An Integrated Processing Platform for Traffic Sensor Data and Its Applications in Intelligent Transportation Systems
Zhuofeng Zhao, Jun Fang, Weilong Ding, Jianwu Wang · 2014
With the continuous expansion of the scope of traffic sensor networks, traffic sensor data becomes widely available and large in amount. Traffic sensor data gathered by large amounts of sensors shows the massive, continuous, streaming and spatio-temporal characteristics compared to traditional traffic data. In order to satisfy the requirements of different applications in Intelligent Transportation Systems (ITS), we need to have the capability of real-time processing over both streaming and historical traffic sensor data. In this paper, we present DeCloud4SD, an integrated processing platform for traffic sensor data, which is designed to provide services for receiving, storing, acquiring and computing traffic sensor data in a scalable architecture with real-time guarantee. Three types of applications using DeCloud4SD in a real ITS project are also described in detail. Through the analysis of these applications, we can see that DeCloud4SD can ensure: 1) scalable and customizable traffic sensor data gathering and computing, 2) rapid application development and deployment using a MapReduce-like model, 3) seamless integration with existing relational data sources and applications.