Smart City Gnosys
Smart city article details
| Title | Sustainable Traffic Management For Smart Cities Using Internet-Of-Things-Oriented Intelligent Transportation Systems (Its): Challenges And Recommendations |
|---|---|
| ID_Doc | 54070 |
| Authors | Musa A.A.; Malami S.I.; Alanazi F.; Ounaies W.; Alshammari M.; Haruna S.I. |
| Year | 2023 |
| Published | Sustainability (Switzerland), 15, 13 |
| DOI | http://dx.doi.org/10.3390/su15139859 |
| Abstract | The emergence of smart cities has addressed many critical challenges associated with conventional urbanization worldwide. However, sustainable traffic management in smart cities has received less attention from researchers due to its complex and heterogeneous nature, which directly affects smart cities’ transportation systems. The study aimed at addressing traffic-related issues in smart cities by focusing on establishing a sustainable framework based on the Internet of Things (IoT) and Intelligent Transportation System (ITS) applications. To sustain the management of traffic in smart cities, which is composed of a hybridized stream of human-driven vehicles (HDV) and connected automated vehicles (CAV), a dual approach was employed by considering traffic as either modeling- and analysis-based, or/and the decision-making issues of previous research works. Moreover, the two techniques utilized real-time traffic data, and collected vehicle and road users’ information using AI sensors and ITS-based devices. These data can be processed and transmitted using machine learning algorithms and cloud computing for traffic management, traffic decision-making policies, and documentation for future use. The proposed framework suggests that deploying such systems in smart cities’ transportation could play a significant role in predicting traffic outcomes, traffic forecasting, traffic decongestion, minimizing road users’ lost hours, suggesting alternative routes, and simplifying urban transportation activities for urban dwellers. Also, the proposed integrated framework adopted can address issues related to pollution in smart cities by promoting public transportation and advocating low-carbon emission zones. By implementing these solutions, smart cities can achieve sustainable traffic management and reduce their carbon footprint, making them livable and environmentally friendly. © 2023 by the authors. |
| Author Keywords | artificial intelligence; Intelligent Transportation System; Internet of Things; smart cities |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
32238  | 0.928 | Jain V.; Mitra A. | Integrative Hybrid Information Systems For Enhanced Traffic Maintenance And Control In Bangalore: A Synchronized Approach | Hybrid Information Systems: Non-Linear Optimization Strategies with Artificial Intelligence (2024) |
| 19433 | 0.922 | Al-Jawahry H.M. | Developing An Intelligent Traffic Management System For Smart Cities Through The Integration Of Machine Learning And Iot Technologies | Lecture Notes in Networks and Systems, 1306 LNNS (2025) |
| 25640 | 0.917 | Joshi S.R.; Rakesh U.; Sripad S. | Exploring Sustainable Techniques For Traffic Management In Urban Environments | 2024 International Conference on Recent Innovation in Smart and Sustainable Technology, ICRISST 2024 (2024) |
| 54093 | 0.916 | Chandra S. | Sustainable Urban Mobility And Smart Traffic Management: Balancing Optimization With Environmental Sustainability Goals | Machine Learning and Robotics in Urban Planning and Management (2025) |
| 24036 | 0.911 | Kabir Md.H.; Islam Md.S. | Enhancing Traffic Flow And Reducing Congestion: A Smart City Approach With An Iot-Based Intelligent Traffic Management System | 2024 International Conference on Innovations in Science, Engineering and Technology: Innovative Technologies for Global Solutions, ICISET 2024 (2024) |
| 58162 | 0.911 | Tao X.; Cheng L.; Zhang R.; Chan W.K.; Chao H.; Qin J. | Towards Green Innovation In Smart Cities: Leveraging Traffic Flow Prediction With Machine Learning Algorithms For Sustainable Transportation Systems | Sustainability (Switzerland), 16, 1 (2024) |
| 56572 | 0.911 | Puzio E.; Drożdż W.; Kolon M. | The Role Of Intelligent Transport Systems And Smart Technologies In Urban Traffic Management In Polish Smart Cities | Energies, 18, 10 (2025) |
| 38883 | 0.911 | Kumar A.; Batra N.; Mudgal A.; Yadav A.L. | Navigating Urban Mobility: A Review Of Ai-Driven Traffic Flow Management In Smart Cities | 2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions), ICRITO 2024 (2024) |
| 42891 | 0.91 | Mirza N.M.; Ali A.; Shifa N.; Ishak M.K.; Ammar K. | Predictive Modeling For Smart Traffic Systems: Harnessing Iot Data Insights | 2023 24th International Arab Conference on Information Technology, ACIT 2023 (2023) |
| 5377 | 0.908 | Salunke M.B.; Kulkarni S.V.; Ovale S.; Manjre B.M.; Limkar S.; Shaikh F.; Sai V. | A Sustainable Iot-Based Smart Transportation System For Urban Mobility | WSN and IoT: An Integrated Approach for Smart Applications (2024) |