NESTIFY: AN INTELLIGENT STUDENT HOUSING DISCOVERY SYSTEM USING MERN STACK AND GENAI-DRIVEN GEOSPATIAL ANALYSIS

The rapid expansion of urban student populations has intensified challenges in discovering safe, affordable, and context-aware housing solutions, with female students facing heightened safety and accessibility concerns.Conventional accommodation platforms rely on static listings and manual filtering, resulting in low personalization and inefficient decision-making.This study proposes Nestify, an intelligent student housing recommendation framework that leverages Generative Artificial Intelligence (GenAI) and deep learning to automate Paying Guest (PG) accommodation matching.The system is implemented using the MERN stack and integrates LangChain-based natural language processing to extract semantic user preferences from unstructured inputs.Additionally, real-time geospatial analysis using the Google Maps API enables proximitybased optimization relative to educational institutions and essential services.Empirical results indicate that the proposed approach significantly enhances recommendation accuracy and user satisfaction while reducing search complexity.Nestify demonstrates the potential of AI-driven recommendation systems in addressing critical challenges within student housing ecosystems.