Bus Enquiry Chatbot for Transportation System with Voice Support and Emergency Assistance Using NLP
Year: 2025
Type: article
Abstract: A web-based chatbot system specifically designed for bus transport services, aimed at assisting passengers with real-time travel-related information. The system leverages Natural Language Processing (NLP) to understand and process user queries, enabling it to provide accurate responses regarding bus schedules, routes, and fare details. To ensure accessibility and ease of use, the chatbot includes a voice interaction feature that allows users to communicate through spoken commands, making it especially helpful for individuals with visual or literacy limitations. A unique feature of this chatbot is its built-in emergency assistance functionality. The chatbot’s intelligence is powered by a Convolutional Neural Network (CNN) model trained on transportation-specific datasets, ensuring precise interpretation of user input. By combining intelligent response generation, multi-modal communication, and emergency support, the system not only reduces the dependency on manual information desks but also promotes a smarter, safer, and more user-friendly public transportation experience. KEYWORDS: Chatbot, Natural Language Processing (NLP), Voice Interaction, Bus Enquiry System, Emergency Assistance, Convolutional Neural Network (CNN), Public Transportation, Intelligent System.
DOI: 10.55041/ijsrem44454
Authors: S Mohammad Rafee, R Ramya Sri
Institution: Sri Guru Gobind Singh College
Language: English
Topic: AI in Service Interactions
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4409396810