AQUAIR Dataset

Domain:

agriculture

Record type:

dataset

Creator:

You

Host:

Dataset overview:
This repository contains the AQUAIR Dataset, a high-resolution log of indoor-environment quality (IEQ) gathered in a trout (Oncorhynchus mykiss) hatchery room at Amghass, Azrou, Morocco. Six airborne variables—air temperature, relative humidity, carbon-dioxide (CO₂), total volatile organic compounds (TVOC), fine particulate matter (PM₂.₅) and inhalable particulate matter (PM₁₀)—were sampled every 5 minutes between 14 October 2024 and 09 January 2025. The data are provided as two comma-separated files:

AQUAIR_1.csv : Contains data recorded from 14th October 2024 to 10th December 2024, has a total of 16 533 rows.

AQUAIR_2.csv : Contains data recorded from 15th December 2024 to 9th January 2025, has a total of 7 323 rows.

Combined, the set delivers 23 856 time-stamped observations suitable for time-series modelling, forecasting, anomaly detection and studies of airborne stressors in aquaculture facilities.

Parameters and units

Parameter	Unit	Relevance in trout culture
Temperature	°C	Influences metabolic rate, feed conversion and dissolved-oxygen levels.
Relative humidity	% RH	High RH accelerates mould growth; low RH increases evaporation.
CO₂	ppm	Head-space CO₂ equilibrates with water; sustained excess slows growth.
VOC	ppb	Proxy for disinfectant off-gassing and human activity; ventilation indicator.
PM₂.₅	µg m⁻³	Fine particles can load bio-filters and irritate gill tissue.
PM₁₀	µg m⁻³	Coarser dust from feed handling and maintenance.


	All values are recorded in SI units; timestamps use ISO-8601 in Coordinated Universal Time (UTC). Reuse potential Benchmark short-horizon IEQ forecasting (ARIMA, LSTM, transformer models). Develop anomaly detectors for hatchery monitoring dashboards. Correlate airborne conditions with fish-health metrics in future multi-modal studies. Validate low-cost sensor stability in high-humidity aquaculture environments. How to cite If you use the AQUAIR dataset, please also cite our paper: Sabiri, Y., Houmaidi, W., El Maadi, O., & Chtouki, Y. (2025). AQUAIR: A High-Resolution Indoor Environmental Quality Dataset for Smart Aquaculture Monitoring. arXiv:2509.24069. AQUAIR: A High-Resolution I… BibTeX: @misc{sabiri2025aquairhighresolutionindoorenvironmental, title={AQUAIR: A High-Resolution Indoor Environmental Quality Dataset for Smart Aquaculture Monitoring}, author={Youssef Sabiri and Walid Houmaidi and Ouail El Maadi and Yousra Chtouki}, year={2025}, eprint={2509.24069}, archivePrefix={arXiv}, primaryClass={cs.LG}, url={arxiv.org, } Licence Creative Commons Attribution 4.0 International (CC-BY-4.0).

All values are recorded in SI units; timestamps use ISO-8601 in Coordinated Universal Time (UTC).

Reuse potential

Benchmark short-horizon IEQ forecasting (ARIMA, LSTM, transformer models).
Develop anomaly detectors for hatchery monitoring dashboards.
Correlate airborne conditions with fish-health metrics in future multi-modal studies.
Validate low-cost sensor stability in high-humidity aquaculture environments.

How to cite

If you use the AQUAIR dataset, please also cite our paper:

Sabiri, Y., Houmaidi, W., El Maadi, O., & Chtouki, Y. (2025). AQUAIR: A High-Resolution Indoor Environmental Quality Dataset for Smart Aquaculture Monitoring. arXiv:2509.24069. AQUAIR: A High-Resolution I…

BibTeX:

@misc{sabiri2025aquairhighresolutionindoorenvironmental,
      title={AQUAIR: A High-Resolution Indoor Environmental Quality Dataset for Smart Aquaculture Monitoring}, 
      author={Youssef Sabiri and Walid Houmaidi and Ouail El Maadi and Yousra Chtouki},
      year={2025},
      eprint={2509.24069},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={arxiv.org, 
}

Licence
Creative Commons Attribution 4.0 International (CC-BY-4.0).

Visit

figshare.com

Licenses

CC BY 4.0