Intelligent Bus Application for Smart City based on LoRa Technology and RBF Neural Network

Abstract

Nowadays smart transportation is one of the most important smart city applications for all the facilities it provides, as well, achieves green transportation. One of these applications include bus monitoring systems for schools and universities. This paper proposes an integrated bus tracking and monitoring system using Internet of Things (IoT) mainly LoRa technology for Islamic University of Lebanon (IUL) to ease the bus issue that comprises a barrier for good service. In the proposed system, we have implemented a case study to monitor the position, speed, humidity and temperature of IUL shuttle buses. In addition to the tracking, a prediction algorithm is implemented for computation of the arrival time of the bus to the Wardanieh campus. The estimation is based on artificial intelligence neural network mainly the Radial Basis Function (RBF) algorithms for the sake of finding the predicted time of arrival in different locations and scenarios starting from Khaldeh campus to the Wardanieh campus. The collected data are instantly shown on a user interface for monitoring, whereas the exact location and arrival time of the bus will be displayed on an android application for students. Results show that the arrival estimated time error is about 0.18%.