Smart City Gnosys
Smart city article details
| Title | An Intelligent Iot Enabled Traffic Queue Handling System Using Machine Learning Algorithm |
|---|---|
| ID_Doc | 8520 |
| Authors | Shamitha C.; Radhika S.; Malathy K.; Ranjith S.; Sasirekha N. |
| Year | 2022 |
| Published | Proceedings of the 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022 |
| DOI | http://dx.doi.org/10.1109/ICSES55317.2022.9914294 |
| Abstract | Overcrowding, pollutants, and logistical delays have been exacerbated by the fast expansion in the number of automobiles. The Internet of Things (IoT) is a new breakthrough that is bringing the world closer to fully automated processes and systems with sophisticated control. The growth of a nation on the other side of the world leads to an increase in personal automobiles. As a result, metropolitan cities have seen an increase in traffic. A improved traffic management system is needed, therefore. Good and dependable traffic control and bottleneck management may save a lot of money and time. IoT-based ITM sensors are installed in automated cars and smart gadgets to detect, acquire, and send data.. The use of machine learning (ML) may also help to enhance the transportation system. Because of the many issues with current transportation management systems, there is a high prevalence of traffic congestion, delays, and fatalities. Adaptive traffic control based on machine learning and the internet of things is the subject of this study. For the purposes of this proposal, vehicles, infrastructure, and events all play a key role in its design. The design uses a variety of situations to address all of the transportation system's challenges. A machine-learning-based DBSCAN clustering algorithm is included into the system's design to catch any unintentional anomalies. The suggested algorithm continually adjusts traffic light timings based on traffic flow and predicted movements from neighboring intersections. In addition to reducing travel time, it also reduces traffic congestion by creating a smoother transition. For smart-city-based transportation systems, the suggested traffic-management technique greatly outperforms the traditional approach, according to the results of an experiment. Decreases traffic jams, decrease traffic fatalities and enhances the overall route experience via the use of a suggested solution. © 2022 IEEE. |
| Author Keywords | DBSCAN method; intelligent traffic management; intelligent transport system; IoT; ML; smart road; traffic management system |
Similar Articles
| Id | Similarity | Authors | Title | Published |
|---|---|---|---|---|
18553  | 0.956 | Lilhore U.K.; Imoize A.L.; Li C.-T.; Simaiya S.; Pani S.K.; Goyal N.; Kumar A.; Lee C.-C. | Design And Implementation Of An Ml And Iot Based Adaptive Traffic-Management System For Smart Cities | Sensors, 22, 8 (2022) |
| 30638 | 0.954 | Sabeer S.; Ali S.S.; Siddiqua A.; Anjum A. | Implementing Ml And Iot-Based Predictive Traffic-Management Systems For Smart Cities | 2024 2nd International Conference Computational and Characterization Techniques in Engineering and Sciences, IC3TES 2024 (2024) |
| 19433 | 0.951 | 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) |
| 58554 | 0.926 | Ouhmidou H.; Nabou A.; Ikidid A.; Bouassaba W.; Ouzzif M.; El Kiram M.A. | Traffic Control, Congestion Management And Smart Parking Through Vanet, Ml, And Iot: A Review | Proceedings - 10th International Conference on Wireless Networks and Mobile Communications, WINCOM 2023 (2023) |
| 6910 | 0.925 | Dankan Gowda V.; Yogi K.S.; Srinivas I.V.; Kumar B.K.; Srinivas D.; Sudhakar Reddy N. | Ai And Machine Learning For Intelligent Traffic Management In Iot-Connected Cities | 2024 Asian Conference on Intelligent Technologies, ACOIT 2024 (2024) |
| 35933 | 0.922 | Balasubramanian S.B.; Balaji P.; Munshi A.; Almukadi W.; Prabhu T.N.; Venkatachalam K.; Abouhawwash M. | Machine Learning Based Iot System For Secure Traffic Management And Accident Detection In Smart Cities | PeerJ Computer Science, 9 (2023) |
| 24036 | 0.919 | 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) |
| 1444 | 0.914 | Vamsi B.; Doppala B.P.; Mahanty M.; Veeraiah D.; Rao J.N.; Rao B.V.S. | A Detailed Case Study On Various Challenges In Vehicular Networks For Smart Traffic Control System Using Machine Learning Algorithms | Artificial Intelligence and Machine Learning for Smart Community: Concepts and Applications (2024) |
| 5762 | 0.911 | Prakash J.; Murali L.; Manikandan N.; Nagaprasad N.; Ramaswamy K. | A Vehicular Network Based Intelligent Transport System For Smart Cities Using Machine Learning Algorithms | Scientific Reports, 14, 1 (2024) |
| 50657 | 0.911 | Saini K.; Sharma S. | Smart City: Road Traffic Monitoring System Based On The Integration Of Iot And Ml | Lecture Notes in Networks and Systems, 686 LNNS (2023) |