AI-Powered Smart Complaint Management System For Rural Area

Abstract

Efficient grievance redressal is critical for inclusive rural development in India. Traditional complaint systems often fail to address the volume and complexity of citizen feedback, especially in underserved rural communities. This paper presents an AI-powered complaint management system tailored for rural India, leveraging Natural Language Processing (NLP) and machine learning to ingest, analyze, classify, and resolve citizen complaints. The system integrates multimodal inputs (text, speech, images), preprocesses and enriches them in a Data Layer, and applies NLP/ML models in a core AI Detection Layer to extract issue categories and severity. A Classification Layer determines complaint priority (mild/moderate/severe), while a User Interface Layer (including mobile/web portals and voice interfaces) enables easy reporting. Explainable AI methods and visualization dashboards promote transparency, and a feedback loop supports continuous learning. In a case study for rural Maharashtra, the system demonstrated significant improvements: complaint resolution times decreased and classification accuracy exceeded 90%. This fully-developed system bridges the urban–rural digital divide by providing scalable, AIdriven grievance redressal with multilingual and low-connectivity