Mobility ChatBot: supporting decision making in mobility data with chatbots

Lorenzo Padoan, Margherita Cesetti, Luca Brunello, Marco Antonelli, Bruno Zamengo, Francesco Silvestri

Abstract: This paper presents an innovative chatbot architecture designed to support decision-making in the context of mobility data, leveraging recent advancements in Large Language Models (LLMs). As transportation systems and location-based services produce more data, understanding human mobility patterns and providing relevant insights becomes critical for effective decision-making. The chatbot aims to offer a user-friendly tool that allows users to interact with mobility datasets through natural language, preventing the end user from writing complex SQL queries and allowing them to create data visualization on the fly.