AI-Powered Smart Civic Issue Management System: A Multi-Modal Approach for Enhanced Urban Governance and Citizen Engagement

DOI

10.2991/978-94-6239-723-1_16How to use a DOI?

Keywords

Civic Issue Management; Artificial Intelligence; Vision Transformers; BERT; CLIP; Smart Governance; Service Level Agreement Monitoring

Abstract

In developing countries like India infrastructure and other public issues which are directly related to the country growth are most prominent and should not delayed. These issues such as potholes, garbage accumulation, water leakage, fire etc requires quick attention of authorities to get resolved. General public must be involved to report such issues and a quick coordination among departments/authorities and also quick monitoring requires to get over. It motivates us to design an automated system that may ensure every complaint reaches the right authority and gets resolved on time. In this system, citizens can register complaints by uploading an image, description, and location of the issue. Using AI models like, Vision Transformers for image understanding and BERT for text analysis, combined through CLIP, the platform accurately identifies the issue type and automatically assigns it to the appropriate department. Each complaint is given a priority level, such as high, medium, or low, based on its urgency and impact. The system continuously monitors the complaint, sends reminders as the SLA approaches, and if unresolved, auto-escalates it to higher authorities. Additionally, a two-way feedback module allows authorities to update progress while citizens can track the real-time status of their complaints.

Copyright

© 2026 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Manas Tripathi
AU  - Praveen Kumar Nishad
AU  - Harshit Mani Tripathi
AU  - Karan Agrahari
AU  - Anupama Sharma
PY  - 2026
DA  - 2026/07/14
TI  - AI-Powered Smart Civic Issue Management System: A Multi-Modal Approach for Enhanced Urban Governance and Citizen Engagement
BT  - Proceedings of the International Conference on Responsible, Risk-aware, and Regulated AI (RRRAI 2026)
PB  - Atlantis Press
SP  - 175
EP  - 185
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6239-723-1_16
DO  - 10.2991/978-94-6239-723-1_16
ID  - Tripathi2026
ER  -