WP9 – Stage 2 – AQI pilot control system
Planned activities during stage 2
Activity 9.1
Development of software architecture of an AQI pilot control system.
Activity 9.2
Building an AQI pilot control system based on the created architecture.
Activity 9.3
Developing AI models for uHealth services.
Activity 9.4
Testing and experimenting with the AQI pilot system to operate in different scenarios and use cases.
Results achieved during stage 2
- A stable architecture of the AQI pilot system has been implemented, ensuring reliable interaction between its individual elements.
- A stable and reliably functioning AQI pilot system has been created with a corresponding software application for planning dynamic routes for the movement of patients with various health problems in order to avoid polluted areas that pose a risk to their health.
- Numerous successfully functioning AI models with machine learning have been developed for use by the EMULSION platform created under the project in providing uHealth services to users in the IoT area of "smart healthcare".
- Successful operation of the developed AQI pilot system has been achieved when used in various scenarios and use cases.
- The results achieved under this work package are presented in the following scientific publications:
- In journals with impact factor / impact rank – 21 publications
[9.1*] L. Pendov, Z. Ji, I. Ganchev. 2024. “Healthy Route Generation and Recommendation”. WSEAS Transactions on Information Science and Applications, Vol. 21, December, Pp. 558-567. ISSN: 1790-0832. eISSN: 2224-3402. DOI: 10.37394/23209.2024.21.52.
Scopus, SJR2023=0.126 / Q4
https://wseas.com/journals/isa/2024/b045109-033(2024).pdf[9.2*] Z. Ji, Z. Yu, C. Liu, Z. Wang, S. Hao, I. Ganchev. 2024. “AFCF-Net: a novel U-Net based asymmetric feature calibration and fusion network for skin lesion image segmentation”. PLoS One, 19(11): e0314000, Pp. 1-26. November. (e)ISSN: 1932-6203. DOI: 10.1371/journal.pone.0314000.
WoS, IF2023=2.9 / Q1; Scopus, SJR2023=0.839 / Q1
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0314000[9.3*] S. Hao, X. Li, W. Peng, Z. Fan, Z. Ji, I. Ganchev. 2024. “YOLO-CXR: A novel detection network for locating multiple small lesions in chest X-ray images”. IEEE Access, Vol. 12, October, Pp. 156003-156019. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2024.3482102.
WoS, IF2023=3.4 / Q2; Scopus, SJR2023=0.960 / Q1
https://ieeexplore.ieee.org/document/10720017[9.4*] Z. Ji, X. Wang, C. Liu, Z. Wang, N. Yuan, I. Ganchev. 2024. “EFAM-Net: A Multi-Class Skin Lesion Classification Model Utilizing Enhanced Feature Fusion and Attention Mechanisms”. IEEE Access, Vol. 12, September, Pp. 143029-143041. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2024.3468612.
WoS, IF2023=3.4 / Q2; Scopus, SJR2023=0.960 / Q1
https://ieeexplore.ieee.org/document/10695064[9.5*] S. Hao, Z. Yu, B. Zhang, C. Dai, Z. Fan, Z. Ji, I. Ganchev. 2024. “MEFP-Net: A Dual-Encoding Multi-Scale Edge Feature Perception Network for Skin Lesion Segmentation”. IEEE Access, Vol. 12, September, Pp. 140039-140052. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2024.3467678.
WoS, IF2023=3.4 / Q2; Scopus, SJR2023=0.960 / Q1
https://ieeexplore.ieee.org/document/10693416[9.6*] Z. Ji, X. Li, Z. Wang, H. Zhang, N. Yuan, X. Zhang, I. Ganchev. 2024. “CafeNet: A Novel Multi-scale Context Aggregation and Multi-level Foreground Enhancement Network for Polyp Segmentation”. International Journal of Imaging Systems and Technology, Wiley. 34:e23183, September, Pp. 1-15. ISSN: 0899-9457. eISSN: 1098-1098. DOI: 10.1002/ima.23183.
WoS, IF2023=3.0 / Q2; Scopus, SJR2023=0.706 / Q2
https://onlinelibrary.wiley.com/doi/10.1002/ima.23183[9.7*] J. Liu, J. Mu, H. Sun, C. Dai, Z. Ji, I. Ganchev. 2024. “DLGRAFE-Net: A Double Loss Guided Residual Attention and Feature Enhancement Network for Polyp Segmentation”. PLoS One, 19(9): e0308237, Pp. 1-18. September. (e)ISSN: 1932-6203. DOI: 10.1371/journal.pone.0308237.
