Skip to main content
Have a personal or library account? Click to login
Advancing Indoor Air Quality Management Through Predictive Feedforward Control - A Comparative Analysis Cover

Advancing Indoor Air Quality Management Through Predictive Feedforward Control - A Comparative Analysis

Open Access
|Sep 2026

References

  1. World Health Organization. WHO guidelines for indoor air quality: selected pollutants; WHO Regional Office for Europe: Copenhagen, Denmark, 2010.
  2. Kalaiarasan, G.; Kumar, P.; Tomson, M.; Zavala-Reyes, J.C.; Porter, A.E.; Young, G.; Sephton, M.A.; Abubakar-Waziri, H.; Pain, C.C.; Adcock, I.M.; et al. Particle number size distribution in three different microenvironments of London. Atmosphere 2024, 15 (1), 45.
  3. https://doi.org/10.3390/atmos15010045
  4. Vijay, P.; Anand, A.; Singh, N.; Schikowski, T.; Phuleria, H.C. Examining the spatial and temporal variations in the indoor gaseous, PM2.5, BC concentrations in urban homes in India. Atmos. Environ. 2024, 319, 120287.
  5. https://doi.org/10.1016/j.atmosenv.2023.120287
  6. Wei, W.; Ramalho, O.; Derbez, M.; Riberon, J.; Kirchner, S.; Mandin, C. Applicability and relevance of six indoor air quality indexes. Build. Environ. 2016, 109, 42–49.
  7. https://doi.org/10.1016/j.buildenv.2016.09.008
  8. Vasile, V.; Iordache, V.; Radu, V.M.; Dragomir, C.S. The relationship between mechanical ventilation, indoor air quality classes, and energy classes in a Romanian context. Atmosphere 2024, 15, 444.
  9. Zhao, L.; Liu, J.; Ren, J. Impact of various ventilation modes on IAQ and energy consumption in Chinese dwellings: First long-term monitoring study in Tianjin, China. Build. Environ. 2018, 143, 99–106.
  10. https://doi.org/10.1016/j.buildenv.2018.06.057
  11. Ganesh, H.S.; Fritz, H.E.; Edgar, T.F.; Novoselac, A.; Baldea, M. A model-based dynamic optimization strategy for control of indoor air pollutants. Energy Build. 2019, 195, 168–179.
  12. https://doi.org/10.1016/j.enbuild.2019.04.022
  13. Ministry of Development, Public Works and Administration. Energy Performance Calculation Methodology of Buildings, Code MC001-2022; MDLPA: Bucharest, Romania, 2022.
  14. Ministry of Development, Public Works and Administration. Regulation for the Design, Execution and Operation of Ventilation and Air Conditioning Installations, Indicativ I5-2022; MDLPA: Bucharest, Romania, 2022.
  15. Kaggle. 1-year indoor environmental dataset (office).
  16. Available online: https://www.kaggle.com (accessed on 20 March 2026).
  17. IBM. What are ARIMA models?
  18. Available online: https://www.ibm.com/topics/arima-models (accessed on 20 March 2026).
  19. IBM. What is random forest?
  20. Available online: https://www.ibm.com/topics/random-forest (accessed on 20 March 2026).
  21. Kallio, J.; Tervonen, J.; Räsänen, P.; Mäkynen, R.; Koivusaari, J.; Peltola, J. Forecasting office indoor CO2 concentration using machine learning with a one-year dataset. Build. Environ. 2021, 187, 107409.
  22. https://doi.org/10.1016/j.buildenv.2020.107409
  23. IBM. What is long short-term memory (LSTM)?
  24. Available online: https://www.ibm.com/topics/lstm (accessed on 20 March 2026).
  25. Gabriel, M.; Auer, T. LSTM Deep Learning Models for Virtual Sensing of Indoor Air Pollutants: A Feasible Alternative to Physical Sensors. Buildings 2023, 13, 1684.
  26. https://doi.org/10.3390/buildings13071684
  27. Tagliabue, L.C.; Re Cecconi, F.; Rinaldi, S.; Ciribini, A.L.C. Data driven indoor air quality prediction in educational facilities based on IoT network. Energy Build. 2021, 236, 110782.
  28. https://doi.org/10.1016/j.enbuild.2021.110782
  29. Dai, H.; Wu, N.; Dong, Z.; Ren, J.; Gao, Y.; Zhao, B. Comparison and evaluation of machine learning models for predicting indoor PM2.5 concentrations on a large spatiotemporal scale. Build. Simul. 2025, 18, 1453–1466.
  30. https://doi.org/10.1007/s12273-025-1276-0
  31. Duan, J.; Gong, Y.; Luo, J.; Zhao, Z. Air-quality prediction based on the ARIMA-CNN-LSTM combination model optimized by dung beetle optimizer. Sci. Rep. 2023, 13, 12127.
  32. https://doi.org/10.1038/s41598-023-36620-4
DOI: https://doi.org/10.2478/mmce-2026-0001 | Journal eISSN: 2784-1391 (formerly 2066-6934) | Journal ISSN: 2066-6934
Language: English
Page range: 1 - 14
Published on: Sep 11, 2026
Published by: Technical University of Civil Engineering of Bucharest
In partnership with: Paradigm Publishing Services
Publication frequency: Volume open

© 2026 Valentin Mihai Radu, published by Technical University of Civil Engineering of Bucharest
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.