Author: Süleyman EKEN, Ahmet SAYAR
Publishing Date: 2014
Volume: 2 Issue: 1
Maps are widely used tools for visualization, interpretation and analysis of geographic and spatial data. People use maps for finding directions and addresses in everyday life. There are various disciplines and eras of map use such as earthquake research, homeland security and early warning systems. Many people using public transport buses experience time losses because of waitings at bus stops. In this study, we propose a web based system to forecast bus arrival times in an intelligent way. The system enables public transport users to schedule their times more efficiently by reducing their waiting times at bus stops. Users can pull the information about bus arrival times and corresponding routes by using web browsers interactively, or if they are registered to the system, they can be informed about routes and bus arrival times via SMS and e-mails. Efficiency of the system has been tested and proved on various scenarios and synthetic data.
Key Words: Smart bus stops, Naïve Bayes classification, machine learning, maps