WoS, IF2023=2.9 / Q1; Scopus, SJR2023=0.839 / Q1
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0308237[9.8*] S. Hao, Y. Jia, J. Liu, Z. Wang, C. Liu, Z. Ji, I. Ganchev. 2024. “ST-Double-Net: A Two-Stage Breast Tumor Classification Model Based on Swin Transformer and Weakly Supervised Target Localization”. IEEE Access, Vol. 12, September, Pp. 117921-117933. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2024.3445954.
WoS, IF2023=3.4 / Q2; Scopus, SJR2023=0.960 / Q1
https://ieeexplore.ieee.org/document/10639378[9.9*] L. Shi, W. Zhou, Y. Wu, N. Yuan, X. Zang, Z. Ji, I. Ganchev. 2024. “DCM-CNER: A Dual-Channel Model for Clinical Named Entity Recognition Based on Embedded ConvNet and Gated Dilated CNN”. IEEE Access, Vol. 12, July, Pp. 97726-97738. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2024.3422677.
WoS, IF2023=3.4 / Q2; Scopus, SJR2023=0.960 / Q1
https://ieeexplore.ieee.org/document/10583858[9.10*] J. Liu, J. Mu, H. Sun, C. Dai, Z. Ji, I. Ganchev. 2024. “BFG&MSF-Net: Boundary Feature Guidance and Multi-Scale Fusion Network for Thyroid Nodule Segmentation”. IEEE Access, Vol. 12, May, Pp. 78701-78713. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2024.3407795.
WoS, IF2023=3.4 / Q2; Scopus, SJR2023=0.960 / Q1
https://ieeexplore.ieee.org/document/10543017[9.11*] Z. Ji, J. Liu, J. Mu, H. Zhang, C. Dai, N. Yuan, I. Ganchev. 2024. “ResDAC-Net: A Novel Pancreas Segmentation Model Utilizing Residual Double Asymmetric Spatial Kernels”. Medical & Biological Engineering & Computing, Springer. March, Pp. x1-x14. ISSN: 0140-0118. eISSN: 1741-0444. DOI: 10.1007/s11517-024-03052-9.
WoS, IF2023=2.6 / Q2; Scopus, SJR2023=0.641 / Q2
https://link.springer.com/article/10.1007/s11517-024-03052-9[9.12*] Z. Ji, H. Sun, N. Yuan, H. Zhang, J. Sheng, X. Zhang, I. Ganchev. 2024. “BGRD-TransUNet: A Novel TransUNet-based Model for Ultrasound Breast Lesion Segmentation”. IEEE Access, Vol. 12, February, Pp. 31182-31196. (e)ISSN: 2169-3536. DOI: 0.1109/ACCESS.2024.3368170.
WoS, IF2023=3.4 / Q2; Scopus, SJR2023=0.960 / Q1
https://ieeexplore.ieee.org/document/10442999[9.13*] Z. Ji, J. Mu, J. Liu, H. Zhang, C. Dai, X. Zhang, I. Ganchev. 2024. “ASD-Net: A novel U-Net based asymmetric spatial-channel convolution network for precise kidney and kidney tumor image segmentation”. Medical & Biological Engineering & Computing, Springer. February, Pp. x1-x15. ISSN: 0140-0118. eISSN: 1741-0444. DOI: 10.1007/s11517-024-03025-y.
WoS, IF2023=2.6 / Q2; Scopus, SJR2023=0.641 / Q2
https://link.springer.com/article/10.1007/s11517-024-03025-y[9.14*] S. Hao, L. Zhang, Y. Jiang, J. Wang, Z. Ji, L. Zhao, I. Ganchev. 2023. “ConvNeXt-ST-AFF: A Novel Skin Disease Classification Model Based on Fusion of ConvNeXt and Swin Transformer”. IEEE Access, Vol. 11, October, Pp. 117460-117473. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2023.3324042.
WoS, IF=3.4 / Q2; Scopus, SJR=0.960 / Q1
https://ieeexplore.ieee.org/document/10283846[9.15*] S. Hao, H. Wu, Y. Jiang, Z. Ji, L. Zhao, L. Liu, I. Ganchev. 2023. “GSCEU-Net: An End-to-End Lightweight Skin Lesion Segmentation Model with Feature Fusion Based on U-Net Enhancements”. Information, Vol. 14, No. 9: 486, September, Pp. 1-18. (e)ISSN: 2078-2489. DOI: 10.3390/info14090486.
WoS, IF=2.4 / Q3; Scopus, SJR=0.703 / Q2
https://www.mdpi.com/2078-2489/14/9/486[9.16*] Z. Ji, Z. Zhao, X. Zeng, J. Wang, L. Zhao, X. Zhang, I. Ganchev. 2023. “ResDSda_U-Net: A novel U-Net based residual network for segmentation of pulmonary nodules in lung CT images”. IEEE Access, Vol. 11, August, Pp. 87775-87789. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2023.3305270.
