AQUAIR Dataset

<br><br><b>Dataset overview:</b><br>This repository contains the <b>AQUAIR Dataset</b>, a high-resolution log of indoor-environment quality (IEQ) gathered in a trout (<i>Oncorhynchus mykiss</i>) hatchery room at <b>Amghass, Azrou, Morocco</b>. 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 <b>5 minutes</b> between <b>14 October 2024 and 09 January 2025</b>. The data are provided as two comma-separated files:<br>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 <b>23 856 time-stamped observations</b> suitable for time-series modelling, forecasting, anomaly detection and studies of airborne stressors in aquaculture facilities.<br>Parameters and unitsParameterUnitRelevance in trout cultureTemperature°CInfluences metabolic rate, feed conversion and dissolved-oxygen levels.Relative humidity% RHHigh RH accelerates mould growth; low RH increases evaporation.CO₂ppmHead-space CO₂ equilibrates with water; sustained excess slows growth.VOCppbProxy for disinfectant off-gassing and human activity; ventilation indicator.PM₂.₅µg m⁻³Fine particles can load bio-filters and irritate gill tissue.PM₁₀µg m⁻³Coarser dust from feed handling and maintenance.<br>All values are recorded in SI units; timestamps use ISO-8601 in Coordinated Universal Time (UTC).<br>Reuse potentialBenchmark 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.<b>How to cite</b>If you use the AQUAIR dataset, please also cite our paper:Sabiri, Y., Houmaidi, W., El Maadi, O., &amp; Chtouki, Y. (2025). AQUAIR: A High-Resolution Indoor Environmental Quality Dataset for Smart Aquaculture Monitoring. arXiv:2509.24069. https://arxiv.org/abs/2509.24069<b>BibTeX:</b><pre><pre>@misc{sabiri2025aquairhighresolutionindoorenvironmental,<br> title={AQUAIR: A High-Resolution Indoor Environmental Quality Dataset for Smart Aquaculture Monitoring}, <br> author={Youssef Sabiri and Walid Houmaidi and Ouail El Maadi and Yousra Chtouki},<br> year={2025},<br> eprint={2509.24069},<br> archivePrefix={arXiv},<br> primaryClass={cs.LG},<br> url={https://arxiv.org/abs/2509.24069}, <br>}<br></pre></pre><br><br><b>Licence</b><br>Creative Commons Attribution 4.0 International (CC-BY-4.0).<br><br><br>