Gas Sensor Array Drift Dataset
Abstract
"Long-term laboratory recordings from a 16-sensor chemical gas array exposed to six different gases across multiple batches, designed to study sensor drift and robustness of gas classification models.[web:87][web:89][web:95][web:104]"
Description
Overview
The Gas Sensor Array Drift Dataset contains real measurements from an array of 16 metal-oxide gas sensors exposed to six distinct pure gases at different concentration levels over time.[web:87][web:89][web:95][web:104]
Data Collection
- 13,910 measurements collected in ten batches over a period of 36 months, capturing long-term sensor drift behavior.[web:87][web:89][web:95]
- Six gases: Ammonia, Acetaldehyde, Acetone, Ethylene, Ethanol, and Toluene.[web:87][web:95][web:104]
- Each measurement is a vector of sensor responses plus a label indicating the gas class (and concentration for the related “different concentrations” variant).[web:87][web:89]
Features
- 16 real-valued features corresponding to conductance-based responses of the metal-oxide sensors.[web:87][web:89]
- Class labels for the six gases, enabling supervised classification and drift-compensation experiments.[web:87][web:95]
- Batch identifiers to study temporal drift and domain adaptation across acquisition sessions.[web:87][web:89][web:104]
Use Cases
- Benchmarking drift compensation and domain adaptation methods for electronic nose systems.[web:95][web:98]
- Developing robust gas classification models for environmental monitoring and industrial safety.[web:87][web:95]
- Analyzing long-term stability of IoT chemical sensor deployments.[web:87][web:89]
License and Terms
The dataset is distributed through the UCI Machine Learning Repository; users should follow the repository’s terms of use and any conditions specified on the dataset page.[web:89][web:70][web:65]
📊 View Data Structure
To explore column names, data types, and sample rows, visit the official dataset page on UCI Machine Learning Repository.
Preview on UCI Machine Learning Repository
Cite This Dataset
Vergara, Alexander et al. (2012). Gas Sensor Array Drift Dataset. [Dataset]. UCI Machine Learning Repository. https://archive.ics.uci.edu/dataset/224/gas+sensor+array+drift+dataset
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Original source: UCI Machine Learning Repository (2012). Visit official page for more details.
Indexed by IoTDataset.com on Jan 27, 2026
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