WoS, IF=3.4 / Q2; Scopus, SJR=0.960 / Q1
https://ieeexplore.ieee.org/document/10216982[9.17*] S. Hao, H. Wu, C. Du, X. Zeng, Z. Ji, X. Zhang, I. Ganchev. 2023. “CACDU-Net: A novel DoubleU-Net based semantic segmentation model for skin lesions detection in images”. IEEE Access, Vol. 11, August, Pp. 82449-82463. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2023.3300895.
WoS, IF=3.4 / Q2; Scopus, SJR=0.960 / Q1
https://ieeexplore.ieee.org/document/10198429[9.18*] Z. Ji, Y. Wu, X. Zeng, Y. An, L. Zhao, Z. Wang, I. Ganchev. 2023. “Lung Nodule Detection in Medical Images Based on Improved YOLOv5s”. IEEE Access, Vol. 11, July, Pp. 76371-76387. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2023.3296530.
WoS, IF=3.4 / Q2; Scopus, SJR=0.960 / Q1
https://ieeexplore.ieee.org/document/10185440[9.19*] Z. Ji, D. Yao, R. Chen, T. Lyu, Q. Liao, L. Zhao, I. Ganchev. 2023. “U-Net_dc: A novel U-Net-based model for endometrial cancer cell image segmentation”. Information, Vol. 14, No. 7: 366, June, Pp. 1-19. (e)ISSN: 2078-2489. DOI: 10.3390/info14070366.
WoS, IF=2.4 / Q3; Scopus, SJR=0.703 / Q2
https://www.mdpi.com/2078-2489/14/7/366[9.20*] Z. Ji, J. Zhao, J. Liu, X. Zeng, H. Zhang, X. Zhang, I. Ganchev. 2023. “ELCT-YOLO: An Efficient One-Stage Model for Automatic Lung Tumor Detection based on CT Images”. Mathematics, Vol. 11, No. 10: 2344, May, Pp. 1-22. (e)ISSN: 2227-7390. DOI: 10.3390/math11102344.
WoS, IF=2.3 / Q1 (top 5%); Scopus, SJR=0.475 / Q2
https://www.mdpi.com/2227-7390/11/10/2344[9.21*] S. Hao, H. Xu, H. Ji, Z. Wang, L. Zhao, Z. Ji, I. Ganchev. 2023. “G2-ResNeXt: A Novel Model for ECG Signal Classification”. IEEE Access, Vol. 11, April, Pp. 34808-34820. (e)ISSN: 2169-3536. DOI: 10.1109/ACCESS.2023.3265305.
WoS, IF=3.4 / Q2; Scopus, SJR=0.960 / Q1
https://ieeexplore.ieee.org/document/10093803 - In conference proceedings, referenced in WoS/Scopus – 4 publications
[9.22*] L. Pendov and I. Ganchev. 2024. “From raw data to 'best' travel route computation”. Proc. of the 2024 International Conference on Applied Mathematics and Computer Simulation (AMCS'24), Pp. 1-5, 1-3 December, Chamonix, France.
(accepted and sent for publication; will be referenced in Scopus)
[9.23*] Z. Ji, S. Hao, J. Pang, I. Ganchev. 2024. “Novel SSD-Based Models for Detection of Multidimensional Pulmonary Nodules in CT Images”. Proc. of the 7th International Conference in Signal Processing and Information Security (ICSPIS 2024), Pp. 1-6, 12-14 November, Dubai, UAE. eISSN: 2831-3844. eISBN: 979-8-3503-6867-3. DOI: 10.1109/ICSPIS63676.2024.10812640.
(will be referenced in Scopus)
https://ieeexplore.ieee.org/abstract/document/10812640[9.24*] Z. Ji and I. Ganchev. 2024. “Impact of Channel Numbers and Training Epochs on U-Net’s Polyp Segmentation Performance”. Proc. of the 7th International Conference in Signal Processing and Information Security (ICSPIS 2024), Pp. 1-4, 12-14 November, Dubai, UAE. eISSN: 2831-3844. eISBN: 979-8-3503-6867-3. DOI: 10.1109/ICSPIS63676.2024.10812647.
(will be referenced in Scopus)
https://ieeexplore.ieee.org/abstract/document/10812647[9.25*] I. Ganchev and Z. Ji. 2024. “IoT system for AQI monitoring and control”. Proc. of the 2024 IEEE International Conference "Automatics and Informatics" (ICAI'24), pp. x1-x6. 10-12 October. Varna, Bulgaria.
(accepted and sent for publication; will be referenced in Scopus)
http://www.tu-varna.bg/icai/images/programa/icai24_program_20241010.pdf