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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM67439
Volume:
10 |
9 |
Sep 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Department of Computer Science And Engineering
P R POTE PATIL COLLEGE OF ENGINEERING AND MANGMENT, AMRAVATI
Department of Computer Science And Engineering
P R POTE PATIL COLLEGE OF ENGINEERING AND MANGMENT, AMRAVATI
Department of Computer Science And Engineering
P R POTE PATIL COLLEGE OF ENGINEERING AND MANGMENT, AMRAVATI
Department of Computer Science And Engineering
P R POTE PATIL COLLEGE OF ENGINEERING AND MANGMENT, AMRAVATI
Department of Computer Science And Engineering
P R POTE PATIL COLLEGE OF ENGINEERING AND MANGMENT, AMRAVATI
Department of Computer Science And Engineering
P R POTE PATIL COLLEGE OF ENGINEERING AND MANGMENT, AMRAVATI
Department of Computer Science And Engineering
P R POTE PATIL COLLEGE OF ENGINEERING AND MANGMENT, AMRAVATI
support activities and local help requests are often shared through scattered channels, making it difficult for Community people to discover nearby opportunities or for organizations to reach suitable volunteers. CiviLink is proposed as a community help and volunteer coordination platform that connects citizens, volunteers, NGOs and other organizations through a common digital environment. The platform supports two major functions: community activity management and help request management. Users can create or discover activities such as blood donation camps, tree plantation drives, food distribution and clothing drives, while people or organizations requiring assistance can create help requests that can be responded to by nearby citizens, volunteers or organizations. Location-based information helps users discover relevant activities and requests in their area. Verification, moderation, authentication and role-based authorization are included to improve reliability and controlled access. The proposed implementation uses HTML, CSS, JavaScript and Bootstrap for the frontend, Spring Boot with Java for the backend, MYSQL for structured data management, and REST APIs for communication. OpenStreetMap and Nominatim can support location-related functionality, while Cloudinary may be used for controlled image storage. An optional AI layer can assist with request classification and duplicate-request detection, while final verification remains under authorized human control. The platform is intended to provide a practical software-based approach for improving community coordination, information sharing and participation.
KEYWORDS
CiviLink presents a practical approach to community help and volunteer coordination by bringing citizens, volunteers, NGOs and organizations into a common digital platform. The proposed Activity Module helps users discover and participate in community activities, while the Help Request Module connects assistance requirements with people willing to respond. Location-based discovery, authentication, verification, moderation and status tracking provide the supporting structure required for reliable coordination. The system can be implemented using a conventional web architecture with HTML, CSS, JavaScript, Bootstrap, Spring Boot, Java and PostgreSQL. Future development can extend the platform with stronger GIS features, notifications and AI-assisted analysis, while keeping human verification and community participation at the center of the workflow.
[1] S. Muthukumar, S. Rajesh, A. Talpallikar, and T. K. Mishra, “A Systematic Review of Artificial Intelligence Frameworks for Holistic Disaster Management,” Discover Artificial Intelligence, 2026. [2] Z. Chen et al., “Integration of Large Vision Language Models for Efficient Post-Disaster Damage Assessment and Reporting,” Nature Communications, 2026. [3] A. Whyte, “Building Centaur Responders: Is Emergency Management Ready for Artificial Intelligence?” Disasters, 2026. [4] F. Xu, J. Ma, N. Li, and J. C. P. Cheng, “Large Language Model Applications in Disaster Management: An Interdisciplinary Review,” International Journal of Disaster Risk Reduction,2025 . [5] Z. Lei, Y. Dong, W. Li, R. Ding, Q. Wang, and J. Li, “Harnessing Large Language Models for Disaster Management: A Survey,” ACL Findings, 2025
Publication Date
9/24/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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