AI -Driven Query Management and Issue Resolution System for Smart Villages

Rural regions across India were confronted with persistent challenges in grievance redressal due to poor infrastructure, low digital literacy, and limited administrative responsiveness. Existing manual processes, such as handwritten complaint logs and toll-free helplines, were found to lack transparency and efficiency. In this work, an AI-Driven Query Management and Issue Resolution System for Smart Villages was presented as an intelligent web-based platform through which villagers were enabled to register, track, and resolve grievances efficiently. Lightweight artificial intelligence models were integrated to automate query handling and to enhance decision-making. DistilBERT was employed for semantic classification and prioritization of textual complaints, while EfficientN et was applied for image-based verification and categorization of uploaded visual evidence. Siamese neural networks were proposed for detecting duplicate queries, and FastText embeddings were explored for multilingual scalability in low-resource environments. Together, these models were shown to form an adaptive framework that improved administrative efficiency, ensured transparency, and empowered rural citizens through accessible, AI -enhanced governance. The proposed approach was demonstrated to show how lightweight deep learning could transform rural complaint management into a faster, fairer, and more inclusive process.