Schuman Min Shao

Stream Processing Based Intelligent Transport Systems

In this paper, we present a Fleet Management Center application implemented using a stream processing infrastructure we call System S. System S enables the deployment of large scale applications with mechanisms for sharing multi-party data sources, software components, and even intermediate results. This approach significantly reduces the cost of software integration, and ownership, the major factor in Intelligent Transportation Systems. In addition, the system includes an adaptive data source management that determines the list of relevant data sources based on the current locations of the entities monitored or managed by the applications.

Data Stream Processing Infrastructure for Intelligent Transport Systems

Intelligence Transportation Systems are critical to improve the efficiency of modern transportation. A system that is flexible and powerful enough to handle diverse demands from a large user base, is still elusive. Studies have shown that developing and integrating the various components constitute a significant portion of the capital cost and complexity of such systems. In this paper, we present a stream processing infrastructure we call System S. System S enables the deployment of large scale applications. It supports a mechanism for sharing data sources, software components, and even intermediate results allowing a reduction in the cost of software integration, and ownership. We experiment the stream processing infrastructure with a Fleet Management Center, and demonstrate how the infrastructure can be used to address unique issues in traffic management.