IoT-Based Emergency Vehicle Detection Using YOLOv8

[1] A. Baghel, A. Srivastava, A. Tyagi, S. Goel, and P. Nagrath, “Analysis Of Ex-Yolo Algorithm With Other Real-Time Algorithms For Emergency Vehicle Detection,” in Intelligent Methods in Emerging Robotics and Automation, vol. 978, Lecture Notes in Networks and Systems, Springer, 2020, doi: 10.1007/978-981-15-3369-3_45. A. Baghel A. Srivastava A. Tyagi S. Goel P. Nagrath “Analysis Of Ex-Yolo Algorithm With Other Real-Time Algorithms For Emergency Vehicle Detection,” in Intelligent Methods in Emerging Robotics and , vol. 978 , Lecture Notes in Networks and Systems , Springer , 2020 , 10.1007/978-981-15-3369-3_45 . Open DOISearch in Google Scholar

[2] V. T. Tran and W. H. Tsai, “Audio-Vision Emergency Vehicle Detection,” IEEE Sensors Journal, vol. 21, no. 24, pp. 27905–27917, Dec. 2021, doi: 10.1109/JSEN.2021.3127893. V. T. Tran W. H. Tsai “Audio-Vision Emergency Vehicle Detection,” IEEE Sensors , vol. 21 , no. 24 , pp. 27905 – 27917 , Dec . 2021 , 10.1109/JSEN.2021.3127893 . Open DOISearch in Google Scholar

[3] N. Dahiya, M. Garg, S. Gupta, and D. Gupta, “Smart Ambulance System Using Internet of Things: A Rumination,” Journal of Computational and Theoretical Nanoscience, vol. 16, pp. 4249–4254, 2019, doi: 10.1166/jctn.2019.8508. N. Dahiya M. Garg S. Gupta D. Gupta “Smart Ambulance System Using Internet of Things: A Rumination,” Journal of Computational and Theoretical , vol. 16 , pp. 4249 – 4254 , 2019 , 10.1166/jctn.2019.8508 . Open DOISearch in Google Scholar

[4] W.-J. Chang, L.-B. Chen, and K.-Y. Su, “DeepCrash: A Deep Learning-Based Internet of Vehicles System for Head-On and Single-Vehicle Accident Detection With Emergency Notification,” IEEE Access, vol. 7, pp. 148 163–148 175, 2019, doi: 10.1109/ACCESS.2019.2946468. W.-J. Chang L.-B. Chen K.-Y. Su “DeepCrash: A Deep Learning-Based Internet of Vehicles System for Head-On and Single-Vehicle Accident Detection With Emergency Noti^ication,” IEEE , vol. 7 , pp. 148 163 – 148 175 , 2019 , 10.1109/ACCESS.2019.2946468 . Open DOISearch in Google Scholar

[5] A. Benjumea, I. Teeti, F. Cuzzolin, and A. Bradley, “YOLO-Z: Improving Small Object Detection in YOLOv5 for Autonomous Vehicles,” arXiv preprint arXiv:2112.11798, 2021. A. Benjumea I. Teeti F. Cuzzolin A. Bradley “YOLO-Z: Improving Small Object Detection in YOLOv5 for Autonomous Vehicles,” arXiv preprint arXiv:2112.11798 , 2021 . Search in Google Scholar

[6] S. Ren, K. He, R. Girshick, and J. Sun, “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks,” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 39, no. 6, pp. 1137–1149, June 2017, doi: 10.1109/TPAMI.2016.2577031. S. Ren K. He R. Girshick J. Sun “Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks,” IEEE Transactions on Pattern Analysis and Machine , vol. 39 , no. 6 , pp. 1137 – 1149 , June 2017 , 10.1109/TPAMI.2016.2577031 . Open DOISearch in Google Scholar

[7] M. Zuraimi and F. Zaman, “Vehicle Detection and Tracking Using YOLO and DeepSORT,” in Proc. 2021 Int. Seminar on Intelligent Control and Future Energy (ISICFE), pp. 23–29, 2021, doi: 10.1109/ISCAIE51753.2021.9431784. M. Zuraimi F. Zaman “Vehicle Detection and Tracking Using YOLO and DeepSORT,” in Proc. 2021 Int. Seminar on Intelligent Control and Future Energy (ISICFE) , pp. 23 – 29 , 2021 , 10.1109/ISCAIE51753.2021.9431784 . Open DOISearch in Google Scholar

[8] J. Lu, C. Ma, L. Li, X. Xing, Y. Zhang, Z. Wang, and J. Xu, “A Vehicle Detection Method for Aerial Image Based on YOLO,” Journal of Computer and Communications, vol. 6, no. 11, pp. 98–107, Nov. 2018, doi: 10.4236/jcc.2018.611009. J. Lu C. Ma L. Li X. Xing Y. Zhang Z. Wang J. Xu “A Vehicle Detection Method for Aerial Image Based on YOLO,” Journal of Computer and , vol. 6 , no. 11 , pp. 98 – 107 , Nov . 2018 , 10.4236/jcc.2018.611009 . Open DOISearch in Google Scholar

