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Original Article
Automated Traffic Monitoring System
Darshan N Y1
Dr. Sharath M N2
1 PG Student, Department of Computer Science and Engineering, Rajeev Institute of Technology, Hassan, Visvesvaraya Technological University, Belagavi, Karnataka, India. 2 Department of Computer Science and Engineering (AI&ML) Rajeev Institute of Technology, Hassan, Visvesvaraya Technological University, Belagavi, Karnataka, India.
Published Online: September-December 2025
Pages: 153-159
Cite this article
No DOIReferences
1. Li, L., & Jayakumar S., Lokesh Kumar K., Purva Darshini S. K., & Sanjeev D & Kumar et al. (2021). Traffic Monitoring System Using IoT and DL. In Advances in Parallel Computing Technologies and Applications. IOS Press.
2. Zhao, X., Dawson, D., Sarasua, W. A., & Birchfield, S. T. & Zhao et al (2020) (2020). Automated Traffic Surveillance System with Aerial Camera Arrays Imagery: Macroscopic Data Collection with Vehicle Tracking.
3. Chen, J., Xing, H.L., Yang, H., & Xu, L.X. (2019).Network Traffic Analysis Using LSTM Neural Networks. Open Journal of Applied Sciences, 9(12), 1–10.
4. Singh, T., Rajput, V., Satakshi, Prasad, U., & Kumar, M. (2022). Real-time traffic light violations using distributed streaming.The Journal of Supercomputing. https://doi.org/10.1007/s11227-022- 04897-9
5. Li, T., Bian, Z., Lei, H., Zuo, F., Yang, Y.-T., Zhu,Q., Li, Z., & Ozbay, K. (2024). Multi-level Traffic- Responsive Tilt Camera Surveillance through Predictive Correlated Online Learning. arXiv. https://arxiv.org/abs/2408.02208
6. Wang, Y., Wang, Q., Suo, D., & Wang, T. (2020). Intelligent traffic monitoring and traffic diagnosis analysis based on neural network algorithm. Neural Computing and Applications.
7. Mandal, V., Mussah, A. R., Jin, P., & Adu- Gyamfi, Y. (2020). Artificial Intelligence Enabled Traffic Monitoring System. Sustainability, 12(21), 9177.
8. Dong, Z., Lu, Y., Tong, G., Shu, Y., Wang, S., & Shi, W. (2020). WatchDog: Real time Vehicle Tracking on Geo-distributed Edge Nodes.
2. Zhao, X., Dawson, D., Sarasua, W. A., & Birchfield, S. T. & Zhao et al (2020) (2020). Automated Traffic Surveillance System with Aerial Camera Arrays Imagery: Macroscopic Data Collection with Vehicle Tracking.
3. Chen, J., Xing, H.L., Yang, H., & Xu, L.X. (2019).Network Traffic Analysis Using LSTM Neural Networks. Open Journal of Applied Sciences, 9(12), 1–10.
4. Singh, T., Rajput, V., Satakshi, Prasad, U., & Kumar, M. (2022). Real-time traffic light violations using distributed streaming.The Journal of Supercomputing. https://doi.org/10.1007/s11227-022- 04897-9
5. Li, T., Bian, Z., Lei, H., Zuo, F., Yang, Y.-T., Zhu,Q., Li, Z., & Ozbay, K. (2024). Multi-level Traffic- Responsive Tilt Camera Surveillance through Predictive Correlated Online Learning. arXiv. https://arxiv.org/abs/2408.02208
6. Wang, Y., Wang, Q., Suo, D., & Wang, T. (2020). Intelligent traffic monitoring and traffic diagnosis analysis based on neural network algorithm. Neural Computing and Applications.
7. Mandal, V., Mussah, A. R., Jin, P., & Adu- Gyamfi, Y. (2020). Artificial Intelligence Enabled Traffic Monitoring System. Sustainability, 12(21), 9177.
8. Dong, Z., Lu, Y., Tong, G., Shu, Y., Wang, S., & Shi, W. (2020). WatchDog: Real time Vehicle Tracking on Geo-distributed Edge Nodes.
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