Smart City Gnosys
Smart city article details
| Title | Renovate Urban Outlook With Ai: Renewable Planning For Smarter Cities |
|---|---|
| ID_Doc | 45073 |
| Authors | Ashreetha B.; Lavanya L.; Kumar K.V.; Lakshmi K.D.; Tharakeswar K. |
| Year | 2025 |
| Published | Proceedings of the International Conference on Intelligent Computing and Control Systems, ICICCS 2025 |
| DOI | http://dx.doi.org/10.1109/ICICCS65191.2025.10984869 |
| Abstract | This paper discusses how artificial intelligence and data analytics can be applied to city planning with instruments such as healthcare facilities and education access enhancements, regulation of the density of population, economic growth, intelligent city strategies, and optimization of transport. Traditional methods of urban planning are not highly responsive to dynamic changes and turbulence in cities. Over these, data needs to be analyzed through means such as the algorithms of Random Forest and Gradient Descent so that the approach to decision-making comes to be data-driven in an attempt towards effective sustainable city development. True, the gradient descent algorithm boosts the accuracy of the model but mistakes reduce with its increased predictive power. On the other hand, Random Forest helps categorize and predict trends for the sectors mentioned, for example, people's distribution, transporting congestion, and resource distribution. We analyze several forms of urban planning through simulation and real-time data analysis using metrics of performance such as accuracy, R-squared scores, and Mean Squared Error (MSE). Improved model accuracy, meaningful visualization, and actionable insights for stakeholders ensure all the potential offered by AI for more effective and sustainable management of urban areas. Considering the limitations due to data and some limitations of assumed models, this body of research has laid a sound foundation for adaptive, informed urban planning in a host of domains. [1] © 2025 IEEE. |
| Author Keywords | Artificial Intelligence (AI); Decision making; Environment Data; Geospatial Analysis; Gradient descent; Infrastructure planning; IoT Sensors; Machine learning (ML); planning; Population Density; Random Forest; Smart cities; Traffic; Urban areas |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
31668  | 0.893 | Baidrakhmanova M.; Karabayev G.; Mamedov S. | Innovative Approaches To Sustainable Urban Planning: Analysing Current Trends | Journal of Studies in Science and Engineering, 5, 1 (2025) |
| 46598 | 0.891 | Bhuvanya R.; Mariammal G.; Sivakumar K.; Ganga M.; Anish T.P.; Swetha S.; Siva Subramanian R. | Revolutionizing Urban Planning: The Role Of Ai And Predictive Analytics In Sustainable City Development | Leveraging Urban Computing for Sustainable Urban Development (2025) |
| 56481 | 0.89 | Cina E.; Elbasi E.; Elmazi G.; AlArnaout Z. | The Role Of Ai In Predictive Modelling For Sustainable Urban Development: Challenges And Opportunities | Sustainability (Switzerland), 17, 11 (2025) |
| 7228 | 0.889 | Son T.H.; Weedon Z.; Yigitcanlar T.; Sanchez T.; Corchado J.M.; Mehmood R. | Algorithmic Urban Planning For Smart And Sustainable Development: Systematic Review Of The Literature | Sustainable Cities and Society, 94 (2023) |
| 31592 | 0.887 | Balushi N.A. | Innovating Economic Models For Smart Green Cities Through Artificial Intelligence Techniques | International Conference for Artificial Intelligence: Applications, Innovation and Ethics, AI2E 2025 (2025) |
| 27848 | 0.882 | Huang J.; Bibri S.E.; Keel P. | Generative Spatial Artificial Intelligence For Sustainable Smart Cities: A Pioneering Large Flow Model For Urban Digital Twin | Environmental Science and Ecotechnology , 24 (2025) |
| 29697 | 0.876 | Zhu W.; He W.; Li Q. | Hybrid Ai And Big Data Solutions For Dynamic Urban Planning And Smart City Optimization | IEEE Access, 12 (2024) |
| 7408 | 0.875 | Mirindi D.; Sinkhonde D.; Mirindi F. | An Advance Review Of Urban-Ai And Ethical Considerations | Urban-AI 2024 - Proceedings of the 2nd ACM SIGSPATIAL International Workshop on Advances in Urban-AI (2024) |
| 5173 | 0.871 | Zheng Y.; Hao Q.; Wang J.; Gao C.; Chen J.; Jin D.; Li Y. | A Survey Of Machine Learning For Urban Decision Making: Applications In Planning, Transportation, And Healthcare | ACM Computing Surveys, 57, 4 (2024) |
| 25477 | 0.869 | Alhazzaa H.A.; Aljarboa F.I.; Albelaihed J.A.; Alqahtani J.A.; Alhazzani R.S.; Aljameel S.S.; Alqahtani D.A. | Exploring Ai Applications For Optimal Business Location Selection In Smart Cities: A Literature Review | 2025 2nd International Conference on Advanced Innovations in Smart Cities, ICAISC 2025 (2025) |