Smart City Feasibility Study using IoT and Machine Learning

Authors

  • Rowedah Hussien Ali Highway and Airport Department, University of Diayla, Diayla, Iraq
  • Suha Falih Mahdi Alazawy Highway and Airport Department, University of Diayla, Diayla, Iraq
  • Ali Mustafa Civil Engineering Department, University of Diayla, Diayla, Iraq
  • Kadhim Raheim Erzaij Civil Engineering Department, University of Baghdad, Baghdad, Iraq
Volume: 14 | Issue: 5 | Pages: 17494-17500 | October 2024 | https://doi.org/10.48084/etasr.8714

Abstract

Complexity and resource constraints accompany urban growth. According to UN figures, cities currently use 75% of the global energy, with 70% of the greenhouse gas emissions being mostly generated from transportation and residence buildings. Furthermore, city residents are susceptible to the consequences of climate change. Therefore, a feasibility study for the possibility of implementing a smart city was conducted in this paper. The results show that the current situation of the cities is/renders them far from being smart, while the environmental aspect needs to be controlled by the use of IoT sensors. The utilized Hyperd algorithm gave highly accurate prediction results.

Keywords:

smart city, IoT, AI, gradient boosting, linear regression, feasibility

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References

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How to Cite

[1]
Ali, R.H., Alazawy, S.F.M., Mustafa, A. and Erzaij, K.R. 2024. Smart City Feasibility Study using IoT and Machine Learning. Engineering, Technology & Applied Science Research. 14, 5 (Oct. 2024), 17494–17500. DOI:https://doi.org/10.48084/etasr.8714.

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