CIVICMIND: AI-Driven Embedded Grievances Logging System

Abstract

Public grievance redressal systems play a crucial role in maintaining transparent and responsive governance. However, existing methods including written forms, phone calls, and even web or mobile applications often depend on manual input, lack intelligent prioritization, and fail to provide real-time updates. These limitations result in delayed responses, poor complaint tracking, and reduced citizen satisfaction. The proposed system, Civicmind: An Ai-Driven Embedded Grievances Logging System, introduces an innovative approach by integrating Artificial Intelligence (AI) with an IoT-based embedded framework. The system employs an ESP32 microcontroller, I2S microphone, GPS module, and OLED display to enable users to log verbal complaints conveniently in real time. The recorded data is securely stored on a microSD card and analyzed using Natural Language Processing (NLP) algorithms to evaluate the content’s urgency and assign a risk score. High-risk grievances are automatically highlighted and forwarded to relevant authorities through email alerts. A web-based dashboard further enhances the system by providing visualization, geospatial mapping, and analytical insights for administrators. This ensures faster decision-making, efficient resource allocation, and improved accountability. By combining IoT, AI, and automation, CIVICMIND aims to create a smart, transparent, and citizen-centric grievance management system that bridges the gap between the public and governing bodies.