Smart City Gnosys

Smart city article details

Title	Integrating Cloud-Based Data Mining Algorithms For Smart City Infrastructure Management And Decision Support Systems
ID_Doc	31957
Authors	Guru Vimal Kumar M.; Jude Moses Anto Devakanth J.; Selvapandian D.; Venkatesan R.; Revathi J.; Aruna R.
Year	2024
Published	Proceedings - 2024 4th International Conference on Soft Computing for Security Applications, ICSCSA 2024
DOI	http://dx.doi.org/10.1109/ICSCSA64454.2024.00024
Abstract	This study explores cloud-based data mining algorithm integration in elevating smart city infrastructure management and decision support systems. Specifically, the authors focus on optimizing traffic management through the analysis of real-Time traffic sensor data. Timestamped history records of vehicle count, traffic speed, density, weather condition, accidents, and traffic signals were utilized. Machine learning models such as Support Vector Machine, K-Nearest Neighbors, Decision Trees, and Random Forest were trained and tested. The analysis indicated SVM to be the most effective instrument, resulting in an accuracy of 98.98%. The model was also instrumental in reducing vehicle count by 16.7%, traffic density by 25%, and traffic speed was increased by 50%. KNN's overall accuracy experience was 94.5%, and the model was shown to be highly optimized for various forever traffic conditions. However, the overall impact on traffic speed and density was not as significant compared to the previously-discussed model. DT and RF demonstrated respective accuracies of 92.3% and 91.2%, offering varying levels of decision interpretation and ensemble learning opportunities. As a result, the study indicates that machine learning can play a critical role in improving urban traffic management via traffic congestion prediction and minimization, resulting in improved traffic flow, overall trip time reduction, and general urban mobility management. T. © 2024 IEEE.
Author Keywords	data mining; infrastructure optimization; machine learning; smart cities; traffic management

Similar Articles

Id	Similarity	Authors	Title	Published
22862	0.912	Jenifer J.; Jemima Priyadarsini R.	Empirical Research On Machine Learning Models And Feature Selection For Traffic Congestion Prediction In Smart Cities	International Journal on Recent and Innovation Trends in Computing and Communication, 11 (2023)
19433	0.909	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)
5762	0.908	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)
32252	0.905	Alla K.R.; Thangarasu G.	Intelliflow: A Machine Learning-Driven Dynamic Traffic Management In Smart Cities	2023 2nd International Conference on Smart Technologies for Smart Nation, SmartTechCon 2023 (2023)
12109	0.905	Mystakidis A.; Tjortjis C.	Big Data Mining For Smart Cities: Predicting Traffic Congestion Using Classification	11th International Conference on Information, Intelligence, Systems and Applications, IISA 2020 (2020)
37160	0.903	Ei Leen M.W.; Jafry N.H.A.; Salleh N.M.; Hwang H.J.; Jalil N.A.	Mitigating Traffic Congestion In Smart And Sustainable Cities Using Machine Learning: A Review	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13957 LNCS (2023)
12161	0.903	Hlaing S.S.; Tin M.M.; Khin M.M.; Wai P.P.; Sinha G.R.	Big Traffic Data Analytics For Smart Urban Intelligent Traffic System Using Machine Learning Techniques	2020 IEEE 9th Global Conference on Consumer Electronics, GCCE 2020 (2020)
60223	0.903	Tsalikidis N.; Mystakidis A.; Koukaras P.; Ivaškevičius M.; Morkūnaitė L.; Ioannidis D.; Fokaides P.A.; Tjortjis C.; Tzovaras D.	Urban Traffic Congestion Prediction: A Multi-Step Approach Utilizing Sensor Data And Weather Information	Smart Cities, 7, 1 (2024)
36035	0.899	Bawaneh M.; Simon V.	Machine Learning-Based Anomaly Detection In Smart City Traffic: Performance Comparison And Insights	International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS - Proceedings (2025)
8520	0.897	Shamitha C.; Radhika S.; Malathy K.; Ranjith S.; Sasirekha N.	An Intelligent Iot Enabled Traffic Queue Handling System Using Machine Learning Algorithm	Proceedings of the 2022 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems, ICSES 2022 (2022)