Machine Learning-Enabled Smart Transit: Real-Time Bus Tracking System for Enhanced Urban Mobility

This project focuses on developing a Machine Learning-Enabled Smart Transit Real-Time Bus Tracking System to improve urban mobility and passenger convenience. The main objective is to track bus location and predict bus availability based on predefined schedules. The system uses a Raspberry Pi integrated with GPS and GSM modules to collect location data and communicate information. Machine learning techniques are applied on preloaded timing and route data (stored in Excel) to predict bus availability at specific locations and times. An LCD is used to display system status, while a push button allows users to request bus information. Upon pressing the button, the system sends an SMS notification via the GSM module based on predicted availability. The results ensure accurate tracking and timely information delivery, helping passengers make better travel decisions. This system enhances public transport efficiency and can be widely used in smart city applications.