Smart Enquiry Chatbot Using Ann And Nlp For Locomotives

Abstract

The railway sector is the major transportation network, catering. Due to the demand of efficient and personalized customer support, classical systems often don’t match with people’s expectations. This research targets to develop a Railway Enquiry chatbot by Artificial Neural Networks (ANN) and Natural Language Toolkit (NLTK), It aims to design an intuitive, efficient, and user-friendly interface for answering passenger queries. This chatbot uses NLTK for natural language processing tasks, such as tokenization, stemming, and intent recognition, ensuringaccurateunderstandingofuserinputs.ANN classifies and generates the responses, providing a continuous interaction. The major functions of this chatbot are ticket availability checks, train schedule inquiries, platform details, and fare estimations. The system utilizes a curated and preprocessed dataset comprising frequently asked railway-related questions and their corresponding answers, ensuring it addresses a wide spectrum of user inquiries. A supervised learning approach is applied to train the Artificial Neural Network (ANN) model, enabling it to accurately identify user intent and deliver appropriate responses. The model's performance is assessed using metrics such as accuracy, precision, recall, and F1-score, all of which affirm its reliability in providing correct information. The chatbot is implemented through a web-based interface, allowing users to conveniently obtain railway-related details. By automating standard queries, the system minimizes reliance on human customer service, thereby improving overall passenger experience. This study underscores the transformative role of ANN and Natural Language Processing (NLP) in modernizing support systems within the railway industry.