[9] J. Hussain, B. R. P. Prathap, and A. Sharma, “An Improved and Efficient YOLOv4 Method for Object Detection in Video Streaming,” in Data Science and Security: Proceedings of IDSCS 2022, Singapore: Springer Nature Singapore, 2022, pp. 305–316, doi: 10.1007/978-981-19-2211-4_27. J. Hussain B. R. P. Prathap A. Sharma “An Improved and Ef^icient YOLOv4 Method for Object Detection in Video Streaming,” in Data Science and Security: Proceedings of IDSCS 2022 , Singapore : Springer Nature Singapore , 2022 , pp. 305 – 316 , 10.1007/978-981-19-2211-4_27 . Open DOISearch in Google Scholar

[10] K. Munasinghe, T. Waththegedara, I. Wickramas-inghe, O. K. Herath, and L. Velmanickam, “Smart Traffic Light Control System Based on Traffic Density and Emergency Vehicle Detection,” in Proc. 2022 Middle East Conf. on Innovation in Revision and Communication (MERCon), pp. 1–6, 2022, doi: 10.1109/MERCon55799.2022.99061 84. K. Munasinghe T. Waththegedara I. Wickramas-inghe O. K. Herath L. Velmanickam “Smart Traffic Light Control System Based on Traffic Density and Emergency Vehicle Detection,” in Proc. 2022 Middle East Conf. on Innovation in Revision and Communication (MERCon) , pp. 1 – 6 , 2022 , 10.1109/MERCon55799.2022.99061 84 . Open DOISearch in Google Scholar

[11] A. Ashir, “A Transfer-Learning-Based Approach for Emergency Vehicle Detection,” Eurasian Journal of Science and Engineering, vol. 8, no. 1, p. 75, 2022, doi: 10.23918/eajse.v8i1p75. A. Ashir “A Transfer-Learning-Based Approach for Emergency Vehicle Detection,” Eurasian Journal of Science and , vol. 8 , no. 1 , p. 75 , 2022 , 10.23918/eajse.v8i1p75 . Open DOISearch in Google Scholar

[12] R. Huang, J. Pedoeem, and C. Chen, “YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers,” in Proc. 2018 IEEE International Conference on Big Data (Big Data), pp. 2503–2507, 2018. R. Huang J. Pedoeem C. Chen “YOLO-LITE: A Real-Time Object Detection Algorithm Optimized for Non-GPU Computers,” in Proc. 2018 IEEE International Conference on Big Data (Big Data) , pp. 2503 – 2507 , 2018 . Search in Google Scholar

[13] W. Fang, L. Wang, and P. Ren, “Tinier-YOLO: A Real-Time Object Detection Method for Constrained Environments,” IEEE Access, vol. 8, pp. 1935–1944, 2020, doi: 10.1109/ACCESS.2 019.2961959. W. Fang L. Wang P. Ren “Tinier-YOLO: A Real-Time Object Detection Method for Constrained Environments,” IEEE , vol. 8 , pp. 1935 – 1944 , 2020 , 10.1109/ACCESS.2 019.2961959 . Open DOISearch in Google Scholar

[14] L. Cheng, J. Li, P. Duan, and M. Wang, “A Small Attentional YOLO Model for Landslide Detection from Satellite Remote Sensing Images,” Landslides, vol. 18, no. 10, pp. 3251–3264, 2021, doi: 10.1007/s10346-021-01694-6. L. Cheng J. Li P. Duan M. Wang “A Small Attentional YOLO Model for Landslide Detection from Satellite Remote Sensing Images,” , vol. 18 , no. 10 , pp. 3251 – 3264 , 2021 , 10.1007/s10346-021-01694-6 . Open DOISearch in Google Scholar

[15] C. Dewi, R.-C. Chen, Y.-T. Liu, X. Jiang, and K. Hartomo, “YOLO V4 for advanced traffic sign recognition with synthetic training data gener-ated by various GAN,” IEEE Access, vol. 9, pp. 97236–97248, 2021, doi: 10.1109/ACCESS.202 1.3094201. C. Dewi R.-C. Chen Y.-T. Liu X. Jiang K. Hartomo “YOLO V4 for advanced traffic sign recognition with synthetic training data generated by various GAN,” IEEE , vol. 9 , pp. 97236 – 97248 , 2021 , 10.1109/ACCESS.202 1.3094201 . Open DOISearch in Google Scholar

[16] S. Chen and W. Lin, “Embedded System Real-Time Vehicle Detection Based on Improved YOLO Network,” in Proceedings of the IEEE 2nd International Conference on Intelligent Control, Measurement and Computing (ICICMC), pp. 1400–1403, 2019, doi: 10.1109/IMCEC46724.2019.8984 055. S. Chen W. Lin “Embedded System Real-Time Vehicle Detection Based on Improved YOLO Network,” in Proceedings of the IEEE 2nd International Conference on Intelligent Control, Measurement and Computing (ICICMC) , pp. 1400 – 1403 , 2019 , 10.1109/IMCEC46724.2019.8984 055 . Open DOISearch in Google Scholar