Environmental Interference Gas Sensor Anomaly Dataset
- Records
- 6530
- Size
- 0.4GB
- Format
- JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-05
This dataset links gas sensor readings with environmental variables such as temperature, humidity, and air pressure in JSON time-series records. It covers both pseudo-anomalies caused by environmental changes and genuine sensor anomalies under relatively stable environmental conditions. Raw measurements, environmental change features, adjusted readings, anomaly categories, and scores support the analysis of multivariate temporal dependencies and the training and evaluation of anomaly detection models.
Overview
Dataset Insights
Preview
Sample Examples
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| is_anomaly | boolean | Indicates whether the current sensor record is classified as anomalous. |
| anomaly_score | number | A sensor anomaly severity score calculated from multivariate temporal dependencies and environment-adjusted readings. |
| raw_measurement | object | Raw JSON measurement records from gas sensors and environmental sensors. |
| anomaly_category | string | An anomaly classification for the current record based on the relationship between environmental changes and sensor behavior. |
| anomaly_confidence | number | The model's confidence in the anomaly detection result, with values ranging from 0 to 1. |
| environment_change_features | object | Environmental change features calculated from the current record and historical environmental variables within a time window. |
| environment_adjusted_gas_readings | object | Gas sensor readings adjusted to remove or reduce the effects of temperature, humidity, and air pressure. |
Trust
Compliance Statement
Authorization Type
Proprietary - Commercial AI Training License (No Redistribution)
Commercial Use
Requires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and Anonymization
No PII, no real company names, simulated scenarios follow industry standards
Compliance System
Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs
FAQ
Frequently Asked Questions
- What types of data are included?
- JSON time-series records link gas sensor measurements with environmental variables. Fields include environmental change features, adjusted gas readings, anomaly categories, anomaly scores, and confidence values.
- How can environmental pseudo-anomalies be distinguished from genuine anomalies?
- Records include environmental variables and time-window change features, along with adjusted readings and anomaly categories. These data can support training and evaluation of models that distinguish environmental effects from sensor faults; the exact decision criteria depend on the task definition and model design.
- Which training and evaluation tasks does the dataset support?
- It can support multivariate time-series anomaly detection, anomaly classification, environmental factor correction, and anomaly confidence evaluation. It is also suitable for hard example mining focused on environmental confounding factors.
- How can the dataset be obtained, and what licensing terms apply?
- Check the dataset product page for available access methods, specifications, and licensing terms. Permitted use, redistribution rights, and commercial use are subject to the applicable license agreement.
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Cite this Work
@dataset{Mobiusi2026,
title={Environmental Interference Gas Sensor Anomaly Dataset},
author={MOBIUSI INC},
year={2026},
url={https://www.mobiusi.com/datasets/0f0ef7f2fae324db44468184ca167d6d?dataset_scene_id=6},
urldate={2026-10-28},
keywords={gas sensor anomaly dataset,sensor anomaly detection,environmental interference data,multivariate time series,gas sensor readings,temperature humidity pressure monitoring,environmental correction,industrial sensor data},
version={1.0}
}Using this in research? Please cite us.