Abstract
There is a rise in the need for urban transportation, which has created new problems regarding the management of parking spaces and has also increased congestion, pollution , and stress levels of drivers. This study suggests the creation of an intelligent parking system based on the imputation of UK postcode and time. Artificial Intelligence and real-time information updates through Firebase. Using data-driven methods like Random Forest and XGBoost, the model predicts available parking space and suggests the nearest free spot to park through a Flask-based API connected to a web dashboard showing Google Maps that provides visual routing and Firebase to handle the real-time updates. The Random Forest achieved performance accuracy of 92% while XGBoost achieved 87%. This study seeks to improve mobility and optimise the utilisation of parking spaces by minimising idle driving time. A hybrid approach of a combination of data analytics, system design, and user-centred testing is employed. 1 The outcome is to contribute practical insights and a prototype solution that is in line with smart city initiatives and contemporary digital transformation in transportation.