Open Access
Issue
EPJ Web Conf.
Volume 379, 2026
2nd International Conference on Sustainable Materials, Methodologies, Technologies & Applications in Engineering (ICS2MT-2026)
Article Number 05003
Number of page(s) 10
Section Energy, Environment, Artificial Intelligence and Sustainable Development
DOI https://doi.org/10.1051/epjconf/202637905003
Published online 03 August 2026
  1. T.R. Oke, G. Mills, A. Christen, J.A. Voogt, Cities and global climate change, in Urban Climates (Cambridge University Press, Cambridge, 2017), pp. 360–384. https://doi.org/10.1017/9781139016476 [Google Scholar]
  2. Spectrum Technologies Inc., WatchDog® 3000 Series Weather Stations Product Manual (Spectrum Technologies, Aurora, IL, USA, 2022) [Google Scholar]
  3. A.N. Cabrera, A. Droste, B.G. Heusinkveld, G.-J. Steeneveld, The potential of a smartphone as an urban weather station — An exploratory analysis. Front. Environ. Sci. 9, 673937 (2021). https://doi.org/10.3389/fenvs.2021.673937 [Google Scholar]
  4. S. Ganesan, C. P. Lean, L. Chen, K. F. Yuan, N. P. Kiat, M. R. B. Khan, IoT-enabled smart weather stations: Innovations, challenges, and future directions. Malays. J. Sci. Adv. Technol. 4, 180–190 (2024). [Google Scholar]
  5. A. Chokhachian, K.K.-L. Lau, K. Perini, T. Auer, Sensing transient outdoor comfort: A georeferenced method to monitor and map microclimate. J. Build. Eng. 20, 94–104 (2018). https://doi.org/10.1016/j.jobe.2018.07.003 [Google Scholar]
  6. K. Lau, Y. Shi, E. Ng, Dynamic response of pedestrian thermal comfort under transient outdoor conditions. Int. J. Biometeorol. 63, 979–989 (2019). https://doi.org/10.1007/s00484-019-01712-2 [Google Scholar]
  7. J. Geletić, M. Lehnert, S. Savić, D. Milošević, Modelled spatiotemporal variability of outdoor thermal comfort in local climate zones of the city of Brno, Czech Republic. Sci. Total Environ. 624, 385–395 (2018). https://doi.org/10.1016/j.scitotenv.2017.12.076 [Google Scholar]
  8. M. Elnabawi, N. Hamza, S. Dudek, Thermal perception of outdoor urban spaces in the hot arid region of Cairo. Sustain. Cities Soc. 22, 136–145 (2016). https://doi.org/10.1016/j.scs.2016.02.005 [Google Scholar]
  9. L. Lovén, V. Karsisto, H. Järvinen, M. Sillanpää, T. Leppänen, E. Peltonen, et al., Mobile road weather sensor calibration by sensor fusion and linear mixed models. PLoS ONE 14, e0211702 (2019). https://doi.org/10.1371/journal.pone.0211702 [Google Scholar]
  10. L. Chapman, S. Bell, S. Randall, Can crowdsourcing increase the durability of an urban meteorological network? Urban Clim. 49, 101542 (2023). https://doi.org/10.1016/j.uclim.2023.101542 [Google Scholar]
  11. F. Barbano, E. Brattich, C. Cintolesi, A.G. Nizamani, S. Di Sabatino, M. Milelli, et al., Performance evaluation of MeteoTracker mobile sensor for outdoor applications. Atmos. Meas. Tech. 17, 3255–3278 (2024). https://doi.org/10.5194/amt-17-3255-2024 [Google Scholar]

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