VehiWalnut: Smart Fuel Management with Real-Time Data and User Interaction

Abstract

This research paper examines the creation and execution of VehiWalnut, a cutting-edge system developed to enhance fuel management processes. VehiWalnut incorporates cutting-edge technologies such as data visualization, cloud-based chatbot evaluation, and deep learning to improve efficiency and user satisfaction. A thorough literature review is conducted to identify important studies in data visualization, Web API analysis, chatbot performance evaluation, and deep learning techniques for machine learning chatbots. These studies are then combined to form the basis of the research. The text describes the development of VehiWalnut, emphasizing its diverse functionalities and the use of the Python programming language for its implementation. The system allows users to enter fuel fill-up data through WhatsApp messages, which are processed using regular expressions to extract and insert the data into a SQLite database. VehiWalnut allows users to request detailed reports on fuel expenses, timing of fuel refills, predictions for the next refill date, and other related information. The system’s effectiveness is assessed by conducting case studies and performance evaluations, showcasing its capacity to enhance fuel management procedures for individual and commercial users. The research findings offer valuable insights into incorporating advanced technologies to improve fuel management systems, thereby paving the way for future advancements in this domain.