Data · dataset · 2026
Raw dataset collected from 45 VOC sensors under controlled pollutant and environmental conditions
Listed in Teesside University Research Data Repository
The included data represents raw sensor responses (from 35 Metal Oxide and 10 electrochemical) under controlled Volatile Organic Compound (VOC) concentrations and environemntal conditions.
Description
The 45 total sensors are a part of 5 identical multisensor arrays, which were installed in a 36 L exposition chamber. The dataset includes seven total experimental campaigns.
Five experimental campaigns investigated the effects of cyclic exposure of sensors to 5 representative indoor VOCs under controlled humidity, resulting in 5 dataset files which contain all the sensor responses and 5 files which contain the reference SIFT-MS synchronised measurements. The last two experiments and the corresponding two dataset files represent the raw sensor responses under varying temperature and humidity levels; one dataset for variations under clean air, and one for variations under constant 500 ppb of Acetone.
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The dataset can support research on drift compensation due to environmental conditions, sensor calibration, pattern recognition, validation of machine learning algorithms and sensor selection.
Links
Where it is published
- DOI doi.org/10.17632/9v3nywn7hy.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Analytical chemistry · Chemistry · Computer Science & AI · Earth & Environmental Science · Machine learning
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/9v3nywn7hy.1 | 16 h ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:3401 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Analytical Chemistry'] |
| concepts[field].anzsrc:group:4611 | mapping · researchdata tees ac uk | vocabulary-mapper@1.0.0 | keywords['Machine Learning'] |
| concepts[field].local:field:chemistry | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |