Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{194774,
        author = {Anuja H. Khandar and Abhishek M. Chavan and Shruti S. Bhakte and Shailesh V. Bakale and Utkarsha D. Tamgire and Dr. L. K. Gautam},
        title = {AI Powered Civic Issue Resolution System In Urban Area},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {5575-5581},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=194774},
        abstract = {The rapid growth of urban populations and the rising demand for infrastructure have increased the need for efficient systems to manage civic issues. Traditional complaint management approaches often face several challenges, including lack of transparency, slow response times, incorrect classification of complaints, and weak accountability mechanisms. This research proposes a Civic Issue Reporting and Resolution System designed to improve municipal service management through automation and effective record handling. The proposed framework allows citizens to report problems such as damaged roads, waste accumulation, and public safety concerns using structured digital inputs. The system stores complaint data and status updates in a secure blockchain-based environment to ensure transparency and prevent unauthorized modifications. In addition, artificial intelligence techniques are applied to automatically categorize reported issues using probabilistic text classification methods. A hybrid prioritization model combining rule-based logic and predictive analysis is used to determine the urgency of complaints. The system also detects duplicate reports through similar measurement techniques and automatically assigns tasks to the appropriate municipal departments based on a scoring mechanism. Furthermore, the analytics module supports performance evaluation and trend analysis, helping authorities plan maintenance activities more effectively. Overall, the proposed architecture aims to reduce manual effort, improve the accuracy of complaint routing, minimize duplicate reports, and enhance public trust through transparent and secure tracking mechanisms. The study highlights that integrating crowd-sourced reporting with intelligent classification, automated prioritization, and secure record management can significantly improve the efficiency of urban governance systems.},
        keywords = {Civic Complaint Management; Blockchain Transparency; Issue Classification; Priority Detection; Smart Governance.},
        month = {March},
        }