Abstract:
Getting and renewing monthly bus tickets by traditional means demands a long waiting
period because people have to queue up while the system operates during limited hours. The
current inefficiencies become worse due to the absence of both real-time support and an
adaptable intelligent system. An Online Monthly Bus Ticketing System linked to a Chatbot
system serves users by processing natural language input through Named Entity Recognition
(NER) and deep learning response generation.
A system using Python as its backend whereas the prototype operated through command-line
interface (CLI). Structured data extraction such as source, destination and travel date can be
performed by the BERT + LSTM encoder-decoder based chatbot system from unstructured
user input. The project team deleted payment gateway integration together with route selection
functionality when data availability along with resource constraints emerged. The existing
system operates with English queries to generate ticket fares through location-based distance
calculation using a simple formula.
The implemented system cut booking time ranges from 90% reduction to the point where users
saw positive results in 85% of survey responses while maintaining 92% accurate query
processing. User assessment results show that the automated system possesses strong
capabilities to boost monthly ticket booking efficiency and accessibility through its approach
which combines intelligent automation with user-friendly interfaces.
