Smart City Feasibility Study using IoT and Machine Learning
Received: 13 August 2024 | Revised: 22 August 2024 | Accepted: 4 September 2024 | Online: 15 September 2024
Corresponding author: Rowedah Hussien Ali
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, feasibilityDownloads
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Copyright (c) 2024 Rowedah Hussien, Suha Falih Mahdi Alazawy, Ali Mustafa, Kadhim Raheim Erzaij
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