CIVICSENSE: AN AI-POWERED MULTI-ISSUE CLASSIFICATION SYSTEM FOR URBAN CIVIC PROBLEM MANAGEMENT
S.R Harshini
, K.Muthukarupaee , T. Praveena , M. Varshini , A. Vijaya Kavi
Artificial Intelligence, Pothole Detection, Garbage Detection, YOLO11, Deep Learning, CCTV Monitoring, Smart City, Computer Vision, Automated Complaint Generation, Municipal Services.
This paper presents an AI-Based Pothole and Garbage Detection System that automates the identification and reporting of
road infrastructure issues using deep learning techniques. The proposed system integrates the YOLO11 (You Only Look
Once) object detection algorithm to analyse live CCTV camera feeds and user-uploaded images for real-time detection of
potholes and garbage accumulation. Upon detection, the system automatically generates structured complaints containing
image evidence, GPS location coordinates, and timestamp information, which are forwarded directly to the concerned
municipal authorities. A maintenance status tracking module enables authorities to update and monitor the resolution
progress of each complaint as pending, in progress, or completed. The system also supports manual image uploads from
citizens in areas lacking CCTV infrastructure, ensuring comprehensive urban coverage. Experimental evaluation confirms
that the YOLO11-based detection pipeline achieves high accuracy across varying environmental and lighting conditions.
The proposed solution significantly reduces manual inspection effort, accelerates municipal response time, and promotes
accountability in urban road maintenance — contributing directly to smart city development objectives.
"CIVICSENSE: AN AI-POWERED MULTI-ISSUE CLASSIFICATION SYSTEM FOR URBAN CIVIC PROBLEM MANAGEMENT", JETNR - JOURNAL OF EMERGING TRENDS AND NOVEL RESEARCH (www.JETNR.org), ISSN:2984-9276, Vol.4, Issue 6, page no.c310-c317, June-2026, Available :https://rjpn.org/JETNR/papers/JETNR2606261.pdf
Volume 4
Issue 6,
June-2026
Pages : c310-c317
Paper Reg. ID: JETNR_235338
Published Paper Id: JETNR2606261
Downloads: 00051
Research Area: Science and Technology
Country: Tiruchirappalli, Tamil Nadu, India
ISSN: 2984-9276 | IMPACT FACTOR: 9.87 Calculated By Google Scholar | ESTD YEAR: 2023
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.87 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: RJPN (IJPublication) Janvi Wave
