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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM65267
Volume:
10 |
6 |
Jun 2026
Pages:
1-4
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
Donbosco Institute Of Technonogy
Department of Computer Science
Donbosco Institute Of Technonogy
Department of Computer Science
Donbosco Institute Of Technonogy
Department of Computer Science
Donbosco Institute Of Technonogy
Department of Computer Science
Donbosco Institute Of Technonogy
The increasing number of civic complaints in urban areas makes manual complaint management slow, inefficient, and difficult to prioritize. Many systems that handle complaints do things in the order they get them, which can make it take a time to fix really important problems like water leaks, road damage and electricity.. The system we are talking about uses civil complaint prioritization and Machine Learning to make things better. The system lets people send in complaints online and then it looks at them , figures out what kind of complaint it is. The Machine Learning algorithms help sort out the complaints and predict which ones are the important so the people in charge can deal with the big problems first. The system makes things more transparent get rid of delays and helps the city use its resources better..It also gives people a way to track their complaints and lets the administrators keep an eye on everything. By making the prioritization process automatic the system tries to make the city’s service better and fix problems faster.
KEYWORDS
The proposed Civil Complaint Prioritization System provides a solution for managing civic complaints. It helps classify complaint and assign priority levels based on the severity and urgency of the issue. This reduces manual effort and helps municipal authorities respond quickly to critical complaints. Overall, the proposed system improves complaint management efficiency, reduces response time, and supports better public service administration. In future the system can be enhanced by integrating image processing, real time notifications , and mobile application support for better user accessibility and accuracy. Finally, the authors would like to acknowledge their families for their constant encouragement, patience, and unwavering support, which served as a strong source of motivation throughout the course of this work.
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Publication Date
6/21/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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