www.mdpi.com/2227-9040/9/6/147 |
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