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International Journal of Science, Strategic Management and Technology

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DISASTER AID CONNECT: ADVANCED DISASTER MANAGEMENT PORTAL FOR PEOPLE LIFE SAFETY

AUTHORS:
Jeeva Shree D
Sanmathi V C
Priya Dharshini P
Kamali S M
Mentor
Affiliation
Computer Science and engineering / Avinashilingam University, Coimbatore, Tamil Nadu
DOI: 10.55041/ijsmt.v2i4.008
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract

Natural disasters such as floods, earthquakes, and landslides pose significant threats to human life and infrastructure, particularly in regions where traditional monitoring systems fail to provide timely alerts. Existing disaster management approaches rely heavily on manual observation and threshold-based techniques, which often result in delayed responses and reduced accuracy. To overcome these limitations, this paper proposes Disaster Aid Connect, an IoT-based disaster detection and management system integrated with machine learning for real-time prediction and alerting.

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PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 04
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Apr 02 2026
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D, J. S., C, S. V., P, P. D. & M, K. S. (2026). Disaster AID Connect: Advanced Disaster Management Portal for People Life Safety. International Journal of Science, Strategic Management and Technology, 02(04). https://doi.org/10.55041/ijsmt.v2i4.008

D, Jeeva, et al.. "Disaster AID Connect: Advanced Disaster Management Portal for People Life Safety." International Journal of Science, Strategic Management and Technology, vol. 02, no. 04, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i4.008.

D, Jeeva,Sanmathi C,Priya P, and Kamali M. "Disaster AID Connect: Advanced Disaster Management Portal for People Life Safety." International Journal of Science, Strategic Management and Technology 02, no. 04 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i4.008.

References
[1]Malika Noui, Abdelaziz Lakhfif, and Mohamed Amin Laouadi, "Towards Useful Event Detection and Sentiment Analysis of OSN for Disaster Management", 2024 International Conference on Information and Communication Technologies for   Disaster   Management   (ICT-DM),   2024,   doi:   10.1109/ICT- DM62768.2024.10798933.

[2] Feng He, Li Li, and Shan Li, "Design of Automatic Disaster Detection Algorithm  for  Remote  Sensing  Images  Based  on  Deep  Learning",  2024 International Conference on Electrical Drives, Power Electronics & Engineering (EDPEE), 2024, doi: 10.1109/EDPEE61724.2024.00006.

[3] Yida Fan, Wei Wu, Ming Liu, et al., "Capacity analysis of GF—4 on the disaster management", 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 2016, doi: 10.1109/IGARSS.2016.7729971.

[4] Han Gao, Haoyu Wu, Lei Xu, et al., "Flood Disaster Detection with Dual- Polarization SAR Data Considering the Impact of Rainfall", IGARSS 2024 - 2024 IEEE  International  Geoscience  and  Remote  Sensing  Symposium,  2024,  doi: 10.1109/IGARSS53475.2024.10642802.

[5] Zhipeng Liu, Chunbo Luo, Geyong Min, et al., "DisasterScope A Comprehensive Dataset and RTMDet-based Methodology for Object Detection in Disaster-Related Remote Sensing Images", IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium, 2024,doi:10.1109/IGARSS53475.2024.1064128.

[6] Reem Hejazi, Muddesar Iqbal, Anees Ara, et al., "An Integrated UGV-UAV System for Real-Time Disaster Management  A Multi-Protocol Communication Framework", 2025 8th International Conference on Enterprise Systems (ES),2025,doi:10.1109/ES64449.2025.11136250

[7] Feng He, Li Li, and Shan Li, “Design of Automatic Disaster Detection Algorithm  for  Remote  Sensing  Images  Based  on  Deep  Learning,”  2024 International Conference on Remote Sensing and Geoinformation (ICRSG), 2024, doi: 10.1109/EDPEE61724.2024.00006.

 

 
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✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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