AI-Powered Framework for Enhancing E-Government Service Automation

The advancement of digital governance has heightened the demand for effective, transparent, and citizen focused service delivery. This initiative introduces an AI-driven framework that utilizes various deep learning techniques to automate and improve E-Government services. To achieve this, the research integrates several methodologies incorporated such as Convolutional Neural Network (CNN) for recognizing digits in scanned or uploaded documents, Natural Language Processing (NLP) models for assessing sentiment from citizen text inputs, and a Facial Emotion Recognition (FER) model for detecting emotions through user images. This multi-modal architecture facilitates intelligent and context-sensitive decision making, enabling adaptive responses based on both visual and textual feedback from users. By automating tasks such as form validation, complaint analysis, and emotional feedback detection, the suggested framework greatly diminishes the need for manual involvement and enhances the responsiveness of digital public services.