Smart City Gnosys

Smart city article details

Title	Characterizing Smart Cities Based On Artificial Intelligence
ID_Doc	13842
Authors	Hammoumi, L; Maanan, M; Rhinane, H
Year	2024
Published	SMART CITIES, 7, 3
DOI	http://dx.doi.org/10.3390/smartcities7030056
Abstract	Cities worldwide are attempting to be labelled as smart, but truly classifying as such remains a great challenge. This study aims to use artificial intelligence (AI) to classify the performance of smart cities and identify the factors linked to their smartness. Based on residents' perceptions of urban structures and technological applications, this study included 200 cities globally. For 147 cities, we gathered the perceptions of 120 residents per city through a survey of 39 questions covering two main pillars: 'Structures', referring to the existing infrastructure of the city, and the 'Technology' pillar that describes the technological provisions and services available to the inhabitants. These pillars were evaluated across five key areas: health and safety, mobility, activities, opportunities, and governance. For the remaining 53 cities, scores were derived by analyzing pertinent data collected from various online resources. Multiple machine learning algorithms, including Random Forest, Artificial Neural Network, Support Vector Machine, and Gradient Boost, were tested and compared in order to select the best one. The results showed that Random Forest and the Artificial Neural Network are the best trained models that achieved the highest levels of accuracy. This study provides a robust framework for using machine learning to identify and assess smart cities, offering valuable insights for future research and urban planning.
Author Keywords	cities; smart city indicators; machine learning; artificial intelligence; classification

Similar Articles

Id	Similarity	Authors	Title	Published
35869	0.973	Hammoumi L.; Rhinane H.	Machine Learning (Ai) For Identifying Smart Cities	International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 48, 4/W9-2024 (2024)
16010	0.908	Yigitcanlar T.; Desouza K.C.; Butler L.; Roozkhosh F.	Contributions And Risks Of Artificial Intelligence (Ai) In Building Smarter Cities: Insights From A Systematic Review Of The Literature	Energies, 13, 6 (2020)
10423	0.907	Gupta A.; Gupta S.; Memoria M.; Kumar R.; Kumar S.; Singh D.; Tyagi S.; Ansari N.	Artificial Intelligence And Smart Cities: A Bibliometric Analysis	2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022 (2022)
11943	0.906	Ravisankar A.; Ibraheem I.K.; Raha S.; Sakthi T.; Ashok J.; Tonk A.	Bibliometric Analysis Of Ai Research In Sustainable Smart Cities	Sustainable Development Goals: Technologies and Opportunities (2024)
28087	0.902	Alkhereibi A.H.; Abulibdeh R.; Abulibdeh A.	Global Smart Cities Classification Using A Machine Learning Approach To Evaluating Livability, Technology, And Sustainability Performance Across Key Urban Indices	Journal of Cleaner Production, 503 (2025)
10505	0.9	Haque A.K.M.B.; Nur A.; Chowdhury R.N.	Artificial Intelligence In Smart City-Systematic Literature Review Of Current Knowledge And Future Research Avenues	Enabling Technologies for Effective Planning and Management in Sustainable Smart Cities (2023)
46981	0.898	Adi Bhaskara J.; Nurmandi A.	Role Of Artificial Intelligence In The Smart City: A Bibliometric Review	Communications in Computer and Information Science, 1655 CCIS (2022)
10503	0.896	Rjab A.B.; Mellouli S.	Artificial Intelligence In Smart Cities: Systematic Literature Network Analysis	ACM International Conference Proceeding Series, Part F148155 (2019)
17741	0.896	Barbierato E.; Gatti A.	Decoding Urban Intelligence: Clustering And Feature Importance In Smart Cities	Future Internet, 16, 10 (2024)
13108	0.896	Karger E.; Rothweiler A.; Brée T.; Ahlemann F.	Building The Smart City Of Tomorrow: A Bibliometric Analysis Of Artificial Intelligence In Urbanization	Urban Science, 9, 4 (2025)