Home / Current Issue / Paper 1719436
SiliconSahaaya: An AI-Powered Smart Civic Grievance Management System
Subject area: Science,Engineering and Technology · Area of research: IOT
DOI: https://doi.org/10.64388/IREV10I1-1719436
Abstract
Rapid urbanization has significantly increased civic issues such as garbage overflow, potholes, drainage blockage, water leakage, broken streetlights, and road damage. Existing grievance management systems often suffer from poor complaint routing, delayed response mechanisms, lack of transparency, and dependency on manual department selection. These challenges reduce citizen satisfaction and create inefficiencies in public administration. To address these limitations, SiliconSahaaya, an AI-powered smart civic grievance management system, is proposed to automate the process of civic issue reporting and complaint resolution. The system enables citizens to register complaints through image uploads, GPS-based location detection, and mobile-friendly interfaces. By integrating Artificial Intelligence and Machine Learning techniques such as XGBoost, TF-IDF with Logistic Regression, TextBlob/VADER sentiment analysis, and YOLOv8 object detection, the platform intelligently analyzes complaints, predicts issue priority, categorizes civic problems, and automatically routes grievances to the relevant government departments. The proposed system also includes a React Native mobile application, real-time notifications using Firebase Cloud Messaging, SMS services through Twilio, email notifications using Nodemailer, and secure authentication using JWT and OTP verification. Furthermore, the platform integrates Leaflet.js-based geographic hotspot detection, enabling authorities to identify frequently affected areas and make data-driven urban planning decisions. SiliconSahaaya improves grievance resolution efficiency, reduces manual intervention, enhances transparency, and promotes smarter civic governance through AI-driven automation.
Keywords
Smart Governance, Civic Grievance System, Artificial Intelligence, XGBoost, YOLOv8, Sentiment Analysis, Smart Cities, Complaint Classification, GPS Tracking, Civic Analytics. Verification, Supabase, Android WebView, Web Application, IoT.
How to cite this paper
@article{1719436,
author = {Dr. J. Narendra Babu, Hemanth S, Ritesh Patil; Shrihari M Kulkarni, Siddaligayya K M; Sai Sadhguru, Saifullakhan; Sangamesh},
title = {SiliconSahaaya: An AI-Powered Smart Civic Grievance Management System},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {1},
pages = {462-468},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1719436.pdf},
abstract = {Rapid urbanization has significantly increased civic issues such as garbage overflow, potholes, drainage blockage, water leakage, broken streetlights, and road damage. Existing grievance management systems often suffer from poor complaint routing, delayed response mechanisms, lack of transparency, and dependency on manual department selection. These challenges reduce citizen satisfaction and create inefficiencies in public administration. To address these limitations, SiliconSahaaya, an AI-powered smart civic grievance management system, is proposed to automate the process of civic issue reporting and complaint resolution. The system enables citizens to register complaints through image uploads, GPS-based location detection, and mobile-friendly interfaces. By integrating Artificial Intelligence and Machine Learning techniques such as XGBoost, TF-IDF with Logistic Regression, TextBlob/VADER sentiment analysis, and YOLOv8 object detection, the platform intelligently analyzes complaints, predicts issue priority, categorizes civic problems, and automatically routes grievances to the relevant government departments. The proposed system also includes a React Native mobile application, real-time notifications using Firebase Cloud Messaging, SMS services through Twilio, email notifications using Nodemailer, and secure authentication using JWT and OTP verification. Furthermore, the platform integrates Leaflet.js-based geographic hotspot detection, enabling authorities to identify frequently affected areas and make data-driven urban planning decisions. SiliconSahaaya improves grievance resolution efficiency, reduces manual intervention, enhances transparency, and promotes smarter civic governance through AI-driven automation.},
keywords = {Smart Governance, Civic Grievance System, Artificial Intelligence, XGBoost, YOLOv8, Sentiment Analysis, Smart Cities, Complaint Classification, GPS Tracking, Civic Analytics. Verification, Supabase, Android WebView, Web Application, IoT.},
month = {July},
doi = {https://doi.org/10.64388/IREV10I1-1719436}
}