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IoT-enabled smart city governance using AI-based data analytics
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Abstract
Integrating Internet of Things (IoT) devices with Artificial Intelligence (AI)-based data analytics transform governance models in smart cities, enabling real-time data-driven decision-making for enhanced urban management. This paper explores the role of IoT-enabled systems in collecting extensive data from urban infrastructure, including traffic, energy usage, waste management, and environmental monitoring. Leveraging AI, these systems analyze data to generate actionable insights, optimize resource allocation, and predict future urban challenges. The research identifies key applications, such as adaptive traffic control, efficient energy distribution, and predictive waste management, highlighting how these innovations lead to improved service delivery, reduced costs, and heightened quality of life for citizens. However, challenges such as data privacy concerns, the high cost of implementation, and the need for advanced infrastructure are also addressed. The study discusses future trends, emphasizing the potential for 5G integration and more sophisticated AI algorithms to advance smart city governance further.
Keywords
Internet of thing Smart cities Artificial intelligence Data analytics Governance Real-time trackingReferences (19)
- [1] Bellini, P., Nesi, P., & Pantaleo, G. (2022). IoT-enabled smart cities: A review of concepts, frameworks and key technologies. Applied sciences, 12(3), 1607. https://doi.org/10.3390/app12031607
- [2] Rehan, H. (2023). Internet of things (IoT) in smart cities: Enhancing urban living through technology. Journal of engineering and technology, 5(1), 1–16. https://B2n.ir/q69721
- [3] Zikria, Y. Bin, Ali, R., Afzal, M. K., & Kim, S. W. (2021). Next-generation internet of things (IoT): Opportunities, challenges, and solutions. Sensors, 21(4), 1174. https://doi.org/10.3390/s21041174
- [4] Shafik, W., Matinkhah, S. M., & Ghasemzadeh, M. (2020). Internet of things-based energy management, challenges, and solutions in smart cities. Journal of communications technology, electronics and computer science, 27, 1–11. http://dx.doi.org/10.22385/jctecs.v27i0.302
- [5] Mohapatra, H. (2021). Socio-technical challenges in the implementation of smart city. International conference on innovation and intelligence for informatics, computing, and technologies (3ICT) (pp. 57–62). IEEE. https://ieeexplore.ieee.org/abstract/document/9581905/
- [6] Van Hoang, T. (2024). Impact of integrated artificial intelligence and internet of things technologies on smart city transformation. Journal of technical education science, 19(Special Issue 01), 64–73. https://doi.org/10.54644/jte.2024.1532
- [7] Taherdoost, H. (2025). IoT-enabled sustainable urban growth management. In Internet of things and big data analytics for a green environment (pp. 1–22). Chapman and Hall/CRC. https://doi.org/10.1201/9781032656830
- [8] Mishra, P., & Singh, G. (2023). Energy management systems in sustainable smart cities based on the internet of energy: A technical review. Energies, 16(19), 6903. https://doi.org/10.3390/en16196903
- [9] Damaševičius, R., Bacanin, N., & Misra, S. (2023). From sensors to safety: Internet of emergency services (IoES) for emergency response and disaster management. Journal of sensor and actuator networks, 12(3), 41. https://doi.org/10.3390/jsan12030041
- [10] Sharma, A., Singh, K. J., Kapoor, D. S., Thakur, K., & Mahajan, S. (2024). The role of IoT in environmental sustainability: Advancements and applications for smart cities. In Mobile crowdsensing and remote sensing in smart cities (pp. 21–39). Springer. https://doi.org/10.1007/978-3-031-72732-0_2
- [11] Mhlanga, D., & Shao, D. (2025). AI-optimized urban resource management for sustainable smart cities. In Financial inclusion and sustainable development in sub-saharan Africa (pp. 96–116). Routledge. https://B2n.ir/r67035
- [12] illegas-Ch, W., García-Ortiz, J., & Sánchez-Viteri, S. (2024). Corrections to “toward intelligent monitoring in IoT: AI applications for real-time analysis and prediction”. IEEE access, 12, 157299-157299. https://doi.org/10.1109/ACCESS.2024.3376707
- [13] Narne, S., Adedoja, T., Mohan, M., & Ayyalasomayajula, T. (2024). AI-driven decision support systems in management: Enhancing strategic planning and execution. International journal on recent and innovation trends in computing and communication, 12(1), 268–276. https://www.ijritcc.org/index.php/ijritcc
- [14] Samaei, S. R. (2023). A comprehensive algorithm for AI-driven transportation improvements in urban areas 13th international engineering conference on advanced research in science and technology (pp. 1-17), Brussels, Belgium. Civilica. (In Persion). https://civilica. com/doc/1930041
- [15] Ikwuanusi, U. F., Adepoju, P. A., & Odionu, C. S. (2023). Advancing ethical AI practices to solve data privacy issues in library systems. International journal of multidisciplinary research updates, 6(1), 33–44. https://doi.org/10.53430/ijmru.2023.6.1.0063
- [16] Ouallane, A. A., Bahnasse, A., Bakali, A., & Talea, M. (2022). Overview of road traffic management solutions based on IoT and AI. Procedia computer science, 198, 518–523. https://doi.org/10.1016/j.procs.2021.12.279
- [17] Al-Raeei, M. (2025). The smart future for sustainable development: Artificial intelligence solutions for sustainable urbanization. Sustainable development, 33(1), 508–517. https://doi.org/10.1002/sd.3131
- [18] Alahi, M. E. E., Sukkuea, A., Tina, F. W., Nag, A., Kurdthongmee, W., Suwannarat, K., & Mukhopadhyay, S. C. (2023). Integration of IoT-enabled technologies and artificial intelligence (AI) for smart city scenario: Recent advancements and future trends. Sensors, 23(11), 5206. https://doi.org/10.3390/s23115206
- [19] Prieto-Avalos, G., Cruz-Ramos, N. A., Alor-Hernandez, G., Sánchez-Cervantes, J. L., Rodriguez-Mazahua, L., & Guarneros-Nolasco, L. R. (2022). Wearable devices for physical monitoring of heart: A review. Biosensors, 12(5), 292. https://doi.org/10.3390/bios12050292
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- Published 2024-03-15
- Issue Vol. 1 No. 1 (2024): Metaversalize
- Section Articles
- Document Type Research Article
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How to Cite
Das, J. . (2024). IoT-enabled smart city governance using AI-based data analytics. Metaversalize, 1(1), 1-15. https://doi.org/10.22105/metaverse.v1i2.54
