Smart City Gnosys
Smart city article details
| Title | Unlocking The Potential Of Time Series Iot (Internet Of Things) Data: The Transformative Role Of Ai And Machine Learning In Smart Cities |
|---|---|
| ID_Doc | 59663 |
| Authors | Singh D.; Singh V.; Singh S.A. |
| Year | 2025 |
| Published | 2025 International Conference on Cognitive Computing in Engineering, Communications, Sciences and Biomedical Health Informatics, IC3ECSBHI 2025 |
| DOI | http://dx.doi.org/10.1109/IC3ECSBHI63591.2025.10990375 |
| Abstract | The integration of the Internet of Things (IoT) within urban environments is reshaping how cities operate, yet the vast data generated often remains underutilized due to significant barriers to effective data management. Despite the widespread use of IoT devices, more than 75 percent of businesses do not follow a data-driven methodology. This is mainly due to obstacles such as the complexity of data integration, a lack of standardization, and insufficient technical skills. This paper examines the obstacles and highlights the transforming impact of Artificial Intelligence (AI) and Machine Learning (ML) in converting IoT data into actionable insights that improve decision-making processes across diverse industries in smart cities. By addressing the complexities of data integration, AI and machine learning (ML) offer scalable solutions enabling real-time analytics, predictive modeling, and effi- cient resource management. This paper discusses specific applications of AI and ML in different industries, such as manufacturing, healthcare, energy, and agriculture. For example, AI-powered predictive maintenance in manufacturing helps reduce maintenance costs by up to 25 percent, while intelligent energy management in buildings can optimize energy consumption, enabling reduced costs by up to 30percent. In healthcare, AI-powered monitoring improves patient outcomes, and in agriculture, data-driven precision techniques can increase agricultural yields by 15percent. These figures indicate how important the role of Machine Learning is expected to be across verticals of the industry in the next few decades. The IoT trends indicate that implementing edge an-alytics further enhances the capabilities and efficiency of AI and ML. It allows for quick decision-making at the main source of data, therefore reducing latency and bandwidth demands. This paper is concluded by discussing the importance of AI and ML in unlocking the full potential of IoT investments, driving efficiencies, reducing costs, and improving the quality of urban living. Using these latest technologies the future of smart cities can be further adaptive, efficient and sustainable. © 2025 IEEE. |
| Author Keywords |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
35091  | 0.907 | Ahmad M.; Mumtaz R.; Khan M.A. | Leveraging Iot And Machine Learning For Smart Urban Planning | Leveraging IoT and Machine Learning for Smart Urban Planning (2025) |
| 28691 | 0.906 | Goel N.; Yadav R.K. | Handbook Of Research On Machine Learning-Enabled Iot For Smart Applications Across Industries | Handbook of Research on Machine Learning-Enabled IoT for Smart Applications Across Industries (2023) |
| 36075 | 0.899 | Bzai J.; Alam F.; Dhafer A.; Bojović M.; Altowaijri S.M.; Niazi I.K.; Mehmood R. | Machine Learning-Enabled Internet Of Things (Iot): Data, Applications, And Industry Perspective | Electronics (Switzerland), 11, 17 (2022) |
| 49921 | 0.895 | Ullah A.; Anwar S.M.; Li J.; Nadeem L.; Mahmood T.; Rehman A.; Saba T. | Smart Cities: The Role Of Internet Of Things And Machine Learning In Realizing A Data-Centric Smart Environment | Complex and Intelligent Systems, 10, 1 (2024) |
| 31974 | 0.893 | Gupta S.; Kumar V. | Integrating Deep Learning, Machine Learning, Ai, Iot And Data Science For Future Innovations | Proceedings - 2024 4th International Conference on Soft Computing for Security Applications, ICSCSA 2024 (2024) |
| 6906 | 0.892 | Gupta S.K.; Singh N. | Ai And Iot- Enabled Technologies And Applications For Smart City | Artificial Intelligence in Cyber-Physical Systems: Principles and Applications (2023) |
| 9370 | 0.889 | Haouam K.-D. | Analysis Of The Role Of Machine Learning In The Internet Of Things (Iot) | Colloquium in Information Science and Technology, CIST (2023) |
| 32035 | 0.889 | Mrabet M.; Sliti M. | Integrating Machine Learning For The Sustainable Development Of Smart Cities | Frontiers in Sustainable Cities, 6 (2024) |
| 22924 | 0.888 | Naaz S.; Parveen S.; Khan I.R.; Tanweer S. | Empowering Smart Cities Through Iot And Ai: Enhancing Decision-Making For A Data-Driven Future | ICDT 2025 - 3rd International Conference on Disruptive Technologies (2025) |
| 34050 | 0.888 | Sahana D.S.; Vidya J.; Madhurya J.A.; Nida K.G. | Iot-Driven Machine Learning Solutions For Smarter Urban Living | Springer Tracts on Transportation and Traffic, 22 (2025) |