Intelligent Navigation Assistant for Campuses Using Speech Recognition, NLP And A* Algorithm

Campus navigation often produce challenges for students, staff, and visitors, specifically in large complex. This research presents an intelligent navigation assistant that combines automatic speech recognition (ASR), Natural Language Processing (NLP), and the A* pathfinding algorithm to tackle these issues through voice interaction. Users can naturally voice their destination queries, which the system converts into text using speech recognition techniques. Then, NLP processes the text to identify intent and relevant entities, which improves the understanding of user commands. The A* algorithm calculates the shortest path on a digital campus map and ensures effective route planning. Experimental evaluation shows high accuracy in speech-to-text conversion, effective command interpretation using NLP, and better navigation efficiency than traditional systems. This intelligent assistant improves user accessibility and convenience by providing a practical solution for hands-free campus navigation. Future work will focus on improving noise resistance, expanding language support, and integrating real-time location updates.